乌鸦传媒 Switzerland 乌鸦传媒 Switzerland Tue, 16 Dec 2025 10:35:55 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.3 /ch-en/wp-content/uploads/sites/44/2025/10/cropped-乌鸦传媒_spade_32x32.png?w=32 乌鸦传媒 Switzerland 32 32 219864080 From ambition to impact: How agentic AI and data foundations are transforming public services /ch-en/insights/expert-perspectives/from-ambition-to-impact-how-agentic-ai-and-data-foundations-are-transforming-public-services/ /ch-en/insights/expert-perspectives/from-ambition-to-impact-how-agentic-ai-and-data-foundations-are-transforming-public-services/#respond Sun, 23 Nov 2025 15:54:33 +0000 /ch-en/?p=555176&preview=true&preview_id=555176

From ambition to impact: How agentic AI and data foundations are transforming public services

Jon Harriman
23 Oct 2025

In today鈥檚 evolving public sector landscape, the demand for efficient, transparent, and citizen-centric services has never been greater.

As per 乌鸦传媒 Research Institute鈥檚 recent report 鈥 鈥64% of public sector organizations are already exploring or actively working on Generative AI initiatives, with 90% planning to explore, pilot, or implement agentic AI within the next 2鈥3 years.鈥 The partnership between 乌鸦传媒 and ServiceNow offers a powerful response to this challenge – combining cutting-edge technology with deep transformation expertise to reimagine how public services are delivered and experienced.

This blog explores how agentic artificial intelligence (AI) is reshaping both employee and citizen experiences, and why 乌鸦传媒 and ServiceNow are uniquely positioned to lead this transformation.

Introducing Agentic AI: From Reactive to Proactive

Unlike traditional AI, which responds to prompts, agentic AI takes initiative. Only 21% of public sector organizations have moved to pilots or actual deployment of Gen AI, and just 6% have put Gen AI into production – highlighting the gap between ambition and execution. Agentic AI can plan, decide, and act autonomously to achieve goals – without needing step-by-step instructions. In a public sector context, this means:

  • Proactive Service Delivery: Identifying issues before they escalate and resolving them autonomously.
  • Autonomous Task Management: Coordinating multi-step workflows across departments.
  • Enhanced Decision-Making: Synthesizing data to support faster, more informed actions.
  • Human-Centric Design: Freeing employees from repetitive tasks so they can focus on meaningful work.

Empowering Public Sector Employees

乌鸦传媒 and ServiceNow are helping public sector organisations create intelligent, efficient, and engaging employee experiences:

  • Automating Routine Tasks: ServiceNow鈥檚 AI automates repetitive processes; 乌鸦传媒 tailors these to maximise impact.
  • Predictive Analytics: ServiceNow predicts incidents; 乌鸦传媒 helps interpret and act on the data.
  • Personalized Support: ServiceNow delivers tailored experiences; 乌鸦传媒 ensures they are intuitive and inclusive.
  • Continuous Improvement: ServiceNow gathers feedback; 乌鸦传媒 drives adoption and iteration.

Together, they enable public sector teams to work smarter, not harder – boosting engagement, reducing attrition, and improving service delivery. Less than 25% of public sector organizations report high maturity in any aspect of data readiness, including infrastructure, skills, and governance.

Elevating the Citizen Experience

Agentic AI isn鈥檛 just transforming internal operations – it鈥檚 revolutionising how citizens interact with public services. Here are some of the most impactful use cases:

  • Healthcare Access: AI agents can schedule GP appointments, send reminders, and triage symptoms – reducing wait times, no-shows and improving outcomes.
  • Tax and Benefits Support: AI can resolve tax queries, track welfare applications, and proactively update citizens for better engagement and faster resolutions.
  • Local Services: From reporting potholes to graffiti removal, agentic AI can log, route, and track issues across departments – ensuring faster resolution and better community relations.
  • Permit and Licence Management: AI can guide citizens through applications for parking permits, business licences, or event permissions – ensuring compliance and ease.
  • Education and School Services: Parents can apply for school places, track transport eligibility, or manage special education needs – all through AI-guided workflows.
  • Public Safety and Crisis Response: AI can coordinate emergency logistics, notify citizens, and track resource deployment in real time.

These capabilities not only improve satisfaction but also build trust in public institutions. Only 25% of citizens are satisfied with customer service from government agencies – Gen AI-powered virtual assistants can help bridge this gap.

Looking Ahead: The Future of Public Sector AI

As AI continues to evolve, agentic AI will play a pivotal role in shaping adaptive, intelligent, and human-centric public services. 乌鸦传媒 and ServiceNow are at the forefront of this shift – empowering organisations to deliver experiences that are not only efficient but also empathetic and inclusive.

By embracing agentic AI, public sector organisations can unlock new levels of autonomy, innovation, and impact – while keeping humans in the loop to provide oversight, context, and judgement – ensuring both their people and their citizens are equipped to thrive in the digital age. 67% of public sector organizations are falling behind in their efforts to build data mastery – highlighting the urgency to invest in foundational capabilities.

Real-World Impact: Case Studies
  • Healthcare: A Healthcare trust is working with ServiceNow and 乌鸦传媒 to enhance HR service delivery. By automating routine HR tasks and providing personalised support, the hospital improved engagement, reduced turnover, and enabled staff to focus on patient care. The UK NHS is rolling out an AI tool that predicts patient falls with 97% accuracy, potentially preventing 2,000 hospital admissions daily and saving 拢2 billion annually.
  • Local Government: A council used ServiceNow鈥檚 AI to automate IT service management. With 乌鸦传媒鈥檚 support, the council reduced incident resolution times by 40%, improved employee satisfaction, and achieved significant cost savings.
  • Defence Sector: By leveraging the ServiceNow platform, the defence sector is building a centralised Service Management layer that unifies HR, Finance, and Commercial functions. With an intuitive, consumer-grade user experience and a single shared services model, departments can work seamlessly together. Orchestration and AI capabilities add further value, streamlining complex processes and enabling faster, smarter decision-making to strengthen resilience and operational efficiency.

Author

Jon Harriman

Jon Harriman

Group Offer Lead 鈥 People Experience
Jon is a renowned expert in employee experience, leveraging his role as the People Experience Group Offer Leader at 乌鸦传媒 to drive organizational success through people-centric approaches. With an extensive and diverse background encompassing roles in portfolio and offer development, pre-sales, solutioning, and delivery, coupled with a fervor for transforming how companies cultivate their workforce, Jon is committed to empowering organizations to establish engaging environments for their employees.
    ]]>     /ch-en/insights/expert-perspectives/from-ambition-to-impact-how-agentic-ai-and-data-foundations-are-transforming-public-services/feed/ 0 555176     Softwarization: How to turn technology into business value /ch-en/insights/expert-perspectives/softwarization-how-to-turn-technology-into-business-value/ /ch-en/insights/expert-perspectives/softwarization-how-to-turn-technology-into-business-value/#respond Tue, 18 Nov 2025 12:44:32 +0000 /ch-en/?p=554600&preview=true&preview_id=554600

    Softwarization: How to turn technology into business value

    G眉nther Reimann
    Nov 18, 2025
    capgemini-invent

    How can organizations harness Softwarization鈥檚 potential while navigating the challenges it brings?

    Softwarization is reshaping how value is created, how quickly it reaches the market, and how deeply technology permeates every function. Organizations expect software-based revenue to grow to nearly 30% by 2030, a clear sign that software is no longer just an enabler, but a core driver of business models.

    In the age of Techceleration, the business landscape is undergoing a profound transformation. Accelerated by AI, cloud computing, and Pervasive Tech, software has moved from being a support function to becoming a core driver of value across every industry. 

    This shift, known as Softwarization, marks a fundamental change in how organizations operate and compete. As clients across industries embrace software-defined products and services, their operating models, risk strategies, and delivery partnerships must also evolve. Executives increasingly expect future revenues to be driven by digital solutions. This expectation prompts the question: How should organizations structure, secure, and scale to meet this new reality? 

    Softwarization marks a fundamental shift toward software-defined products, platforms, and services. But it is important to note that Softwarization is not just a target state; it鈥檚 a process of continuous transformation. Organizations must embrace change. This often means reimagining how they build trust, structure operating models, and deliver software. Softwarization is a critical enabler for organizations navigating the shift toward software-first strategies.

    This blog looks at three pillars of Softwarization:

    Softwarization How to turn technology into business value infographic 1
    Each of these pillars plays a key role in helping organizations navigate and succeed in a world increasingly shaped by software-first strategies.

    Trust as a business promise 

    Trust is a cornerstone of business success, earned through consistency, transparency and accountability. In the context of Softwarization, trust goes beyond simply compliance. It becomes a business promise: a core principle that underpins every digital interaction, transaction, and relationship. As organizations digitize more of their operations, the risks associated with cyberattacks, data breaches, and AI bias grow exponentially. Customers, employees, and partners expect robust cybersecurity. But they also expect transparency, ethical use of data, and resilience in the face of disruption. 

    Digital trust encompasses several interconnected pillars: cybersecurity, compliance, end-to-end risk management, resilience, and the fight against fraud. These are concerns that extend beyond the IT department, they are important throughout the business. For example, compliance with regulations such as GDPR (General Data Protection Regulation) is not only about avoiding fines but about building confidence with customers. Similarly, ethical AI practices are essential for maintaining trust as AI becomes more pervasive in decision-making. 

    Softwarization How to turn technology into business value infographic 2

    There are a huge number of opportunities for those who get trust right. By fostering a culture of trust and deploying state-of-the-art cybersecurity solutions, businesses can achieve stronger resilience, better incident detection, and enhanced business continuity. However, the challenges are real. Confidence in technology can be fragile, and incidents of cyberattacks or AI bias can quickly erode hard-won trust. 

    Organizations need to embed trust across the operating model, from secure architecture and risk management to transparent communication and continuous education. They should also treat trust as a differentiator: organizations that can demonstrate their trustworthiness win and retain customers. 

    Performant operating model 

    If trust is the foundation, the operating model is the engine that drives value from Softwarization. Traditional, functionally siloed IT can鈥檛 keep pace with Techceleration. A new approach is required, agile, product centric, outcome driven. 

    At its core, a performant operating model empowers cross-functional product teams, simplifies governance, and attracts digital talent. It is designed to break down silos, foster collaboration between business and IT, and accelerate time-to-market for new products and services. 

    A product-centric IT operating model aligns business and IT around end-to-end journeys, focusing on customer, employee and strategic outcomes, and supporting ongoing software modernization. This alignment is about efficiency and unlocking innovation, deepening customer relationships, and creating new revenue streams. Key components are adaptive governance, just-enough architecture, and data-driven portfolio management. 

    However, this transformation is not easy. The journey to a performant operating model requires careful change-management, a willingness to experiment, and a commitment to continuous improvement. Organizations must balance autonomy with alignment, manage complexity, and ensure accountability at every level. 

    Recommendations for implementation include: 

    • Starting with pilot product teams to test new ways of working. 
    • Iterating based on data and feedback. 
    • Establishing a transformation capability 鈥 such as a Value Realization Office 鈥 to scale successful pilots. 
    • Leveraging a digital factory to incubate new digital culture and operating models. 

    Augmented software house 

    An augmented software house is a collaborative approach for software development that combines business and IT teams with advanced tools, applications, and practices 鈥 like AI, automation, and platform engineering 鈥 to deliver high-quality software faster and more efficiently.  

    As software becomes the primary source of competitive advantage, excellence in software delivery is no longer optional. An augmented software house brings together operating model, platform engineering, CI/CD (continuous integration/continuous delivery) pipelines, and AI-enhanced developer experience. It is built on partnership, shared objectives, and a commitment to continuous transformation. 

    What sets an augmented software house apart is its ability to unite client and partner teams through joint management, fostering shared business objectives and mutual risk ownership. It also stands out by leveraging state-of-the-art sourcing models, accelerators, and continuous improvement cycles. An augmented software house also maintains a sharp focus on delivering business value through adaptive architecture and cultivating an effective agile and DevOps culture. 

    Opportunities include: 

    • Maximizing value delivered to the business. 
    • Achieving higher productivity and software quality. 
    • Building the capacity to keep pace with rapid technological evolution. 

    However, alongside these opportunities are challenges, particularly in building the right partnerships, maintaining flexibility, and adapting experience. There is no one-size-fits-all blueprint; success depends on the ability to learn, adapt, and co-create value. 

    In practice, organizations are advised to: 

    • Define a joint management cockpit to oversee the software house. 
    • Commit to shared business objectives and transparent measurements. 
    • Invest in software excellence assets and accelerators. 
    • Continuously measure and adapt based on business impact. 

    As technology becomes ever more pervasive, the winners will be those who can build trust as a business promise, operate with agility and performance, and deliver software excellence through augmented, collaborative models.

    Software excellence is a leadership choice

    Enterprises that treat software as a core business capability will outpace those that treat it as a cost center. This requires re-architecting operations, driving software modernization, making trust tangible for customers and regulators, and fostering augmented partnerships that continuously learn and evolve. Softwarization is here, the question is whether your organization will turn it into your advantage.

    Meet our experts

    G眉nther Reimann

    G眉nther Reimann

    Vice President, Global Head of Inventive & Sustainable IT
    G眉nther Reimann is practical strategist for business technology and digitization with over 20 years of experience. G眉nther drives client growth through purpose-led IT transformation, competitive capabilities, and innovation. Leading Germany鈥檚 Business Technology portfolio and Inventive & Sustainable IT globally, he champions resilient tech and the strategic acceleration of the digital (r)evolution.

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      FAQs

      What is Softwarization in simple terms?

      Softwarization is the shift toward software-defined products, platforms, and services. It enables agility, scalability, and innovation by replacing rigid hardware with flexible, programmable solutions.

      The main advantages of softwarization include improved scalability, cost efficiency, and flexibility. It supports software modernization and orchestration, driving digital transformation across industries.

      Software augmentation uses AI and automation to enhance human decision-making. It complements software transformation and software modernization by improving productivity without replacing existing systems.

      A business can start using software effectively by modernising legacy systems, adopting cloud-native platforms, and leveraging orchestration tools for seamless integration and automation.

      Stay informed

      Subscribe to get notified about the latest articles and reports from our experts at 乌鸦传媒 Invent

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      ]]>       /ch-en/insights/expert-perspectives/softwarization-how-to-turn-technology-into-business-value/feed/ 0 554600       From reactive to resolution: How agentic AI is redefining Customer and Employee Experience /ch-en/insights/expert-perspectives/from-reactive-to-resolution-how-agentic-ai-is-redefining-customer-and-employee-experience/ /ch-en/insights/expert-perspectives/from-reactive-to-resolution-how-agentic-ai-is-redefining-customer-and-employee-experience/#respond Mon, 03 Nov 2025 10:29:55 +0000 /ch-en/?p=555251&preview=true&preview_id=555251

      From reactive to resolution: How agentic AI is redefining Customer and Employee Experience

      Jon Harriman
      3 Nov 2025

      In today鈥檚 experience-driven economy, customers expect fast, personalized service, and employees demand frictionless, consumer-grade digital experiences. Yet many organizations still rely on siloed systems and manual processes that fall short.

      According to 乌鸦传媒 Research Institute (CRI) report, agentic AI could generate up to $450 billion in economic value by 2028, transforming how organizations operate across industries.

      乌鸦传媒, in partnership with ServiceNow, is changing that 鈥 by harnessing the power of agentic AI to reimagine both customer experience (CX) and people experience (PX). Unlike traditional AI-assist tools that merely suggest next steps, agentic AI is autonomous, goal-driven, and capable of reasoning, planning, and acting across systems to deliver outcomes 鈥 not just recommendations.

      This shift moves service from interaction-first to resolution-first, focusing on solving problems entirely, not just logging them. It鈥檚 a fundamental change in how organizations approach both customer and employee service.

      From reactive to proactive

      Traditional CRM systems are designed to log and route issues 鈥 not resolve them. Customers often find themselves repeating their problems to multiple agents, while service teams struggle to navigate disconnected systems.  乌鸦传媒鈥檚 CX with ServiceNow flips this model by putting resolution at the core. 乌鸦传媒鈥檚 research shows that customer service and sales are among the functions with the fastest wins from agentic AI thanks to their well-defined processes and measurable outcomes.

      Agentic AI enables:

      • End-to-end workflow orchestration across IT, supply chain, finance, and field service
      • Predictive case management that detects and resolves issues before customers even notice
      • Self-healing automation that eliminates repetitive escalations and reduces agent workload.

      For example, in utilities, outage detection can trigger automated crew scheduling, customer notifications, and supply chain updates 鈥 all before the first call is answered.

      The results speak for themselves, according to the research paper, :

      • 30-50% faster resolution times
      • 20% reduction in call abandonment
      • 40% drop in escalations
      • 25% higher CSAT

      Crucially, CX with ServiceNow integrates with existing CRM and CSM platforms like Salesforce, Microsoft Dynamics, and Zendesk, extending their capabilities rather than replacing them. This protects previous technology investments while unlocking resolution-focused, AI-powered workflows.

      Agentic AI not only ensures ServiceNow works correctly (in-system testing) but also orchestrates workflows across integrated platforms like Salesforce and Microsoft Dynamics 鈥 enabling seamless resolution across systems.

      Moments that matter: Agentic AI in people experience

      Many organizations still rely on fragmented systems and manual processes that slow productivity and frustrate employees.

      乌鸦传媒鈥檚 PX with ServiceNow transforms the employee journey by delivering moments that matter 鈥 powered by agentic AI. These are the pivotal points in an employee鈥檚 working life where experience has the greatest impact: onboarding, development, day-to-day work, getting support, and offboarding. By orchestrating these moments with intelligent automation, organizations can create seamless, personalized experiences that boost satisfaction, productivity, and retention.

      Key capabilities include the following:

      • Automated onboarding: New hires receive equipment, access, and training on day one 鈥 without HR or IT chasing multiple departments.
      • Contextual guidance: Agentic AI surfaces help and automates actions to reduce repetitive clicks and improve adoption.
      • Unified self-service: Employees can access HR, IT, and workplace services from a single portal, without needing to know which system to use.

      PX with ServiceNow complements existing Human Capital Management (HCM) systems and IT Service Management tools 鈥 avoiding 鈥渞ip and replace鈥 鈥 and orchestrates workflows across them so employees simply request what they need and the system takes care of the rest.

      This isn鈥檛 just about convenience; it鈥檚 about impact. According to 乌鸦传媒 Research Institute, , organizations that focus on employee experience see:

      • 21% improvement in profitability
      • 17% increase in productivity
      • 20% increase in sales.

      These gains translate into higher talent retention, reduced absenteeism, and faster onboarding 鈥 all critical in today鈥檚 competitive talent landscape.

      Why 乌鸦传媒 and ServiceNow?

      乌鸦传媒 is a globally recognized ServiceNow Elite Partner, offering deep expertise across IT Service Management (ITSM), Human Resources (HR), and Customer Experience (CX). With over 600 successful ServiceNow engagements and a workforce holding more than 12,000 certifications and accreditations, we deliver the scale, experience, and innovation required to implement agentic AI solutions that drive real business outcomes.

      Our delivery model is outcome-led and human-centered, combining industry-specific workflows, AI-powered automation, and change management to drive adoption and measurable results. Whether you鈥檙e looking to transform customer service, reimagine the employee journey, or unify service delivery across departments, 乌鸦传媒 and ServiceNow provide the tools, talent, and vision to make it happen. Only one-third of organizations understand where to deploy AI agents, underscoring the need for strategic guidance from partners like 乌鸦传媒 and ServiceNow. This joint approach is validated by CRI findings: 62% of organizations prefer partnerships with solution providers and system integrators to deploy AI agents effectively.

      As organizations scale agentic AI, ethical and safety risks become critical. 乌鸦传媒鈥檚 governance frameworks proactively address concerns around bias, transparency, and data privacy – ensuring responsible AI adoption. 乌鸦传媒鈥檚 RAISE accelerator offers pre-built AI agents, orchestration tools, and low-code platforms – designed to scale agentic AI across industries and domains.

      Ready to experience the future?

      乌鸦传媒 calls this synergy 鈥Human-AI collaboration鈥- a model where AI agents and human teams collaborate seamlessly to elevate outcomes, creativity, and satisfaction. Discover how agentic AI can help you move from reactive service models to proactive, outcome-driven experiences 鈥 for your customers and your people.

      Book your exclusive PX or CX Living Lab session today and see how leading organizations are transforming service and experience with agentic AI.

      Let鈥檚 create moments that matter 鈥 together and make it real.



      Author

      Jon Harriman

      Jon Harriman

      Group Offer Lead 鈥 People Experience
      Jon is a renowned expert in employee experience, leveraging his role as the People Experience Group Offer Leader at 乌鸦传媒 to drive organizational success through people-centric approaches. With an extensive and diverse background encompassing roles in portfolio and offer development, pre-sales, solutioning, and delivery, coupled with a fervor for transforming how companies cultivate their workforce, Jon is committed to empowering organizations to establish engaging environments for their employees.
        ]]>         /ch-en/insights/expert-perspectives/from-reactive-to-resolution-how-agentic-ai-is-redefining-customer-and-employee-experience/feed/ 0 555251         The 乌鸦传媒 Emission Experience Centre 鈥 The Place to Collaborate and Co-Innovate /ch-en/insights/expert-perspectives/the-capgemini-emission-experience-centre-the-place-to-collaborate-and-co-innovate/ /ch-en/insights/expert-perspectives/the-capgemini-emission-experience-centre-the-place-to-collaborate-and-co-innovate/#respond Fri, 31 Oct 2025 10:09:00 +0000 /ch-en/?p=555247&preview=true&preview_id=555247

        The 乌鸦传媒 Emission Experience Centre – The Place to Collaborate and Co-Innovate

        Claire Gauthier
        Oct 31, 2025

        Tackling the uniquely complex challenges inherent in the energy industry鈥檚 efforts to reduce CO2 emissions requires collaboration on a scope and scale unseen in the sector鈥檚 long history

        But in a famously competitive environment, there is growing appreciation that working together in a common cause not only makes commercial sense, it also provides the best opportunity to develop world-class emission management solutions. When applied consistently and transparently, these solutions can deliver game changing results for the industry, society and our planet.

        In this first of a short series of white papers, we set out 乌鸦传媒鈥檚 vision for global collaboration and co-innovation and the ecosystem in which it can be achieved. We explain the importance of achieving early consensus on the challenges we face, our collective aspirations for the future, and what the roadmap for action should look like.

        Subsequent white papers will summarize the results of an in-depth industry feasibility study and provide more detail on how, together, we will deliver our shared vision and the benefits we expect to unlock. Most importantly we hope that colleagues and the industry will join us on this journey, adding their voices, skills and experience to this global effort.

        But in a famously competitive environment, there is growing appreciation that working together in a common cause not only makes commercial sense, it also provides the best opportunity to develop world-class emission management solutions. When applied consistently and transparently, these solutions can deliver game changing results for the industry, society and our planet.

        In this first of a short series of white papers, we set out 乌鸦传媒鈥檚 vision for global collaboration and co-innovation and the ecosystem in which it can be achieved. We explain the importance of achieving early consensus on the challenges we face, our collective aspirations for the future, and what the roadmap for action should look like.

        Subsequent white papers will summarize the results of an in-depth industry feasibility study and provide more detail on how, together, we will deliver our shared vision and the benefits we expect to unlock. Most importantly we hope that colleagues and the industry will join us on this journey, adding their voices, skills and experience to this global effort.

        Our vision

        In its 2025 Global Energy Review, the International Energy Agency (IEA) finds room for guarded optimism, despite ongoing and unprecedented market turbulence. The IEA reports that although the global appetite for energy continues to grow, almost all additional demand is being satisfied by renewables and nuclear, while the growth of CO2 emissions from the sector is slowing compared to 2023, avoiding 2.6 billion tonnes of additional emissions per year.

        With emissions management now as crucial as finance, accounting and the license to operate, energy businesses are increasingly seeking new ways to reduce their operational carbon footprint. Many have been capitalizing on 乌鸦传媒鈥檚 extensive expertise in digital transformation and emissions reduction consultancy, and now, increasingly in its ability to inspire and facilitate ground-breaking technological collaboration and co-creation.

        By bringing the best brains, from industry, business, government and regulators together in a shared endeavor, 乌鸦传媒鈥檚 vision is to provide the ideal environment and world-class ecosystem in which robust, long-term, data and insight-driven emissions management solutions emerge, for universal use.

        In May 2024, 乌鸦传媒 launched its purpose-built Emission Experience Center (EEC), based in Stavanger, Norway, Europe鈥檚 largest producer of oil and gas, and a hub of regional energy expertise.

        The EEC, designed in partnership with Amazon Web Services, is dedicated to advancing and accelerating emission management best practice and the development of scalable, interoperable and globally compliant solutions that can accelerate industry鈥檚 achievement of a net-zero future.

        Overcoming net zero barriers through collaboration and co-innovation

        Supporting national and international energy companies to achieve their net-zero objectives involves navigating an increasingly complex landscape. Constantly evolving regulations are producing compliance difficulties and potential financial and reputational risk.

        Global data standards are inconsistently implemented, while a lack of unified data management reduces operational efficiency. Resource and skill constraints are hampering execution, siloed and fragmented systems are limiting collaboration, while partial digitalization, automation and incomplete integration are restricting the impact of advanced technologies.

        A lack of clarity around end-to-end emission processes results in missed opportunities for improvement. Critically, with transitioning to net zero requiring significant investment, the business case and associated financial benefits are often not clearly articulated, while misleading claims can undermine trust and credibility. Most importantly, there is a cross-industry consensus that there are significant shortcomings in current emissions reporting practices and an urgent need for integrated systems and common standards that satisfy all national and international emissions reporting requirements, with the current box-ticking approach resulting in lost opportunities to utilize data and insights.

        Accelerating solution development by pooling resources, ideas and knowledge

        We believe that individual nations or businesses cannot solve these challenges alone, and that collaboration and co-innovation is essential to ensure the outcomes that we need, and to avoid the risks and huge costs of duplication. Partnerships bring together diverse expertise and complementary perspectives, fostering synergies among multiple stakeholders to develop comprehensive, scalable and interoperable solutions that can benefit businesses, regulators and society as a whole.

        By pooling resources, ideas and knowledge, co-innovation accelerates the development and deployment of ground-breaking solutions and best practice that are not only compliant with all regulatory standards, but also optimize operational efficiency and sustainability, and enable continuous improvement.

        Collaborative innovation can produce the vital industry infrastructure of the future, delivering a shared, standardized approach to interoperability, data transparency and consistency, unlocking priceless insights, cutting costs and improving efficiencies, equipping the industry with the business intelligence to accelerate its drive for net zero.

        Successful change requires leadership, with a clear vision, to achieve the cultural and organizational shift to new ways of thinking and working, that values partnership in the pursuit of mutual interest as equally as commercial competition.

        The EEC has been conceived and designed to help address and overcome these challenges. At its core will be an advanced Emission Foundation that acts as a transformation engine and innovation platform shared by key stakeholders throughout the value chain.

        How the Emission Experience Center enables collaboration and co-innovation

        The EEC is a collaboration between two of the world鈥檚 leading consultancy and climate technology companies, 乌鸦传媒 and Amazon Web Services (AWS), coming together to establish a co-innovation ecosystem with the vision of supporting national and international energy companies in achieving their net-zero objectives.

        Situated in the heart of Stavanger in Norway, Europe鈥檚 largest producer of oil and gas, and a hub of regional energy expertise, since 2024 the Emissions Experience Center has provided a collaborative space for innovation to prosper among diverse players in the energy industry, ranging from startups to large conglomerates.

        Capitalizing on 乌鸦传媒’s extensive expertise in digital transformation, energy industry technology and innovation platforms and accelerators, the EEC operates as a collaborative hub within the company鈥檚 Norwegian operations. It features cross-functional teams from various departments, including business technology solutions, engineering, data science and sustainability, supported by 乌鸦传媒鈥檚 reinvention and experience partner, frog.

        This collaborative environment promotes the sharing of knowledge and resources, enabling accelerated development of innovative products, technologies, updated processes, concepts and services, all aimed at improving emission management practices.

        It facilitates partnership working using open innovation and data analysis platforms that provide the tools for analyzing and optimizing emissions data to drive informed decision-making, workshops, hackathons, and joint projects and events with industry partners. These activities ensure alignment and progress tracking, fostering a dynamic environment for continuous learning and innovation.

        State-of-the-art collaborative workspaces are designed to inspire lateral thinking, creativity and innovation, driving the development of cutting-edge solutions for the energy industry’s transition towards a net-zero future.

        The Emission Foundation: The EEC鈥檚 cornerstone for co-innovation

        At the heart of our plans for the EEC will be the Emission Foundation, a transformation engine and innovation platform shared by stakeholders throughout the value chain. The Emission Foundation will be the embodiment of the EEC’s commitment to fostering co-innovation for a sustainable future.

        Serving as both a starting point and an accelerator, the Foundation will drive collaborative efforts to address the critical challenges of emissions reduction and environmental sustainability, by providing the resources, support and guidance necessary to turn visionary concepts into reality. The Foundation will be built on open-source technologies and grounded in the DIFI principles of:

        • Data and Data Quality (D): Ensuring accurate and reliable data for audits and verification.
        • Interoperability (I): Promoting seamless integration, sharing, and collaboration among stakeholders.
        • Frequency (F): Transitioning from yearly assessments to real-time monitoring.
        • Insight and Knowledge (I): Facilitating a deeper understanding and informed decision-making.

        By nurturing early-stage initiatives and accelerating their growth, the Foundation will ensure that the most promising innovations reach the market swiftly and effectively.

        Grounded in robust processes and advanced digitalization, the Emission Foundation will enable companies to adopt a focused, insight-driven, and end-to-end approach to emission management and improvements, ensuring compliance, reducing costs, enhancing supply chain resilience, mitigating environmental risks, and strengthening corporate reputation.

        Unlocking the benefits of collaboration and co-innovation

        Bringing diverse stakeholders together will ensure the swift design and frictionless deployment of world-class solutions to shared emissions management challenges. Important benefits of this approach include:

        • Enhanced Emission Management Practices: By developing advanced technologies and process optimization solutions, companies can significantly improve their emission management practices. Up to 60%-time savings are achievable from interoperable systems and standardized data.
        • Improved Operational Efficiency: Collaborative efforts lead to streamlined operations, resulting in reduced emissions of up to 10%.
        • Regulatory Compliance: Co-innovation ensures adherence to evolving standards and regulatory requirements, reducing the risk of non-compliance.
        • Cost Reduction: Effective emission management practices lead to substantial cost savings in operations, quotas, taxes, and reporting, with up to 50% cost reductions in some activities.
        • Increased Reputation and Shareholder Value: Demonstrating a commitment to sustainability enhances a company’s reputation and increases shareholder value.
        • New Business Opportunities: Innovative solutions can open new revenue streams and business opportunities.
        • Sustainability: Driving the industry towards a net-zero future through sustainable practices and long-term environmental stewardship.
        • Strengthened Partnerships and Collaboration: Fostering a culture of continuous improvement and excellence through strong industry partnerships and collaboration.
        • Market Competitiveness: Companies that embrace co-innovation are better positioned to lead in the market, leveraging new technologies to gain a competitive edge.
        • Resilience: Advanced emission management solutions increase supply chain resilience and reduce environmental risks.

        The EEC鈥檚 co-innovation ecosystem accelerates industry-wide access to transformative advancements, fostering a dynamic environment for continuous improvement and operational excellence.

        Bringing our vision to reality: Listening to the Voice of the Industry

        Reaching the broadest consensus possible on a standardized method of capturing, comparing and acting upon emissions data is an essential foundation stone on which to begin our journey.

        The oil and gas industry on the Norwegian Continental Shelf (NCS) stands at a pivotal moment for emissions management. To capture the industry鈥檚 voice and opinion on the proposed creation of a National Emissions Database (NED), we conducted interviews with leaders and practitioners in a broad range of pivotal roles, including asset management, finance, ESG and technology.

        Their perspectives blend optimism and pragmatism, shining light on incumbent solutions, opportunities and challenges, and essential factors to consider in supporting the decision to develop a National Emissions Database (NED) for Norway.

        Across the board, these industry experts acknowledge significant shortcomings in current emissions management and reporting practices, and express a clear appetite for collaboration and innovation to improve data management, with the NCS positioned as a leader in transparent, efficient emissions reporting.

        They repeatedly emphasized the need for higher data quality, more integrated systems, and common standards to satisfy both national and international requirements. These include the EU Emissions Trading System, the Corporate Sustainability Reporting Directive, the Greenhouse Gas Protocol, and upcoming Securities and Exchange Commission climate disclosure rules.

        In our second white paper we synthesize insights from our interviews in four focus areas, namely:

        • Current Approaches to Emissions Reporting
        • Industry Sentiment and Outlook
        • Challenges
        • Opportunities
        • Next steps

        Crucially, several interviewees envisioned an NED as a catalyst that could eventually scale into a Corporate Emissions Database (CED) across companies, ultimately potentially feeding into a global Emissions Data Universe (EDU) with cross-jurisdictional impact. Across all interviews, opportunities presented by an NED clustered around four themes – efficiency, insight, transparency, and collaboration. With the right design, an NED could enable faster, more streamlined reporting, drive continuous improvement through benchmarking and analytics, build trust through shared, auditable data, and unlock new forms of business value and cross-sector cooperation.

        Authors

        Claire Gauthier

        Claire Gauthier

        Executive Vice President and Global Energy & Utilities Leader at 乌鸦传媒
        Claire brings over 20 years of experience driving transformation across the energy sector. Her expertise spans power and utilities, oil & gas, renewables, and emerging technologies across five continents. Claire leads five strategic pillars鈥擨ntegrated Power, Operational Excellence, Nuclear Renaissance, Capital Projects, and Value Chains of the Future 鈥攈elping organizations navigate disruption and accelerate the shift to sustainable, technology-enabled solutions. Her global perspective and leadership helps turn innovation into real-world impact for clients worldwide.
        James Forrest

        James Forrest

        Group Industry Leader for Energy Transition and Utilities at 乌鸦传媒
        I lead in helping global clients with major business transformations involving smart grid, IoT, the reform of gas and electricity markets, major software and infrastructure changes, and the use of machine learning and artificial intelligence to drive significant business performance improvement.
        Bragadesh Damodaran

        Bragadesh Damodaran

        Vice President| Energy Transition & Utilities Industry Platform Leader, 乌鸦传媒
        He is responsible for driving Clients CXO Proximity through聽Industry Infused Innovation and Partnerships, Thought leadership, building Industry-centric Assets and Solutions with Intelligent Industry focus aligning to Energy Transition, Smart Grid, New Energies, Water, Nuclear and Customer Transformations. Bragadesh is a seasoned ET&U Industry and Strategy Consultant in a career spanning over 24 years. Worked for major multinationals driving E&U Value chain strategies and CXO Advisory.
        Eirik Rasmussen

        Eirik Rasmussen

        Director of Business Development and Leader of the Emission Experience Centre
        As a leader of the Emission Experience Centre I engage with national and global clients to accelerate the pathway to a more sustainable future.

          ]]>           /ch-en/insights/expert-perspectives/the-capgemini-emission-experience-centre-the-place-to-collaborate-and-co-innovate/feed/ 0 555247           A Nobel Prize for the Planet: Metal-Organic Frameworks, Quantum Computing, and the Future of Materials Design /ch-en/insights/expert-perspectives/a-nobel-prize-for-the-planet-metal-organic-frameworks-quantum-computing-and-the-future-of-materials-design/ /ch-en/insights/expert-perspectives/a-nobel-prize-for-the-planet-metal-organic-frameworks-quantum-computing-and-the-future-of-materials-design/#respond Tue, 28 Oct 2025 17:23:01 +0000 /ch-en/?p=555210&preview=true&preview_id=555210

          A Nobel Prize for the Planet: Metal-Organic Frameworks, Quantum Computing, and the Future of Materials Design

          Phalgun Lolur
          Oct 28, 2025

          The world鈥檚 most pressing challenges include clean energy, water security, pollution control, and sustainable manufacturing. Meeting these challenges requires new materials with properties that were once the stuff of science fiction.

          In 2025, the Nobel Prize in Chemistry recognized a breakthrough that is reshaping how we design and deploy such materials ( ). The development of metal-organic frameworks, or MOFs, is not just a scientific curiosity. MOFs are a platform for innovation across industries. They have the potential to transform the way we approach materials design.

          The Nobel Prize Story: Metal-Organic Frameworks (MOFs)

          This year鈥檚 Nobel Prize in Chemistry was awarded to Susumu Kitagawa, Richard Robson, and Omar Yaghi for their pioneering work on MOFs. These crystalline materials are built from metal ions connected by organic molecules. The result is a vast and tuneable network of molecular 鈥渞ooms.鈥 The genius of MOFs lies in their modularity. By swapping out building blocks, scientists can create materials with tailored properties for a wide range of applications.

          MOFs have already demonstrated their value in areas as diverse as water harvesting from desert air, the removal of persistent pollutants from water, hydrogen and methane storage, catalysis, drug delivery, and the stabilization of sensitive electronic components. Their ability to selectively trap, store, or transform molecules makes them a game-changer for industries that need sustainable and high-performance solutions.

          Heiner Linke, Chair of the Nobel Committee for Chemistry, said, 鈥淢etal-organic frameworks have enormous potential, bringing previously unforeseen opportunities for custom-made materials with new functions.鈥

          鈥淭he Nobel recognition for metal organic frameworks is more than a scientific milestone. It is a blueprint for action. By combining high performance computing with quantum ready methods, we can screen and refine MOF candidates with greater confidence today. We can unlock even higher fidelity predictions as quantum hardware matures.鈥

          Julian van Velzen, CTIO and Head of 乌鸦传媒鈥檚 Quantum Lab

          Beyond the Lab: The Versatility of MOFs

          What sets MOFs apart is their extraordinary versatility. Here are some highlights from recent research and industrial trials:

          • Water Harvesting: MOFs can extract potable water from desert air. This offers hope for water-scarce regions.
          • Pollution Control: Certain MOFs can remove 鈥渇orever chemicals鈥 (PFAS) and pharmaceutical residues from water. Some can break down toxic gases.
          • Energy Storage: MOFs are being explored for storing hydrogen and methane. This enables safer and more efficient fuel systems.
          • Catalysis: Their tunable cavities allow MOFs to act as highly selective catalysts. This accelerates chemical reactions for cleaner manufacturing.
          • Gas Separation and Sensing: MOFs can separate industrial gases. They can capture rare earth elements from waste streams. They also serve as sensitive detectors for environmental monitoring.
          • Healthcare and Life Sciences: MOFs are being developed for targeted drug delivery. They are also used as platforms for diagnostics.

          The modular nature of MOFs means that the same design principles can be adapted to solve problems across sectors. These sectors include clean technology, pharmaceuticals, electronics, and food safety.

          乌鸦传媒鈥檚 Workflow: Accelerating Materials Innovation

          Turning the promise of MOFs into real-world solutions requires more than scientific insight. It demands robust and scalable workflows that bridge the gap between discovery and deployment. At 乌鸦传媒, we have developed a workflow that brings together the best of classical computational modelling, machine learning, and quantum-centric approaches. This accelerates materials design.

          Key elements of our workflow:

          • High-Throughput Screening: We aim to use cheminformatics and AI to rapidly evaluate thousands of MOF candidates. This helps us identify those with the most promising properties for a given application.
          • Hybrid Computational Methods: We combine classical simulations with quantum-ready algorithms. This enables us to model complex materials with greater accuracy and efficiency.
          • Modular, Scalable Design: Our workflow is designed to be adaptable. Whether the goal is water purification, energy storage, or advanced catalysis, the same pipeline can be tuned to different industrial needs.
          • Collaboration and Validation: We work closely with industry partners and use feedback from real-world trials. This ensures that our predictions translate into practical and scalable solutions.

          This approach is already being applied in collaborative projects with global leaders in energy, manufacturing, and technology. It is supported by initiatives such as DARPA鈥檚 ARC/IMPAQT program (/ch-en/news/press-releases/capgemini-announces-new-project-with-the-defense-advanced-research-projects-agency-on-quantum-computing-for-energy-transition/). By enabling rapid, data-driven selection and validation of advanced materials, the workflow helps manufacturers reduce waste, optimize resource use, and accelerate the adoption of more energy efficient processes. As a result, it is a key enabler for more sustainable manufacturing practices across industries.

          鈥淓ngineering more sustainable products and materials is a business imperative for many of our clients cross industry, as they have to meet regulation, customer needs as well as reacting to supply disruptions and material scarcity. Metal-organic frameworks are a powerful example of how advanced materials can address challenges from clean water to energy storage and environmental emission control. By combining digital workflows, data-driven insights, core engineering and ecosystem collaboration, we are helping organizations accelerate the adoption of sustainable practices and turn scientific breakthroughs into real-world impact.鈥

          Dorothea Pohlmann, CTO Sustainability, 乌鸦传媒

          Quantum Computing: The Next Leap in Materials Discovery

          Quantum computing is poised to revolutionize how we design materials. While today鈥檚 quantum hardware is still evolving, its potential to simulate complex molecular systems with unprecedented fidelity is clear. This momentum is reflected across the scientific and technology landscape. The 2025 Nobel Prize in Physics was awarded for discoveries that brought quantum effects into practical electronics, laying the foundation for today鈥檚 quantum technologies ( ). The United Nations has declared this is the International Year of Quantum Science and Technology. TIME magazine also recognized three quantum breakthroughs among its Best Inventions of 2025, including advances in quantum navigation, room-temperature microprocessors, and next-generation chips from industry leaders. The focus is rapidly shifting from theory to real-world impact, and the race to practical quantum computing is accelerating across industries.

          乌鸦传媒鈥檚 workflow is fully deployable today using existing classical high-performance computing resources. Organisations can already benefit from advanced materials screening and design with our current platform. As quantum hardware matures, we are ready to seamlessly integrate quantum algorithms into the same workflow. This approach ensures that every organisation can access state-of-the-art materials innovation now, while staying prepared to harness the next generation of quantum-powered capabilities as they become available.

          By integrating quantum computing into our materials design pipeline, we can:

          • Explore larger and more complex chemical spaces.
          • Achieve higher accuracy in predicting material properties.
          • Reduce the time and cost from concept to deployment.

          This positions 乌鸦传媒 and its partners to lead in the next era of materials science. Digital and quantum technologies will work together to drive progress.

          Looking Ahead: From Nobel Science to Industrial Impact

          The Nobel Prize for MOFs is a testament to the power of materials innovation. The real story is just beginning. By combining modular materials like MOFs with advanced computational workflows and quantum computing, we are opening new frontiers in industrial design, sustainability, and performance. These digital-first approaches not only speed up innovation but also support more sustainable manufacturing by minimizing trial-and-error, reducing material waste, and enabling smarter, cleaner production methods.

          乌鸦传媒 invites partners across sectors to join us in this journey. From ideation to implementation, from digital simulation to real-world deployment, we can turn Nobel-winning science into solutions that shape a better and more sustainable future for all.

          Meet the author

          Phalgun Lolur

          Phalgun Lolur

          Scientific Quantum Development Lead
          Phalgun leads the 乌鸦传媒 team on projects in the intersection of chemistry, physics, materials science, data science, and quantum computing. He is endorsed by the Royal Society for his background in theoretical and computational chemistry, quantum mechanics and quantum computing. He is particularly interested in integrating quantum computing solutions with existing methodologies and developing workflows to solve some of the biggest challenges faced by the life sciences sector. He has led and delivered several projects with partners across government, academia, and industries in the domains of quantum simulations, optimization, and machine learning over the past 15 years.
            ]]>             /ch-en/insights/expert-perspectives/a-nobel-prize-for-the-planet-metal-organic-frameworks-quantum-computing-and-the-future-of-materials-design/feed/ 0 555210             Unlocking new value: Building a competitive edge with collaborative data ecosystems /ch-en/insights/expert-perspectives/unlocking-new-value-building-a-competitive-edge-with-collaborative-data-ecosystems/ /ch-en/insights/expert-perspectives/unlocking-new-value-building-a-competitive-edge-with-collaborative-data-ecosystems/#respond Fri, 17 Oct 2025 09:47:36 +0000 /ch-en/?p=554742&preview=true&preview_id=554742

            Unlocking new value: Building a competitive edge with collaborative data ecosystems

            Rajashree Das
            Oct 17, 2025

            鈥淏usinesses have spent years treating data like treasure that should be locked away in a vault. But the real value of data emerges when we treat it as a shared resource 鈥 one that connects, empowers, and transforms. Collaborative data ecosystems are more than a trend; they鈥檙e the building block of a smarter, more connected future.鈥

            鈥 Rajashree Das 

             For decades, businesses have been told that their data is their most valuable asset 鈥 one that must be protected from everyone at all costs. Data has always been thought of as something to collect, guard, and keep proprietary. The thought process here is simple; own the data, own the competitive advantage. But could this mindset be preventing organizations from growth? 

            Today, forward-thinking businesses are beginning to recognize that the real power of data doesn鈥檛 lie in isolation, but in collaboration. When organizations share data responsibly and ensure the right controls, agreements, and technologies are in place, they open the door to transformative value creation.  

            This growing shift towards collaborative data ecosystems is something we refer to as 鈥淒ata Sharing is Caring,鈥 and it鈥檚 one of the most critical trends from our TechnoVision 2025 playbook.  

            Inside collaborative data ecosystems 

            Collaborative data ecosystems are environments where multiple organizations, sometimes even competitors, share data responsibly and securely under applicable regulations. The goal of these ecosystems is to co-create new services and generate mutual benefit. Depending on the industry and use case, collaborative ecosystems may be built differently, however all rely on a common foundation of trust, transparency, and shared purpose. 

            Privacy, ethics, and compliance are non-negotiable elements of every collaborative data ecosystem. Data must be handled with care and governed by clear agreements and certified technologies that protect organizations from data misuse. Ownership and governance are equally important, especially as businesses increasingly adopt federative 鈥 or data mesh 鈥 approaches to data management where data is treated as a first-class product that鈥檚 ready for consumption. This shift enables both internal and external partners to collaborate and access data more effectively.  

            Interoperability and accessibility are equally as critical to collaborative data ecosystems. Open data protocols and interoperable systems ensure that data can flow securely and efficiently across organizational boundaries. The rise of data marketplaces and self-service platforms are also making it easier than ever to discover, exchange, and monetize data products. 

            How data sharing is powering innovation across industries  

            From medical research to media and advertising, new models of responsible data sharing are proving that secure access to shared data across institutional and geographic boundaries can unlock previously out of reach insights. 

            In Europe, a across multiple European institutions is using AI to better understand chronic immune-mediated diseases. The project securely combines sensitive health data from multiple diverse sources to train predictive models with improved accuracy 鈥 underscoring how responsible data sharing can accelerate medical research while maintaining individual privacy.  

            Additionally, a North American media organization with multiple data partners to create data clean rooms that enable advertisers to share data and build audiences in a secure and privacy-compliant way. This initiative exemplifies how organizations are advancing responsible data sharing to support privacy while enhancing advertising capabilities. 

            From data to impact: What the future holds 

            As is evident in our real-world examples, the impact of collaborative data ecosystems is already being felt. Our past has indicated the benefits of data ecosystems for the private sector, with organizations participating in collaborative data ecosystems experiencing up to a 15% improvement in customer satisfaction, 14% gains in productivity, and 11% cost reductions over the course of a two-to-three-year period. But the benefits go far beyond these metrics. Collaborative data sharing is helping to address some of society鈥檚 most pressing challenges. It鈥檚 also permitting the formation of unexpected partnerships, unlocking new revenue streams, and pioneering breakthrough business models. 

            Collaborative data ecosystems are reshaping what鈥檚 possible. By moving beyond the mindset of data as a guarded asset and embracing it as a shared resource, businesses are positioning themselves to lead in the years to come. Data sharing isn鈥檛 just a trend. For organizations that are ready to embrace it, it鈥檚 a differentiator capable of enabling a more intelligent, connected, and impactful future. 

            Learn more 

            • TechnoVision 2025 鈥 your guide to emerging technology trends 
            • Data Sharing is Caring (But Take Care!) – a new trend in Thriving on Data 
            • Voices of TechnoVision 鈥 a blog series inspired by 乌鸦传媒鈥檚 TechnoVision 2025 that highlights the latest technology trends, industry use cases, and their business impact. This series further guides today鈥檚 decision makers on their journey to access the potential of technology. 

            Meet the author

            Rajashree Das

            Rajashree Das

            India Capability Leader
            Rajashree is a seasoned technology leader, currently playing the role of the India Capabilities Leader and India Country Board member, with 27 years in tech, consulting, and leadership. 乌鸦传媒鈥檚 first L4 Women Master Architect, she drives career growth, diversity, and innovation across the group. A mentor and award-winning thought leader, she鈥檚 recognized for her impact in enterprise architecture and women in tech.
              ]]>               /ch-en/insights/expert-perspectives/unlocking-new-value-building-a-competitive-edge-with-collaborative-data-ecosystems/feed/ 0 554742               Agentic AI in wealth management /ch-en/insights/expert-perspectives/agentic-ai-in-wealth-management/ /ch-en/insights/expert-perspectives/agentic-ai-in-wealth-management/#respond Fri, 17 Oct 2025 08:10:14 +0000 /ch-en/?p=553821&preview=true&preview_id=553821

              Agentic AI in wealth management
              What advisors can do now

              乌鸦传媒 Logo
              Hardik Budhiraja, Shweta Sehgal, Ranjan Pradhan
              Oct 06, 2025
              capgemini-invent

              Agentic AI is transforming wealth management by blending human expertise with intelligent automation, boosting advisor efficiency, client trust, and personalized financial outcomes

              The wealth management industry faces a dilemma. On one hand, a major demographic shift comes as a large percentage of advisors near retirement. On the other hand, the rise of advanced self-service generative AI (Gen AI) agents raises questions about future relevance of human advisors. Investment firms must now consider whether to invest in a new generation of professionals or transition toward AI financial advisors and hybrid advisory models that promise operational efficiency, despite lingering concerns over client trust in non-human financial interactions.

              Advisors in the U.S. from aging to training 

              The financial advisor industry is experiencing a notable aging trend which has various known and un-known impacts on the industry. Given that 48% of relationship managers (a role synonymous with financial advisor) are expected to retire by 2040,1 it can have a significant impact on investor relationship and trust, leading to a decline in efficiency and diminishing AUM.  

              While aging remains to be a significant concern, it is accompanied with other worrying trends, a major wealth transfer arising from doubling of population aged 65 and above2 and an army of digital advisors (at times dubious) promising returns. 

              To address the impending shortage and ensure that investors do not get alluded by new age investment advisors, the industry needs to attract and train a significant number of new advisors. Over the next decade, over 100 thousand advisors are expected to retire and the replacement from new advisors falls short with a 72% failure rate to perform the job well.3  

              Agentic wealth advisors infographic 11

              Even when investment firms decide to invest in the above success areas, there remain notable differences in knowledge and experience between aging advisors and new entrants. Older advisors tend to possess what is often called 鈥渋ntelligence to sell,鈥 the ability to understand client needs, build trust, and craft persuasive, tailored advice based on years of relationship management. In contrast, younger advisors often excel in 鈥渇luid intelligence,鈥 which refers to the capacity to learn quickly, adapt to new technologies, and apply innovative approaches to problem-solving.4 Bridging this gap requires embedding mentorship into day-to-day work, supported by a willingness to adopt fluid intelligence or offer it directly to tech-savvy clients. In both cases, leveraging digital tools across the advisory journey can capture and document the 鈥渋ntelligence to sell鈥 before retirement and make it usable through advanced agentic AI in finance tools. 

              Enhancing efficiency in financial advisory with specialized gen AI workflow agents

              We are witnessing the emergence of AI systems capable of autonomous decision-making, designed to specialize in specific tasks and take action. This is achieved by implementation of agentic AI, a specialized AI bot for a specific task, in our case performing various steps in the financial advisory journey.5 

              These agents learn from past behavioral data, including client interactions and transactions, and deliver personalized, automated services. They help advisors maintain trust through genuine human-to-human connection while introducing what we call augmented advisory: a model that combines human judgement with AI support. Agents can provide real time dialogue assistance, generate financial analysis, execute routine tasks, and produce clear summaries. Together, these capabilities enable proactive, intelligent actions that improve client outcomes. 

              Time is a scarce resource for advisors and it takes immense effort to personalize each report, manage client asks, while being effectively able to summarize and persuade clients. Especially for new advisors, it is difficult for them to cope with multiple client requests which requires experience and knowledge in handling clients, here specialized bots come to aid offering support with real-time operations, dialogue, and research. We provide you with a glimpse of few emerging industry examples.

              Categorization of AI agents for financial services 

              Marketing Agent: Identifies prospective clients by life stage and preference. Delivers timely, personalized messages across channels. Tracks return on investment, analyzes click throughs and conversions, and helps lower acquisition cost while increasing retention through data driven interactions.

              Master Agent: Provides a single dashboard for the advisor to monitor client activity and agent output. Orchestrates specialized agents, allocates work, and measures value. Prompts the advisor for manual steps and proposes automation as it learns the workflow.

              Operations Agent: Collects client details, validates documents, and triggers the steps to open or amend accounts. Supports compliance reporting, captures minutes, and handles routine administration. Improves accuracy and reduces cycle time.

              Service Agent: Tracks prior actions and conversations, then sends timely updates to clients and advisors. Triggers other agents to prepare documents and surfaces priority items such as scheduled portfolio reviews. Manages task lists so critical work is handled on time.

              Sales Advisory Agent: Supports advisors during client calls with prompts on planning topics, product fit, and required compliance language. Shares clear next actions with the client, including documents to gather, portfolio details, and recommendations. Flags market linked changes and helps the relationship manager act promptly.

              Research Agent: Generates research based on client goals and recent discussions. Provides market and portfolio analysis on demand for advisors and, where appropriate, for clients. Pulls from approved data sources to support recommendations.

              Call Agent: Understands caller intent and routes calls to the right agent or to the advisor. Reduces call time and improves first contact resolution. Sends real time nudges to the advisor and produces a short summary with key actions and follow up dates.

              Snapshot of AI use cases in financial services

              AI in finance services 鈥 specifically agentic AI 鈥 is changing advisory work. They deliver advanced analytics, personalized recommendations, automation of routine tasks, support for real time conversations, and help with content creation. AI agents can generate client reports, answer client queries, and surface market insights. They can also be tailored to niche tasks such as portfolio rebalancing. Together, these capabilities improve advisor efficiency and the client experience.6

              Investing in future advisors 

              The financial advisory industry in the U.S. is at a crossroads. To sustain growth and meet rising demand, firms should adopt agentic AI and related tools in ways that augment human judgment. This approach can bring experienced and new advisors together, raise service quality, and help clients achieve financial goals.

              Ready to reimagine client engagement in wealth management?

              乌鸦传媒 can be your end-to-end partner in harnessing Agentic AI to transform advisor-client interactions. We invite you to schedule a discussion to explore how our suite of Gen AI innovations and robust partner ecosystem can help elevate engagement and deliver intelligent, outcome-driven experiences.

              Meet our experts

              Hardik Budhiraja

              Hardik Budhiraja

              Gen AI Banking Lead, 乌鸦传媒 Invent
              Currently working at 乌鸦传媒 Invent as part of the India Banking team with a focus to drive global sales and solutions.
              Shweta Sehgal

              Shweta Sehgal

              Senior Director, Retail Banking and Wealth Management Leader, 乌鸦传媒 Invent
              Shweta is a dynamic and results-driven Business Managing Consultant with over 19 years of expertise in the banking and financial services sector. She excels in delivering tailored consulting services to banking clients, driving business transformation, and implementing effective solutions that meet stakeholder needs. With a robust international background, Shweta specializes in consulting, product management, and program implementation within the financial services industry.
              Ranjan Pradhan

              Ranjan Pradhan

              Senior Director, Financial Services 鈥 CTIO Office, 乌鸦传媒
              With over 20 years of experience in the banking and financial services industry, Ranjan Pradhan is currently a Senior Director at 乌鸦传媒, specializing in Product Management, data,AI and analytics, digital strategy, and transformation. He leads strategic workforce planning and technology initiatives within the Financial Services Strategic Business Unit, collaborating with product partners to build accelerators and innovative offerings.

                References

                1. [Accessed on the 11th of September 2025]
                2. [Accessed on the 11th of September 2025]
                3. . [Accessed on the 23rd of September 2025]
                4. [Accessed on the 11th of September 2025]
                5. [Accessed on the 11th of September 2025]
                6. [Accessed on the 11th of September 2025]

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                FAQs

                Agentic AI is different from traditional AI in Financial Services because it takes the initiative to autonomously compose workflows and enhance decision-making. Its ability to dynamically adapt to changes in a scenario is a key differentiator. This is invaluable for fluctuating markets. It analyses new data in real time and collaborates with human advisors to deliver better client outcomes.

                Agentic AI supports hybrid advisory models by combining the power of automation with human ingenuity and expertise. Agentic AI can perform data analysis and manage routine tasks with more efficiency. It can flag more complex decisions for advisors to review. The net result is better experiences for all, including scalable personalization and optimal management of costs.

                The benefits of using AI financial advisors for client retention are numerous, including customized insights, better response times, and proactive engagement. Moreover, AI agents experience no downtime, meaning they are always available to resolve issues. Knowing this support is always there builds trust and improves client satisfaction. Clients are less likely to churn. AI agents strengthen long-term relationships by anticipating clients鈥 needs and responding swiftly.

                Agentic AI improves time management for financial advisors by automating important research, performing vital compliance reviews, and monitoring portfolios. This liberates advisors and enables them to focus on more value-adding tasks for clients and services, such as performing strategic planning, strengthening relationships, and generating business growth.

                Yes. Agentic AI can be customized for niche financial services with training on industry-specific data, regulations, and workflows. These agents can then provide tailored recommendations, model risk, and tune communication to markets and clients鈥 needs.

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                ]]>                 /ch-en/insights/expert-perspectives/agentic-ai-in-wealth-management/feed/ 0 553821                 Recognized for innovation: 乌鸦传媒鈥檚 trailblazing work with Engie and Salesforce /ch-en/insights/expert-perspectives/recognized-for-innovation-capgeminis-trailblazing-work-with-engie-and-salesforce/ /ch-en/insights/expert-perspectives/recognized-for-innovation-capgeminis-trailblazing-work-with-engie-and-salesforce/#respond Thu, 16 Oct 2025 09:42:54 +0000 /ch-en/?p=554739&preview=true&preview_id=554739

                Recognized for innovation: 乌鸦传媒鈥檚 trailblazing work with Engie and Salesforce

                Katerina Hubka
                16 Oct 2025

                I鈥檓 excited to share that 乌鸦传媒 has been recognized with a 2025 Salesforce Partner Innovation Award. This award highlights our strong AI customer service expertise across industries, the strength of our partnership with Salesforce, and the bold outcomes we鈥檝e delivered together.

                At 乌鸦传媒, our partnership with Salesforce is more than a strategic alliance 鈥 it鈥檚 a shared mission to help organizations reimagine how they connect with their customers. Together, we bring the best of cloud, data, and AI to deliver experiences that are not only intelligent and scalable, but also deeply human.

                One story that truly embodies this spirit is our recent work with Engie M&S Belgium, where we helped redefine customer service through Salesforce Agentforce.

                How 乌鸦传媒 and Engie redefined service with Agentforce

                When Engie approached us, they had a clear and ambitious goal: make their mobile app the primary channel for customer service. They wanted more than a chatbot 鈥 they envisioned a conversational agent that could deliver real-time, actionable support, operate within strict AI guardrails, and serve customers in their native language, 24/7.

                Their existing solution was limited to FAQs. Engie wanted to go further 鈥 enable customers to check balances, update payments, and receive personalized recommendations, all through a seamless conversational interface. And we had just three weeks to deliver a working prototype.

                Our approach: Speed, innovation, and partnership

                To meet Engie鈥檚 vision, we mobilized quickly. Our team at 乌鸦传媒 designed an agile, phased strategy 鈥 starting with a rapid proof-of-concept and evolving through deep integration with Engie鈥檚 systems.

                We leveraged Salesforce Agentforce, enhanced with Microsoft retrieval-augmented generation (RAG) and vector search, to ensure every customer interaction was precise, relevant, and actionable. By integrating with Engie鈥檚 ERP systems, we enabled the agent to do more than just respond 鈥 it could execute customer care actions.

                The results: Customer experience, redefined

                The impact was immediate and measurable:

                • 80%+ of client conversations handled by AI
                • 1,200+ daily interactions
                • More than 70% autonomous case resolution

                What impressed me most was the speed to value 鈥 from concept to deployment in just three weeks. This wasn鈥檛 just about deploying technology 鈥 it was about understanding Engie鈥檚 customers, anticipating their needs, and delivering a solution that truly makes a difference.

                What鈥檚 next: Scaling innovation

                The success of this project is just the beginning. Engie is now exploring how to expand Agentforce across more services, deepen automation, and personalize experiences even further with generative AI.

                Why this matters

                This story is a testament to what鈥檚 possible when partnership, purpose, and innovation come together. It reflects the strength of our partnership with Salesforce and our shared belief that customer experience should be intuitive, intelligent, and inclusive.

                At 乌鸦传媒, we鈥檙e proud to help clients like Engie turn bold visions into reality. Because when we put the customer at the heart of everything we do, that鈥檚 when true transformation happens.

                Dreamforce 2025: This is what customer experience really looks like

                These achievements wouldn鈥檛 have been possible without the dedication of our teams and the strength of our partnership with Salesforce. We brought these innovations to life at Dreamforce 2025, where 乌鸦传媒 was an Innovator Sponsor.

                From immersive demos to expert-led sessions, we showcased how Agentforce and AI-powered solutions are transforming customer experience across industries.

                Connect with me on LinkedIn if you would like to learn how we make it real for our clients.

                .

                Author

                Katerina Hubka

                Katerina Hubka

                Global Salesforce Partner Executive
                Katerina is an assertive mover and shaker, and a creative communicator with strong project, program, portfolio and people management skills. With more than 20 years of expertise, Katerina has served as a leader in many roles across 乌鸦传媒, including in the Americas, Group Sales, Global Strategic Initiatives and Partners, and Group Marketing. Katerina brings her passion for building genuine relationships and driving mutually beneficial collaboration to our partnership with Salesforce. Stepping in to lead the partnership in 2024, she has been consistently delivering against goals in collaboration with stakeholders across 乌鸦传媒 and the Salesforce ecosystem.
                  ]]>                   /ch-en/insights/expert-perspectives/recognized-for-innovation-capgeminis-trailblazing-work-with-engie-and-salesforce/feed/ 0 554739                   Set the score, keep the tempo: Why a ServiceNow Centre of Excellence and Innovation turns noise into value /ch-en/insights/expert-perspectives/set-the-score-keep-the-tempo-why-a-servicenow-centre-of-excellence-and-innovation-turns-noise-into-value/ /ch-en/insights/expert-perspectives/set-the-score-keep-the-tempo-why-a-servicenow-centre-of-excellence-and-innovation-turns-noise-into-value/#respond Thu, 16 Oct 2025 09:15:31 +0000 /ch-en/?p=554726&preview=true&preview_id=554726

                  Set the score, keep the tempo: Why a ServiceNow Centre of Excellence and Innovation turns noise into value

                  Alan Connolly, Global Head 鈥 Employee Experience and Digital Workplace, 乌鸦传媒
                  Alan Connolly
                  16 Oct 2025

                  You鈥檝e invested millions in ServiceNow, but are you truly getting enterprise-wide value or just running IT workflows?

                  Most organizations believe their stage is set. You鈥檝e invested in the best instruments: platforms, partners, and processes. Signals are everywhere: cost, risk, MTTR, release velocity, experience. But when those signals aren鈥檛 coordinated 鈥 and there鈥檚 no conductor 鈥 you pay a tax on complexity.

                  By treating a ServiceNow investment as just a technical platform without recognizing it as a strategic enabler for the business, many enterprises miss the importance of clear enterprise-wide strategy and orchestration, and of coordinated roadmaps leading to business targets. ServiceNow was sold as a platform of platforms 鈥 a foundation for enterprise workflows across IT, HR, customer service, and beyond. Its potential is huge: AI-driven automation, integrated data, and faster decision-making.

                  Yet most organizations hit the same wall:

                  • Siloed ownership keeps adoption IT-centric.
                  • Unmanaged demand floods the backlog with pet projects.
                  • Customization sprawl drives upgrade pain and technical debt.
                  • Governance gets political, slowing decisions and eroding trust.

                  The result isn鈥檛 harmony 鈥 it鈥檚 noise. Value stalls, costs rise, and the platform becomes a patchwork of local optimizations rather than an enabler for enterprise transformation.

                  Case in point: ServiceNow found that after 180 days. 聽That equates to $3.5 billion spent on technology worldwide over that period without any tangible value for IT or the business.

                  Adopting a single, business-aligned operating model

                  A dedicated organizational model can consolidate strategy, governance, architecture, delivery, and innovation into one structure.

                  The reflexive idea is to strike up new projects, but that鈥檚 the opposite of what is required. To unlock measurable outcomes, enterprises need to avoid piling on more piecemeal solutions and instead create a Centre of Excellence and Innovation (CoE&I)聽that聽applies the same principles of Service Integration and Management (SIAM) to the platform itself. A CoE&I is not a rebadged platform team. It鈥檚 a single, business-aligned operating model that consolidates strategy and governance, business engagement, platform architecture and support, innovation and experience, and delivery. Done right, it turns your ServiceNow investment from an operational expense into a transformation engine for IT and the business, removing the seams that slow down value and embedding continuous improvement and velocity into your enterprise strategy.

                  • Project vending machine: no enterprise prioritization
                  • 颁耻蝉迟辞尘颈锄别鈥慺颈谤蝉迟: pattern entropy, upgrade paralysis
                  • Shadow demand: political work, stranded value
                  • No conductor: metrics abound, outcomes don鈥檛

                  Shifting from legacy systems to vehicles for innovation

                  Intelligent orchestration on now (ION) is 乌鸦传媒鈥檚 two-layer model for an effective COE&I that works in concert, aligning purpose, direction, and performance to move from projects to product-mode delivery with measurable business impact.

                  Orchestration layer: Owns vision, value cases, roadmap, and demand triage. It鈥檚 the single front door for work, prioritizing by business outcomes, not politics, and ensures the platform plays to the enterprise score 鈥 keeping tempo and sequencing releases for maximum impact.

                  Custodian layer: Owns architecture guardrails, integration standards, security, and run. It makes fast safe, and controls customization sprawl, upgrade debt, and risk, and ensures every release is crisp, compliant, and repeatable.

                  Across these layers, SIAM principles matter: integration, orchestration, and accountability are critical for success with ServiceNow. They provide the structure for multi-vendor ecosystems, clear roles, and a roadmap that links platform investment to P&L impact.

                  For example, a Nordic food producer wanted greater control and business agility on ServiceNow. 乌鸦传媒 helped establish a dedicated instance, set governance guardrails, and prioritize a roadmap for IRM, health and safety, and catalog improvements. With clearer ownership and a product鈥憁ode delivery model, the client achieved faster change velocity, cleaner data, and a platform that supports hybrid operations and continuous improvement.

                  The payoff:

                  • 50 percent reduction in maintenance cost through standardization and reuse
                  • 38 percent faster implementation via accelerators and release trains
                  • 80 percent improvement in first-contact resolution with integrated workflows
                  • Lower TCO, higher adoption, and enterprise-grade risk control

                  The 90-day activation plan

                  The focus should be on big-picture strategies, not short-term tactics, with the vision of the platform as a vehicle for innovation that transcends simple IT service management.

                  Through 乌鸦传媒鈥檚 partnership with ServiceNow, and our expertise with orchestrating platform solutions across industries, we can help you take the required steps.

                  Days 1鈥30, foundation: We establish the charter, appoint an executive sponsor, and create a single demand intake process. At this stage, we baseline technical debt and set governance and architecture guardrails to ensure control from day one.

                  Days 31鈥60, quick wins: Together, we prioritize two or three high-value use cases and launch a product-mode team to deliver them. We embed joint KPIs, define platform service levels, and enforce standards for speed without risk.

                  Days 61鈥90, scale and sustain: We publish a rolling roadmap, implement a release cadence, and introduce a platform scorecard to track adoption, cycle time, and value realized. Early wins feed an innovation backlog, creating a sustainable engine for continuous improvement.

                  Unleashing potential to keep up with business

                  Governance first, then speed. Without a CoE&I, you鈥檒l keep funding work that doesn鈥檛 move your P&L. With one, you unlock value at scale, and finally make the platform perform.

                  A mature CoE&I doesn鈥檛 just optimize workflows; it creates the conditions for AI-driven efficiency, connected data intelligence, and seamless customer and employee experiences. It turns fragmented processes into integrated journeys: personalized, automated, and future-ready.

                  The choice is simple: keep spending on projects that stall or invest in a model that delivers measurable outcomes and continuous innovation. 乌鸦传媒 brings the expertise, accelerators, and partnership to make it real 鈥 fast.

                  The question is: will you keep playing catch-up, or start orchestrating value today?

                  Author

                  Alan Connolly

                  Alan Connolly

                  Global Head of Digital Workplace Services – Cloud Infrastructure Services
                  Alan has a passion for working closely with customers, partners, and industry experts to solve complex challenges across the workplace. As a seasoned professional with over 20 years experience, he brings a unique blend of creativity and analytical thinking to the table to develop comprehensive plans that meet the needs of both the organization, and its employees.
                    ]]>                     /ch-en/insights/expert-perspectives/set-the-score-keep-the-tempo-why-a-servicenow-centre-of-excellence-and-innovation-turns-noise-into-value/feed/ 0 554726                     How Agentic AI can make OT infrastructure more robust and secure /ch-en/insights/expert-perspectives/how-agentic-ai-can-make-ot-infrastructure-more-robust-and-secure/ /ch-en/insights/expert-perspectives/how-agentic-ai-can-make-ot-infrastructure-more-robust-and-secure/#respond Thu, 16 Oct 2025 09:09:29 +0000 /ch-en/?p=554722&preview=true&preview_id=554722

                    How Agentic AI can make OT infrastructure more robust and secure
                    Leveraging telecom鈥檚 Dark NOC strategy to enhance your OT Network Operations Center resilience, efficiency and security

                    Nikhil Gulati
                    Oct 16, 2025
                    capgemini-engineering

                    Imagine a sprawling oil refinery, where thousands of sensors, controllers, and automated systems orchestrate the transformation of crude oil into usable products. Every valve, pump, and pressure gauge is connected to a central network, feeding real-time data into control systems that ensure safety, efficiency, and compliance.

                    In this environment, disruption to the Operational Technology (OT) network can cascade with serious consequences, from halting production and incurring millions in losses to risking environmental damage and putting lives at risk.

                    Why it’s important to shed light on the Industrial NOC

                    Historically, IT and OT operated in silos: IT managed data, connectivity, and enterprise systems, while OT focused on process control, machinery, and safety. But with the rise of Industry 4.0 and digital transformation, we鈥檙e witnessing increasing convergence鈥攁 steady blurring of boundaries where OT data now flows into IT systems to power predictive maintenance, AI/ML optimization, business intelligence, and more.

                    This convergence addresses the need to enhance IT/OT integration and modernize Industrial Network Operations Centers鈥攖he infrastructure nerve centers where industrial systems (like MES, SCADA, Historians, and advanced analytics) operate and converge with IT systems. OT infrastructure availability is crucial for maintaining operational continuity and any disruption in these systems can lead to significant financial losses, physical damage to equipment, or severe societal impacts.

                    Below are a few examples of IT/OT convergence related network efforts increasing resilience:

                    • A Siemens plant in Texas faced frequent network-related production disruptions due to poor IT/OT integration. After redesigning their OT network, the company claims that .
                    • Cisco deployed Software Defined Networking. According to Cisco, this enabled Audi to virtualize production assets and ensure deterministic, secure, and scalable networking across its manufacturing operations, resulting in .
                    • Faced with the challenge of modernizing its fragmented IT/OT infrastructure, a utility provider turned to Juniper鈥檚 zero-trust, programmable network fabric to unify operations from control centers to substations. Juniper claims that the transformation was so effective that SCADA circuit provisioning, which previously took hundreds of hours, was 鈥攄ramatically improving efficiency and reliability.

                    The opportunity for next gen Industrial NOCs

                    Even with modernized infrastructure, network incidents continue to rely heavily on human monitoring and intervention. Typically, and for good reasons, the OT world runs on predefined alert thresholds and manual runbooks to manage problem solving. This ensures that fixes, adjustments, or restarts can be carried out without disrupting critical processes or causing serious consequences. The downside of this approach is reduced response time and agility during costly network downtime or periods of limited availability.

                    With the rise of Agentic AI technology now available, transformational benefits can be unlocked for industrial NOCs, such as real-time issue detection, analysis and proposed resolutions to improve uptime and scalable operations. Powered by strong human-AI chemistry, reliable agentic systems can balance autonomous capabilities with human-in-the-loop oversight. With such tools, people and operations can be augmented While Agentic AI is extremely ahead of the adoption curve, industrial organizations appear to have a strong appetite for deployment in industrial maintenance and support environments.

                    From the CRI Report 鈥淓R&D Trends鈥
                    71% of organizations believe AI will transform the maintenance and support activities (eg. AI-based diagnostics, predictive maintenance planning, intelligent support bots) over the next 2-3 years.

                    Agentic AI can significantly enhance Human-AI collaboration in Industrial Network Operations Centers by deploying intelligent agents that continuously monitor systems, detect anomalies, and perform root cause analysis in real time. These agents act as proactive partners, surfacing insights and recommended actions to human operators, enabling faster, more informed decision-making. By fostering a responsive and transparent interaction loop, Agentic AI builds trust and synergy between humans and machines to accelerate issue resolution, minimize downtime, and ensure operational resilience.

                    At the 2025 Mobile World Congress in Barcelona, we showcased a working proof of concept in collaboration with Exfo, Salesforce and ServiceNow, demonstrating our Agentic AI enhanced Dark NOC approach for telcos.

                    Can the Dark Industrial NOC concept work in the OT world?

                    The answer is 鈥榶es鈥, with the right approach. In the traditional context, the term “dark” in Network Operations Center (NOC) operations typically refers to a lights-out facility 鈥 one where no personnel are physically present because routine tasks are fully automated. The vision of a future-state Dark NOCs builds on this concept by introducing intelligent systems capable of observing, analyzing, and acting autonomously.

                    However, we believe that to be successful, you must go a step further, redefining the DARK concept from merely an automation milestone to a Digital Twin & Agentic AI-powered Reasoning Kernel (DARK) enabled NOC.

                    Our approach centers on a unified, AI-driven decision-making framework that enhances network management through deep contextual understanding and autonomous reasoning. At the core of this model are network digital twins, enriched with semantic models, which simulate and analyze network behavior with high fidelity. Importantly, this is not about eliminating human involvement; it鈥檚 about redefining the human-machine loop. In a DARK-enabled NOC, AI and automation handle routine detection, diagnostics, and remediation across domains. Human expertise is reserved for oversight, handling exceptions, and driving strategic evolution, not day-to-day firefighting.

                    A true Dark NOC is not a patchwork of scripts or rule-based automation. It requires systems that can understand context, correlate across silos, and reason to make decisions. Without semantically integrated data and agentic AI, this level of intelligence is unattainable.

                    Is it safe and robust?

                    Intelligent, self-operating network and operations centers in an industrial setting require a robust AI framework. This is why 乌鸦传媒 developed the Resonance AI framework. It helps organizations unlock the full potential of AI at scale, and reinforces organizations鈥 AI readiness, while creating the right 鈥榟uman-AI chemistry鈥, to ensure long-lasting adoption.

                    Implications for decision makers: cost and revenue impact

                    For decision-makers, the short-term implications are clear: investing in advanced NOC capabilities must become a business imperative鈥攏ot only for maintaining uptime, safety, and competitiveness, but also for unlocking cost and revenue potential, focusing on:

                    • Higher uptime for industrial networks can now be assured without scaling headcount, reducing operational costs while improving service continuity.
                    • A stronger security posture minimizes risk exposure and regulatory penalties, protecting both brand and bottom line.
                    • Enabling robotics-driven production environments鈥攚hich demand superior network connectivity鈥攔emoves a key constraint to achieving higher industrial efficiency and throughput.

                    Conclusion: Building the smart backbone of industrial innovation

                    As OT systems become more intelligent and interconnected, the networks that support them must evolve in tandem. The journey from complexity to autonomy in network operations is not just a technical challenge, it鈥檚 a business opportunity. Those who lead this transformation will define the future of industrial performance.

                    Meet the author

                    Nikhil Gulati

                    Nikhil Gulati

                    Head of Intelligent Support and Services, 乌鸦传媒 Engineering
                    Nikhil is a results-oriented professional with extensive experience in IT/telecom, project management, software development/support, client relationship management, business development and operations, and pre-sales.
                      ]]>                       /ch-en/insights/expert-perspectives/how-agentic-ai-can-make-ot-infrastructure-more-robust-and-secure/feed/ 0 554722