乌鸦传媒 Finland /fi-en/ 乌鸦传媒 Tue, 29 Jul 2025 09:09:08 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.2 /fi-en/wp-content/uploads/sites/26/2022/10/cropped-cropped-favicon-1.webp?w=32 乌鸦传媒 Finland /fi-en/ 32 32 192805541 Shaping the inclusive leaders of tomorrow聽 /fi-en/insights/expert-perspectives/shaping-the-inclusive-leaders-of-tomorrow/ /fi-en/insights/expert-perspectives/shaping-the-inclusive-leaders-of-tomorrow/#respond Fri, 25 Jul 2025 09:08:13 +0000 /fi-en/?p=547084&preview=true&preview_id=547084 Our long-term partnership with HEC Paris, a premium global business school, helps test our thinking and anticipate future trends, while mentoring the next generation of leaders through inclusion challenges.听

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Shaping the inclusive leaders of tomorrow聽

Karine Vasselin
Jul 25, 2025

At 乌鸦传媒, our commitment to inclusion isn鈥檛 just limited to our people, but extends to supporting the next generation of leaders, ensuring they can build the inclusive workplaces of tomorrow through key partnerships like our long-term collaboration with HEC Paris. 

As a business partner to HEC Paris, we鈥檝e mentored batches of 25 students for a Master鈥檚 course on diversity and inclusion (D&I) in the last three years. We help students understand our approach toward inclusion at 乌鸦传媒 and propose a team challenge, aligned with the latest D&I trends and topics. Students are then given six weeks to complete their research and present their final reports in our Paris office.  

Working with Matteo Winkler, Associate Professor at HEC Paris, who teaches courses on international business law as well as diversity and inclusion, this is an opportunity for us to connect with emerging talent, test new ideas, and anticipate trends while we mentor them through real-world challenges. 

In this blog, Matteo and I take a closer look at this year鈥檚 challenge and what we as practitioners can learn from it.

About the partnership

Matteo: When I created this course years ago as part of the Master of Management program of CEMS (previously the Community of European School of Management), which has now evolved into a global alliance of business schools of which HEC Paris is a partner. I looked for a company committed to inclusion, and who could help my students understand the challenges that D&I poses to both corporate leadership and day-to-day operations. 乌鸦传媒 felt like a natural fit.

The focus for the 2025 student challenge 

Karine: Each year, we set the students a challenge, designed to stretch their thinking 鈥 past topics have included understanding the role of ENGs as inclusion activators or discussions on the emerging debate on inclusion versus meritocracy, or whether DEI trainings should be mandatory or voluntary. The topic this year, 鈥2025 鈥 a turning point for DEI,鈥 was set to encourage a focus on emerging trends, even before the US executive orders were issued in January 2025.

Students were briefed to provide a rational analysis of the global situation, factoring in opportunities and risks from a regional perspective, and drawing on concepts developed during Matteo鈥檚 classes, and fed with their own academic research. 

Matteo: We鈥檙e seeing a global narrative shift: before January 2025, we needed DEI corporate programs to not discriminate against minorities and people from non-privileged backgrounds. Particularly those who were unable to reach positions of power in a corporate setting. 

The Executive Orders in the US tell us the contrary; we now need to dismantle these programs 鈥 to not discriminate, following the 2023 Supreme Court ruling ending affirmative action in the US education system.  

In the US, the risks for companies who do not comply with regulations is financially high, compared to Europe. So the narrative has changed, and private organizations (if they have federal funding or not) are in many cases, abiding.  

This team assignment encouraged students to consider how global and local organizations continue to build diverse and inclusive places to work: where the definition of diversity, the collection of people data, work-related policies and benefits and more are directly impacted by local laws around the world. 

The findings from our student teams 

Matteo: As my colleague and panel member Marcelle Lalibert茅 has said, for major global companies, it鈥檚 as if you鈥檙e steering a global organization through rapidly shifting waters 鈥 with political tides in the US pushing back on diversity efforts, in Europe you鈥檙e facing regulatory currents that require you to provide details on pay gaps, and in the Middle East you may be aiming to embed global DEI standards into a local context. Against this backdrop, the student teams highlighted several risks:  

  • Legal vulnerability 鈥 organizations are facing new legal and regulatory challenges pulling in different directions: from executive orders in the US rescinding diversity initiatives to the increased (and evolving) public reporting duties of the EU Corporate Social Reporting Directive (CSRD) and strengthened anti-discrimination laws in APAC.  
  • Potential political and cultural backlash for company reputations, as they attempt to strike the balance between supporting marginalized groups and inclusion for all.  
  • Slower progress on DEI goals 鈥 economic downturns means DEI budgets, roles, and overall progress is at risk, as companies prioritize cost-cutting. 
  • Talent exodus 鈥 most job seekers consider workplace diversity important when evaluating companies, and may look elsewhere if organizations change their commitments.  

With D&I at a crossroads, the student teams identified some key opportunities in shaping and evolving global strategies: 

  • Establishing a flexible DEI framework allows for region-specific modifications while maintaining a unified global commitment. 
  • Skills-based hiring and inclusive leadership 鈥 continuing merit-based hiring and leadership development enhances diversity while ensuring compliance in restrictive regions. 
  • Compliance as a competitive advantage 鈥 successfully delivering on ESG commitments can position a company as an industry leader in fair and inclusive practices and continue to attract talent. 

Key reflections for organizations like 乌鸦传媒 

Karine: The students navigated an extremely complex topic. Overall, the recommendations from the student teams followed broad themes for global organizations to consider: 

  1. Reaffirm and communicate organizational commitment toward the diversity and inclusion ambition, as a fundamental ingredient of their identity and success 
  2. Demonstrate agility, repositioning DEI initiatives to make them accessible for all and more engaging for all employees, and partnering with talent, health and safety, or wellbeing programs 
  3. Use data-driven insights and employee feedback to guide actions and increase transparency on global and location actions and impact 
  4. Leave flexibility for localized DEI initiatives and expertise under a global framework, strengthening leadership pipelines and fostering a culture of belonging through education and mentorship 
  5. Build client-focused strategies to strengthen relationships, collaborate, and grow. 

The presentations from the teams were excellent. Inclusion in the workplace is critical for all businesses. We were delighted to hear their views on the complex situation in 2025, building their experiences and helping them to be ready to make an impact in their future. 

Together with HEC Paris, I look forward to another year of our continued collaboration!

Karine Vasselin

Expert in Diversity and Inclusion
Karine Vasselin is the Group 鈥淚nclusive Futures鈥 Lead at 乌鸦传媒. With an initial background in research and teaching, Karine is an experienced HR Business Partner and People Manager. A strong advocate of embedding inclusion into business and operating models, she is actively involved in developing joint initiatives with Universities, NGOs, and partners in her ecosystem.

Matteo Winkler

Associate professor of business and human rights in HEC Paris.
Matteo Winkler is an associate professor of business and human rights in HEC Paris. His research interests and most recent publications, all in top academic law journals, span non-discrimination in sports, international contracts, and human rights.

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    FinOps excellence unlocked: Our strategic differentiators /fi-en/insights/expert-perspectives/finops-excellence-unlocked-our-strategic-differentiators/ /fi-en/insights/expert-perspectives/finops-excellence-unlocked-our-strategic-differentiators/#respond Tue, 15 Jul 2025 07:40:01 +0000 /fi-en/?p=546993&preview=true&preview_id=546993 FinOps is more than a methodology. It鈥檚 a cultural shift that promotes accountability by aligning cloud engineering and finance teams to function as a cohesive unit. This collaboration enables near real-time, data-driven decision-making to ensure every dollar spent is optimized.

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    FinOps excellence unlocked: Our strategic differentiators

    Deepak Shirdhonkar
    Deepak Shirdhonkar
    Jul 15, 2025

    颁补辫驳别尘颈苍颈鈥檚 winning formula for financial operations excellence

    FinOps is more than a methodology. It鈥檚 a cultural shift that promotes accountability by aligning cloud engineering and finance teams to function as a cohesive unit. This collaboration enables near real-time, data-driven decision-making to ensure every dollar spent is optimized.

    However, the FinOps team has encountered several challenges when a structured approach is not consistently applied. While FinOps offers a robust framework of principles and capabilities, implementing isolated initiatives or selectively adopting a few principles on an ad hoc basis often results in only short-term gains. Enterprises struggle to realize the full potential of FinOps due to fragmented adoption and the absence of a unified strategy.

    Some of the key challenges include:

    • Delays in execution: Cloud engineers often face bottlenecks due to delayed approvals from the application portfolio team, impeding progress on proposed initiatives.
    • Lack of real-time insights: The absence of a comprehensive tooling platform limits access to timely data, making informed decision-making difficult.
    • Unclear ownership: Limited visibility about relevant technical and functional stakeholders who owns the cloud resources hampers the ability to drive decisions forward efficiently.

    A cohesive and well-structured FinOps strategy is essential to overcoming these barriers and unlocking long-term value.

    In our approach to FinOps, we collaborate closely with enterprises to establish a top-down framework that is strengthened by executive sponsorship and empowered teams. At the heart of our approach lies transparency, which serves as the foundation for all decision-making and collaboration. overall methodology is built on the three pillars:

    1. People 鈥 Empowering FinOps team with clear roles and accountability
    2. Assets 鈥 Aligning strategic vision with financial and operational goals
    3. Tools 鈥 Leveraging robust tools and data to drive informed, real-time decisions.

    Designated people forming the FinOps team 鈥 including FinOps practitioners, assigned engineers, and analysts 鈥 collaborate across teams to conduct a comprehensive 360掳 analysis of cloud resources, aligned with each FinOps capability. To help customers initiate their FinOps journey, we鈥檝e developed a Flash Assessment. This instrument is designed to provide a clear understanding of the current ecosystem and identify key areas for optimization around strategy, cloud consumption visibility, optimization, adoption, and tooling and automation.

    Once the initial step toward FinOps is complete, we advocate for treating FinOps not as a linear lifecycle but as a continuous, iterative process. This approach empowers clients to embrace a dynamic and ongoing cloud operations model, i.e., FinOps as a service.

    FinOps should evolve through progressive stages, starting with Crawl, advancing to Walk, and eventually reaching Run. This phased approach allows organizations to begin with a modest scope and gradually scale in size, complexity, and capability. To support this journey, we鈥檝e developed a FinOps Maturity Assessment based on proven, cloud-agnostic best practices drawn from our extensive experience across diverse enterprises. This assessment helps customers establish a clear baseline for FinOps adoption across key capability areas.

    乌鸦传媒 Flash Assessment is a rapid, high-level evaluation methodology applied across various domains. On the other side, a FinOps Maturity Assessment offers a structured approach to evaluating an organization鈥檚 capabilities in managing cloud financial operations.

    Additionally, we鈥檝e developed a comprehensive internal FinOps repository that serves as a centralized resource hub. These resources are thoughtfully curated to help optimize operations and enhance the financial efficiency of cloud infrastructure services. It includes:

    • Standard operating procedures to guide consistent execution
    • An automation library focused on streamlining and automating key FinOps initiatives to boost efficiency
    • A best practices cookbook that captures industry-standard approaches.

    In today鈥檚 dynamic enterprise environment, organizations rely on a broad spectrum of FinOps tools, including cloud-native services, third-party applications, open-source tools, and custom build/proprietary platforms to meet their operational goals. Our strategy is intentionally designed to be flexible and inclusive. We support native tools from hyperscalers, client-owned FinOps solutions, and third-party platforms alike. This approach ensures resilient and adaptable support for FinOps operations, regardless of the tooling landscape.

    Complementing these tools, we offer internally developed dashboards, both hyperscaler-specific and multicloud, that empower data-driven decision-making across FinOps initiatives.

    Our differentiator: FinOps beyond basics We take a forward-thinking approach to FinOps, one that goes beyond the traditional focus on IaaS cost optimization through resource tuning, waste reduction, or rate negotiation. Instead, we enable enterprises to significantly advance their FinOps maturity by adopting our accelerators with a comprehensive and step-by-step approach:

    This holistic approach empowers organizations to undergo a cultural and operational transformation, integrating financial accountability, engineering agility, and real-time decision-making. We emphasize adopting these principles collectively, as overemphasis on any single area may lead to imbalances and unintended challenges.

    About the author

    Deepak Shirdhonkar

    Deepak Shirdhonkar

    Senior Hyperscaler Architect, FinOps Lead & Full Stack Distinguished Engineer
    Deepak is a seasoned professional with 18 years of rich experience in architecture, transformation projects, and developing and planning solutions for both public and private cloud environments. Deepak has extensive technical acumen in AWS, Google, FinOps, and Network. Academically, Deepak holds a Master of Technology in Thermal Engineering from Maulana Azad National Institute of Technology. Deepak serves as the Lead Architect for Cloud Delivery in CIS India at 乌鸦传媒. Throughout Deepak’s career, Deepak has taken on various roles, including Technical Lead, Infra Architect, and Cloud Architect.

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      Beyond the hype: Why agentic AI is a must-have for today鈥檚 businesses /fi-en/insights/expert-perspectives/beyond-the-hype-why-agentic-ai-is-a-must-have-for-todays-businesses/ /fi-en/insights/expert-perspectives/beyond-the-hype-why-agentic-ai-is-a-must-have-for-todays-businesses/#respond Mon, 19 May 2025 06:54:43 +0000 /fi-en/?p=545625&preview=true&preview_id=545625 Beyond the hype: Why agentic AI is a must-have for today鈥檚 businesses

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      Beyond the hype: Why agentic AI is a must-have for today鈥檚 businesses

      Rajesh Iyer
      May 19, 2025

      鈥淓veryone is obsessing over agentic AI, and rightfully so. When it comes to operational agility, autonomous agentic systems are set to deliver game-changing benefits to enterprises. In the coming years, the successful integration of these systems won鈥檛 just be a good idea, it鈥檒l be the defining factor that separates industry leaders from the rest of the competition.鈥 鈥 Rajesh S. Iyer 

      In our world, there are many kinds of agents. Travel agents help us book travel plans, with everything from flight bookings to hotel reservations falling under their jurisdiction. Sports agents help professional athletes navigate the legal and business side of sports, enabling clients to maximize their career and financial opportunities. Secret agents typically deal with top-secret matters.  

      What about AI agents? Regarded for their intelligence and ability to tackle business challenges with flexibility and precision, AI agents have quickly become a hot topic for business leaders. The same goes for autonomous AI systems, which are growing increasingly more prominent within organizations.  

      While the terms agentic AI and autonomous AI are often used interchangeably, these systems have distinctive qualities that set them apart. Autonomous AI refers to systems that can operate independently within predefined parameters, like self-driving cars or factory robotics. On the other hand, agentic systems are equipped with a deeper sense of agency. These systems are designed to actively pursue goals, dynamically adapt strategies, and make context-dependent decisions. In short, all agentic AI is autonomous, however not all autonomous AI is agentic.  

      As more organizations look to integrate AI agents and autonomous AI systems into their operations, a new kind of partnership between people and technology is emerging 鈥 one that鈥檚 pushing businesses to learn and evolve. 

      Making a real-world impact: from education to finance 

      The benefits of AI agents and autonomous AI systems are already materializing across industries. In an effort to enhance its learning experiences, a US-based non-profit education company recently started leveraging an that autonomously supports educators and students. Providing teachers with an online teaching assistant and students with an online learning coach, this system helps break complex educational goals into actionable tasks 鈥 completely revolutionizing the classroom experience.  

      The financial sector is also reeling in the benefits of autonomous agentic systems. In the US, a major bank is using to autonomously handle tasks like interest rate queries, account openings, and fund transfers, drastically improving operational efficiency. Across the globe in India, a leading digital lending and savings platform is leveraging an to automate its customer support services. Since integrating the agent into their operations, the platform has managed to automate 70% of its support tickets in multiple languages, delivering a vast reduction in costs and faster ticket resolution times. 

      As organizations continue to leverage these systems and the technology itself continues to develop, benefits such as those mentioned here are just the beginning of a much broader transformation.  

      Looking forward: a bright future ahead  

      Agentic systems are at the forefront of the next wave of automation and AI. Representing a powerful shift for enterprises, these systems are positioned to improve operational efficiency, workplace collaboration, and customer satisfaction 鈥 transforming how organizations across industries pursue their strategic objectives.  

      Though the benefits of agentic systems are certainly apparent, human oversight and the continuous adaptation of these systems are paramount for their success. Collaboration between humans and technology must remain at the core of any agentic system to build trust, safeguard privacy, and ensure resilience. As challenges like missing data, system outages, or other unexpected conditions arise, businesses must be able to adjust their systems at speed. Addressing this confluence of factors will dictate whether organizations successfully integrate autonomous agentic systems into their value chains. 

      These agents aren鈥檛 just tools, but rather catalysts for change capable of unlocking new levels of productivity, personalization, and innovation. The path forward is full of promise for those who are ready to embrace the next chapter of AI-powered business operations. As humans and machines continue to collaborate, the possibilities are only beginning to unfold. 

      Important Definitions 

      Agentic AI  

      Agentic AI refers to AI systems that can act and reason autonomously, collaborate with humans, adapt to changing environments, and use enterprise tools. These systems are designed to act with goals in mind, and are capable of making decisions, taking initiative, and carrying out complex tasks to achieve specific outcomes. 

      Autonomous AI  

      Autonomous AI refers to AI systems that can operate and process data without human interaction or oversight. These systems perform tasks independently and continuously learn from input data to become more efficient over time. 

      Learn more 

      • TechnoVision 2025 鈥 your guide to emerging technology trends 
      • Autonomous Agent Alliance – a new trend in We Collaborate 
      • Voices of TechnoVision 鈥 a blog series inspired by 颁补辫驳别尘颈苍颈鈥檚 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

      Rajesh Iyer

      Global Head of AI and ML, Financial Services 乌鸦传媒 & Data
      Rajesh is the Global Head of AI and ML for Financial Services. He has almost three decades of of experience in the Financial Services Industry, working with Fortune/Global 500 clients seeking to maximize the value of investments in their Enterprise Data and AI programs.

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        Should we use generative AI for embedded and safety software development? /fi-en/insights/expert-perspectives/should-we-use-generative-ai-for-embedded-and-safety-software-development/ /fi-en/insights/expert-perspectives/should-we-use-generative-ai-for-embedded-and-safety-software-development/#respond Tue, 13 May 2025 09:56:33 +0000 /fi-en/?p=545173&preview=true&preview_id=545173 The idea of deploying generative AI (Gen AI) in software for safety critical systems may sound like a non-starter. With AI coding implicated in declines in code quality, it鈥檚 hard to imagine it playing a role in the safety-critical or embedded software used in applications like automatic braking, energy distribution management, or heart rate monitoring.

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        Should we use generative AI for embedded and safety software development?

        Vivien Leger
        May 6, 2025
        capgemini-engineering

        The idea of deploying generative AI (Gen AI) in software for safety critical systems may sound like a non-starter. With , it鈥檚 hard to imagine it playing a role in the safety-critical or embedded software used in applications like automatic braking, energy distribution management, or heart rate monitoring.

        Engineering teams are right to be cautious about Gen AI. But they should also keep an open mind. Software development is about much more than coding. Design, specification, and validation can collectively consume more time than actual coding, and here, Gen AI can significantly reduce overall development time and cost. It could even improve quality.

        Incorporating Gen AI in safety-critical environments

        Before we come onto these areas, let鈥檚 quickly address the elephant in the room: Gen AI coding. AI code generation for safety-critical software is not impossible, but it would need extensive training of the AI algorithms, rigorous testing processes, and will bring a lot of complexities. Right now, Gen AI should never directly touch a safety-critical line of code. But we should certainly keep an eye on it, as Gen AI code writing as it advances in other sectors.

        However, other areas 鈥 from specification to validation 鈥 are ripe for Gen AI innovation. Our recent 乌鸦传媒 Research Institute report, Turbocharging software with Gen AI, found that software professionals felt Gen AI could assist with 28% of software design, 26% of development, and 25% of testing in the next two years. In the report, one Senior Director of Software Product Engineering at a major global pharmaceutical company was quoted as saying: 鈥渦se cases like bug fixing and documentation are fast emerging, with others like UX design, requirement writing, etc. just around the corner.鈥

        Software design

        Let鈥檚 consider how the software development journey may look, just a few years from now. Let鈥檚 say you are designing a control system for car steering, plane landing gear, or a medical device (pick a product in your industry).

        Right at the start, you probably have a project brief. Your company or customer has given you a high-level description of the software鈥檚 purpose. Gen AI can analyze this, alongside regulatory standards, to propose functional and non-functional requirements. It will still need work to get it perfect, but it has saved you a lot of time.

        However, you want to go beyond technical requirements and ensure this works for the user. Thus, you ask Gen AI to develop a wide range of user stories, so you can design solutions that pre-empt problems. That includes the obvious ones you would have come up with, Gen AI just writes them more quickly. But it includes all the weird and wonderful ways that future customers will use and abuse your product, ways that never would have occurred to a sensible software engineer like you.

        In most cases, this is about improving the user experience, but it could also prevent disasters. For example, many of Boeing鈥檚 recent troubles , which led to two crashes. While the software was a technically well-designed safety feature, its implementation overlooked pilot training requirements and risks from sensor failures. This is the sort of real-world possibility that Gen AI can help identify, getting engineers who are laser-focused on a specific problem to see the bigger picture.

        Armed with this insight, you start writing the code. While the AI doesn鈥檛 have any direct influence on the code, you may let it take a hands-off look at your code at each milestone, and make recommendations for improvements against the initial brief, which you can decide whether to act upon.

        Test and validation

        Once you have a software product you are happy with, Gen AI is back in the game for testing. This is perhaps one of its most valuable roles in safety-critical systems. In our CRI report, 54% of professionals cited improved testing speed as one of the top sources of Gen AI productivity improvements.

        Gen AI can start the verification process by conducting a first code review, comparing code industry standards (eg. for automotive, for aerospace), to check for errors, bugs, and security risks. You still need to review it, but a lot of the basic stuff you would have spent time looking for has been sorted in the first pass, saving you time, and giving you more headspace to ensure everything is perfect.

        Once you are satisfied with the product, you want to test it. Your Gen AI assistant can quickly generate test cases 鈥 sets of inputs to determine whether a software application behaves as expected 鈥 faster and more accurately than when you did it manually. This is already a reality in critical industries, as Fabio Veronese, Head of ICT Industrial Delivery at Enel Grids noted in our report that his company uses generative AI for user acceptance tests.

        And, when you are confident your software product is robust, Gen AI can help generate the 鈥榩roofs鈥 to show it works and will function under all specified conditions. For example, in the rail industry, trains rely on automated systems to process signals, ensuring trains stop, go, or slow down at the right times. Gen AI can look at data readouts and create 鈥榩roofs鈥 that show each step of the signal processing is done correctly and on time under various conditions 鈥 and generate the associated documents.

        In fact, as you progress through these processes, Gen AI can expedite the creation and completion of required documentation, by populating predefined templates and compliance matrices with test logs. This ensures consistency and accuracy in reporting and saves engineering time.

        Automating processes

        Gen AI can also help you automate many laborious processes that can be so mundane that human brains struggle to stay focused, thus creating the risk of error.

        Take the example of the process used in the space industry for addressing software defects. When a defect is discovered, developers must create a report documenting this defect, develop a test to reproduce the defect, correct the defect in a sandbox, put the updated software through a verification process, reimplement the corrected code back into the main project, and finally test it in within the product.

        A five-minute code fix may take hours of meetings and tens of emails. This is exactly the sort of task Gen AI is well suited to support. Any organization writing safety-critical software will have hundreds of such tedious documentation and procedural compliance processes. We believe (in some cases) that as much as 80% of the time could be saved in such processes by deploying Gen AI for routine work.

        Don鈥檛 just take our word for it. Speaking to us for our report, Akram Sheriff, Senior Software Engineering Leader at Cisco Systems notes that, 鈥淥ne of the biggest drivers of generative AI adoption is innovation. Not just on the product side but also on the process side. While senior professionals leverage generative AI combined with their domain expertise for product innovation, junior professionals see value in AI process and tool innovation, and in automation and productivity optimization.鈥

        Managing the risks to get the rewards

        Despite all these opportunities, we must acknowledge that this is a new and fast-moving field. There are risks, including the correctness of outputs (Gen AI can hallucinate plausible but wrong answers), inherited risk from underlying models, and bias in training data. But there are also risks of not acting out of fear, and missing out on huge rewards while your competitors speed ahead.

        Gen AI needs safeguards, but also a flexible architecture that allows companies to quickly adopt, test, and use new Gen AI technologies, and evolve their uses as needs demand.

        In our report, we propose a risk model (see image 1). It states that any use of Gen AI requires (a) a proper assessment of the risks and (b) that 鈥 where mistakes could have serious consequences 鈥 you have the expertise to assess whether the outputs are correct.

        Image 1: A risk assessment framework to kickstart generative AI implementation in software engineering

        For now, safety-critical code creation will fall into 鈥楴ot safe to use鈥, because the consequence of error is high, and the expertise needed to assess the code would probably be more of a burden than starting from scratch. However, testing would fall into 鈥楿se with caution鈥, because it would provide valuable insights about software behavior, that experts can assess.

        Finally, a key part of managing risks is comprehensive user training to understand how Gen AI works and its strengths and weaknesses. In our research, 51% of senior executives said that leveraging Gen AI in software engineering will require significant investment to upskill the software workforce. Yet only 39% of organizations have a generative AI upskilling program for software engineering.

        There is a real risk of becoming overly reliant on, or trusting of, Gen AI. We must ensure that humans retain their ability to think critically about the fundamental nature of software and safety. Software engineers must be well-informed and remain actively engaged in verification and decision-making processes, so they can spot problems and be ready to step in if Gen AI reaches its limits.

        In conclusion

        While Gen AI won’t be building safety-critical software on its own anytime soon, it has the potential to enhance development, documentation, and quality assurance right across the software development lifecycle. In doing so, it can not only save time and money, and speed time to market, but it can even improve safety.

        Companies like 乌鸦传媒 can help shape achievable, phased roadmaps for Gen AI adoption. We guide organizations to integrate AI carefully, following sensible adaption and risk management frameworks and deploying appropriate training, ensuring both its potential and limitations are carefully navigated.

        Download our 乌鸦传媒 Research Institute report Turbocharging software with Gen AI to learn more.

        Gen AI in software

        Report from the 乌鸦传媒 Research Institute

        Meet the author

        Vivien Leger

        Head of Embedded Software Engineering
        With over 14 years of experience, Vivien has led teams in building a culture focused on technical excellence and customer satisfaction. He has successfully guided software organizations through their transformation journeys, aligning technology with business goals and designing strategic roadmaps that accelerate growth and profitability.

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          Trends in 2025 for Smart Cities /fi-en/insights/expert-perspectives/trends-in-2025-for-smart-cities/ /fi-en/insights/expert-perspectives/trends-in-2025-for-smart-cities/#respond Mon, 12 May 2025 07:37:52 +0000 /fi-en/?p=544988&preview=true&preview_id=544988 With more than half the global population now living in cities, urban areas are under immense pressure to adapt to growing populations and environmental concerns. Smart cities are rising to the challenge, integrating advanced technologies to improve infrastructure, enhance public services, and foster sustainable living. This will also ensure inclusivity, while improving the quality of life for urban dwellers.

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          Trends in 2025 for Smart Cities

          Hans Teuben, Luc Baardman, Ravi Shankar Arunachalam & Ambika Chinnappa
          Apr 15, 2025

          Technology is redefining urban living. Rapid urbanization this century has transformed cities into bustling centers of growth and innovation. However, this progress comes with challenges, such as resource management, climate resilience, and efficient governance. In 2025, emerging technologies will play a pivotal role in reimagining how cities function at scale.

          With more than half the global population now living in cities, urban areas are under immense pressure to adapt to growing populations and environmental concerns. Smart cities are rising to the challenge, integrating advanced technologies to improve infrastructure, enhance public services, and foster sustainable living. This will also ensure inclusivity, while improving the quality of life for urban dwellers.

          The following insights into the trends shaping the future of our cities reveal that a new chapter in urban living is under way.

          With cities getting smarter, novel digital services鈥攕uch as smart grids, on-demand mobility, smart water management鈥攁re reinventing public service models and processes. At the same time, they are driving an unprecedented surge in data generation and flows. Urban data platforms serve as the essential infrastructure for effectively utilizing city data to enhance operational efficiency and scale smart city initiatives. They connect, analyze and visualize all data from diverse domain systems in urban fabric. From here, data can be further shared to city services or third-party private entities, enabling innovative business models to flourish.

          As part of the project, Rotterdam, Ume氓聽and Glasgow developed urban data platforms to tackle respective city specific challenges. The Digital City Platform in Rotterdam聽discloses and visualizes actual energy use, as well as use over a period of time (by individual buildings, as well as the whole area). is connected to the platform and, together with real-time data, it forms a 3D digital twin of the city. This 3D digital twin supports Rotterdam in crowd and public space management, smart mobility, electricity and thermal grid planning and operational optimization, as well as energy and resource efficient waste collection and processing.
          Cities are also beginning to adopt a federated data spaces model to facilitate sovereign and secure ways of data sharing across city domains, as well as across cities and borders. EU-funded initiatives such as the have developed a multi-stakeholder data governance blueprint. This initiative creates a cross-sectoral data space for governments and their providers, enabling interoperability to improve service delivery to citizens. Several pilot projects鈥斺攁re underway in the DS4SSCC program where multiple cities are collaborating to co-create value.

          Digital twins and IoT technologies are shaping optimized city operations feeding off data from urban data platforms. By creating virtual models of cities, planners can simulate and test the impact of new developments, identify potential issues, optimize city services and proactively create policies to avoid future impact. Through simulation, monitoring, and optimization of various urban elements, digital twins help cities achieve a balance between economic growth, efficient operations, and environmental protection.听

          Depending on the maturity levels, cities are adopting digital twin solutions that range from descriptive analysis and predictive intelligence to scenario simulations.听
          The platform is a digital twin of the city-state, providing a dynamic 3D model that enables users across various sectors to develop advanced tools and applications for testing concepts and services. It also supports planning, decision-making, and research on innovative technologies to address complex and emerging challenges.听
          Shanghai has developed an extensive to monitor and manage city operations, including traffic flow, energy consumption, and environmental conditions. This digital representation aids in optimizing urban planning and improving public services.
          As the next evolution, digital twin models are overlaid with immersive experience technologies such as augmented reality (AR), virtual reality (VR) and mixed reality (MR), to provide additional context about the urban elements. 聽 (Citiverse) was launched by the International Telecommunication Union (ITU), the United Nations International Computing Centre (UNICC) and Digital Dubai to provide normative guidance and framework for virtual world solutions in cities.
          Digital twins and citiverse initiatives are redefining city operations by making urban environments more efficient, resilient, and citizen-friendly.

          With increasing frequency of extreme weather events, cities need to buckle up, investing in the resilience of their infrastructure. From IoT-enabled flood monitoring systems to predictive analytics for disaster management, urban areas are focusing on safeguarding both people and resources. Smarter water systems address challenges like scarcity through innovative recycling and distribution methods. Physical systems, such as water systems, were not built with the digital age in mind. Yet rebuilding is also often not an option given the enormous costs of (temporary) replacements. A mitigation can be found in retrofitting 聽these physical assets to digital infrastructures using sensors and remote-control digital components. A great example can be found in France with Voies navigables, the French inland waterway network facilitator.
          Another compelling example of climate adaptation strategies can be found in the battling of urban heat islands (UHRs). For instance, the city of has undertaken significant measures, such as planting trees, revamping its iconic zinc rooftops, and installing cooling public infrastructure, to reduce heat retention. Similarly, adapted ancient Persian techniques by using qanat water supply systems, enhanced with renewable energy, to cool buildings through water circulation within walls. These initiatives exemplify the proactive steps European cities are taking to mitigate the effects of urban heat islands. Albeit the outcome is physical, extensive modelling in digital twins forms the basis upon which cities act.

          Governments across the globe are no longer merely setting ambitious climate goals, they are operationalizing these commitments into tangible outcomes. The European Green Deal stands as a hallmark initiative, aiming to make the EU the world鈥檚 first climate-neutral continent by 2050. Under this framework, the program, launched in May 2022, has achieved significant milestones: for the first time, electricity generation from wind and solar has surpassed gas, with an 18% reduction in gas consumption in just two years.
          Governments understand that they need to lead by example. The global with its 18 partner nations has set stringent targets for net-zero emissions in government agency operations by 2050. This initiative employs strategic measures like carbon pollution-free electricity, net-zero buildings & operations, zero-emission vehicles, climate resilient infrastructure & operations, and circular economy practices. Progress is evident: Australia achieved a more than in operations in 2022 compared to the previous year.
          鈥 Local Governments for Sustainability is a global network working with more than 2,500 local and regional governments committed to sustainable urban development. Active in 125+ countries, this network is influencing sustainability policy and driving local action for zero emission, nature-based, equitable, resilient and circular development. City agencies are increasingly leveraging circular economy principles, transforming waste into raw materials and fostering innovative business models. Amsterdam is a pioneer city in sustainable and circular urban development and is focused on three value chains鈥攆ood and organic waste streams, consumer goods, and built environment.听 It is constantly tracking progress through a .听
          Despite notable progress, governments face hurdles, such as budget constraints, siloed institutional frameworks, cultural resistance to change, and complexities in measuring and reporting progress. Overcoming these barriers demands a combination of political commitment, inter-agency collaboration, investment in innovation, and robust public-private partnerships. Sharing global best practices will be critical in refining sustainability strategies and achieving long-term goals.

          聽Health as a priority for urban planners
          Environmental health technologies will take center stage in urban planning. After all, cities are made for humans to thrive. Sensors will be used to monitor air quality, noise pollution, and other factors that influence well-being. Predictive health tools will guide the development of spaces that support healthier lifestyles. An earlier study showed the potential for a quick return-on-investment, with savings reported by of between 485-700鈧 per inhabitant. A stark demographic fault line is, however, emerging, splitting urban centers into two distinct camps: old and young.
          Aging cities, primarily in high-income nations and parts of the developing world, face a demographic crunch. Public transit systems, pedestrian infrastructure, even housing鈥攁ll demand costly retrofits to accommodate aging populations. Economically, these cities struggle with a shrinking workforce shouldering the weight of pension systems and healthcare needs. To address this issue, is exploring the development of AI-driven robots, such as AIREC, designed to assist with tasks like shifting patients, cooking, and folding laundry. Meanwhile, youthful cities are experiencing the inverse. Here, labor markets churn with opportunity, powered by policies prioritizing education, employment, and entrepreneurial ambition. But these cities aren鈥檛 without growing pains. Pollution, congestion, and urban stress loom large, as does a rising tide of respiratory disorders and mental health struggles among young, high-strung populations. One creative solution is a low cost and flexible gondola-like ride hailing network being piloted in . This cable car transit system will appeal to younger residents seeking efficient and sustainable mobility options.

          The road ahead: Challenges and opportunities

          The future of urban living will be defined by how effectively cities adopt and integrate these technological innovations. While the potential benefits are immense鈥攕marter resource management, reduced environmental impact, and improved citizen experiences鈥攕uccess depends on political commitment, societal acceptance, and the ethical use of technology.

          In 2025, smart cities will not only focus on innovation but also on creating inclusive, resilient, and sustainable communities. By leveraging the technologies shaping today鈥檚 urban transformation, we can build cities that thrive in harmony with people and the planet.

          Authors

          Luc Baardman

          Managing Consultant and Lead Enabling Sustainability 乌鸦传媒 Invent NL
          鈥淪ustainability at its core is the most important transformation question of our time. Left unanswered, it will wreak havoc upon the world and its population, and it is up to all of us to play our part in becoming sustainable in an inclusive manner. 颁补辫驳别尘颈苍颈鈥檚 part is to remove the impediments for a better future, to truly enable sustainability.鈥

          Ravi Shankar Arunachalam

          Public Administration & Smarter Territories SME – Global Public Sector
          “As a Public Sector strategist and technologist at 乌鸦传媒, I assist local, state, and federal governments worldwide in harnessing the full potential of a collaborative, Government-as-a-platform model to revolutionize citizen service delivery. With a deep understanding of industry challenges, citizen expectations, and the evolving technology landscape, I develop systemic transformation strategies and solutions that provide lasting value to both people and the planet”

          Hans Teuben

          Director Strategy and Innovation Public Sector – Smart Cities and Mobility
          “We take cities and citizens on a journey to address societal challenges using digitization and data: Tackling environmental, sustainability and mobility issues, improving quality of life, overcoming societal divides, and supporting economic development. Our ethical approach prioritizes privacy and security. We help to develop strategy, design and co-create solutions with ecosystems, develop transparent AI and build, run and maintain interoperable data platforms and services for cities.”

          Ambika Chinnappa

          Knowledge Management Lead, Global Public Sector
          鈥淎t 乌鸦传媒, I lead Knowledge Management initiatives to ensure that critical expertise, insights, and best practices are effectively captured, curated, and shared across our global teams. By enabling efficient knowledge flow and collaboration, I help our Public Sector colleagues stay informed, aligned, and empowered to drive impactful outcomes. Through structured KM strategies, I aim to enhance organizational learning, support smarter decision-making, and contribute to the delivery of innovative, sustainable solutions for governments and the communities they serve.鈥

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            You Experience 鈥 Transforming user experience with AI, spatial technologies, and digital twins聽聽 /fi-en/insights/expert-perspectives/you-experience-transforming-user-experience-with-ai-spatial-technologies-and-digital-twins/ /fi-en/insights/expert-perspectives/you-experience-transforming-user-experience-with-ai-spatial-technologies-and-digital-twins/#respond Mon, 05 May 2025 11:43:46 +0000 /fi-en/?p=545186&preview=true&preview_id=545186 As our digital and physical worlds grow more intricately connected, we find ourselves at the start of the next chapter of user experience 鈥 You Experience.

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            You Experience – Transforming user experience with AI, spatial technologies, and digital twins聽聽

            Alexandre Embry
            May 5, 2025

            As our digital and physical worlds grow more intricately connected, we find ourselves at the start of the next chapter of user experience 鈥 You Experience.  

            鈥淪patial computing, digital twins, and AI are blurring the line between the physical and digital. As more businesses look to deliver the hyper-personalized experiences their customers want, they鈥檙e turning towards next-gen technologies that carry the potential to drastically transform user experiences for the better.鈥 鈥 Alexandre Embry 

            In this world, digital interactions no longer consist of just humans using machines. Thanks to advancements in AI, interfaces, and digital twins, these interactions are traversing their technological confinements and impacting our physical world in ways we鈥檇 previously only dreamed of. The result? Businesses are becoming faster, smarter, and greener.  

            Striking a balance 

            With the evolution of user experience comes great responsibility. Human-like agents and cognitive twins are quickly evolving, and to access their full potential, businesses must balance the benefits of hyper-personalization, automation, and efficiency while prioritizing privacy, empathy, and human-touch.  

             
            Despite their ability to deliver speed and precision, it takes the right approach to avoid the misuse of these new technologies and ensure they鈥檙e used sustainably. Over the years, many trends have aimed to bring businesses closer to successfully balancing the forces of innovation. This year, two new trends promise to bring them closer than ever before: “Face to Interface” and “You鈥檙e Something Spatial”.  

            Connecting the digital and physical 

            Recent years have shown an uptick in the volume of human and AI interactions, presenting an opportunity for businesses to craft these interactions in ways that feel more natural. New AI agents, designed to look, act, and behave more like humans, are making this possibility a reality.  With the ability to collaborate, converse, and connect with people, connections with AI are now designed to feel more engaging 鈥 resulting in technologies being viewed increasingly as partners as opposed to just tools. But that鈥檚 only the beginning.  

            Advancements in spatial technologies are also transforming the way we design user experiences. By combining digital twins, real-time 3D (RT3D), and AI-powered vision, this convergence of technology is strengthening the connection between the physical and digital, enabling immersive insights, enhanced decision making, and hyper-personalization. Everything from shopping to the design of factory floors is being uplifted by these technological advancements, leaving businesses across industries eager to leverage them within their value chains.  

            Next steps for businesses 

            How can businesses navigate this new era of experience? Embracing AI and spatial technologies is a necessary first step in improving personalization and designing interactions that feel more human. By integrating AI-driven systems, large vision models, and spatial computing, businesses will realize benefits like improved training, collaboration, and competitiveness.  

            The adoption of digital twins and cognitive agents will also be vital to the successful evolution of user experiences. Enabling organizations to improve human and AI collaboration, automate complex tasks, and reduce errors, these technologies will bridge virtual and physical environments and empower organizations to optimize innovation cycles and drive down costs. 

            Ensuring innovation remains in-line with sustainability must also be a top priority. Organizations will need to walk the tightrope between generating business value and meeting their environmental targets. Doing so will enable them to achieve their goals while also delivering long-term value for the planet.   

            What the future holds 

            As this new era begins to take shape, the integration of next-generation technologies will offer organizations an immense opportunity to redefine what it means to create user experiences. By leveraging AI, digital twins, cognitive agents, and advanced spatial technologies, businesses will achieve levels of personalization, efficiency, and engagement that were previously unobtainable. The next chapter of experience is here, and it鈥檚 time to embrace it.  

            Learn more 

            • TechnoVision 2025 鈥 your guide to emerging technology trends聽
            • You Experience – One of the seven containers of TechnoVision 2025 
            • Voices of TechnoVision 鈥 a blog series inspired by 颁补辫驳别尘颈苍颈鈥檚 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.听

            Meet the author

            Alexandre Embry

            Vice President, Head of the 乌鸦传媒 AI Robotics and Experiences Lab
            Alexandre leads a global team of experts who explore emerging tech trends and devise at-scale solutioning across various horizons, sectors and geographies, with a focus on asset creation, IP, patents and go-to market strategies. Alexandre specializes in exploring and advising C-suite executives and their organizations on the transformative impact of emerging digital tech trends. He is passionate about improving the operational efficiency of organizations across all industries, as well as enhancing the customer and employee digital experience. He focuses on how the most advanced technologies, such as embodied AI, physical AI, AI robotics, polyfunctional robots & humanoids, digital twin, real time 3D, spatial computing, XR, IoT can drive business value, empower people, and contribute to sustainability by increasing autonomy and enhancing human-machine interaction.

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              颁补辫驳别尘颈苍颈鈥檚 Digital Human Avatar is revolutionizing healthcare /fi-en/insights/expert-perspectives/capgeminis-digital-human-avatar-is-revolutionizing-healthcare/ /fi-en/insights/expert-perspectives/capgeminis-digital-human-avatar-is-revolutionizing-healthcare/#respond Wed, 30 Apr 2025 12:19:21 +0000 /fi-en/?p=545248&preview=true&preview_id=545248 乌鸦传媒's digital avatar "Anna" revolutionizes healthcare with emotionally intelligent AI, enhancing patient engagement and operational efficiency.

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              乌鸦传媒’s Digital Human Avatar is revolutionizing healthcare

              Maciej Sowa Regional Portfolio Lead - IA Delivery EMEA, 颁补辫驳别尘颈苍颈鈥檚 Business Services
              Maciej Sowa
              Apr 30, 2025

              乌鸦传媒’s award-winning Digital Human Avatar “Anna” revolutionizes healthcare with emotionally intelligent AI, enhancing patient engagement and operational efficiency.

              Healthcare providers today are increasingly recognizing the need for emotionally intelligent digital platforms that can quickly understand and respond to patients’ emotions.

              But integrating emotionally intelligent AI into any new digital platform requires balancing development with realistic empathetic responses and regulatory demands.

              乌鸦传媒 saw this as an opportunity to develop its Digital Human Avatar (DHA) 鈥 “Anna”鈥 to meet this demand.

              Overcoming challenges with innovation

              However, developing any digital human avatar comes with several challenges. First, developers need to ensure the avatar can address users鈥 needs by transitioning between emotions naturally. Doing this guarantees any avatar can provide truly engaging experiences to its users.

              Next, the data the avatar handles needs to be secured. Therefore, robust encryption and access control processes are implemented to manage sensitive user data effectively.

              Finally, a guided pathway conversation model helps to minimize security and legal issues, ensuring a seamless and secure user experience for every user who engages with the digital human avatar.

              Leveraging technology to achieve significant outcomes

              Based on Dataflow technology, 鈥淎nna鈥 followed this exact model of development. It leverages emotional intelligence to interpret user intent and emotional cues accurately. Its access to the Google Cloud Platform (GCP) also enables it to scale accordingly with patient demand when necessary.

              All this is why 鈥淎nna鈥 has achieved significant milestones to date, including substantial market adoption across the healthcare industry. For example, after just two months, Anna generated 1.01 million views on Facebook, 3,246 landing page link clicks and conducted 1,396 conversations.

              But that鈥檚 not all. 鈥淎nna鈥 was recently announced as a winner at the in the Natural Language Processing category. And although the solution is still highly experimental, further research suggests significant benefits in hyper-personalized services and next-generation analytics across all business process families.

              颁补辫驳别尘颈苍颈鈥檚 Intelligent Process Automation infuses robotic process automation, AI, and smart analytics into your ways of working to deliver an unprecedented level of self-service and automation to your organization to learn more visit our website.

              Meet our experts

              Maciej Sowa Regional Portfolio Lead - IA Delivery EMEA, 颁补辫驳别尘颈苍颈鈥檚 Business Services

              Maciej Sowa

              Regional Portfolio Lead – IA Delivery EMEA, 颁补辫驳别尘颈苍颈鈥檚 Business Services
              Maciej Sowa is a seasoned technology leader with deep expertise in AI, Intelligent Automation, and digital transformation. He excels in delivering innovative solutions that enhance operational efficiency and drive business value. With extensive experience in international environments and complex delivery ecosystems, Maciej is passionate about technological innovation, and delivering pragmatic business value.
              Wojciech Najdyhor, Intelligent Process Automation Practice, 颁补辫驳别尘颈苍颈鈥檚 Business Services

              Wojciech Najdyhor

              Intelligent Process Automation Practice, 颁补辫驳别尘颈苍颈鈥檚 Business Services
              Wojciech Najdyhor is a delivery manager focused on IT services and automation. He leverages the potential of intelligent automation and conversational AI to transform clients鈥 operations and bring value to them and their customers.

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                How accessible are today鈥檚 digital public services? /fi-en/insights/expert-perspectives/how-accessible-are-todays-digital-public-services/ /fi-en/insights/expert-perspectives/how-accessible-are-todays-digital-public-services/#respond Tue, 29 Apr 2025 12:15:58 +0000 /fi-en/?p=545242&preview=true&preview_id=545242 Explore the importance of digital accessibility in public services. Ensure everyone can benefit from online services by 2030.

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                How accessible are today鈥檚 digital public services?

                A photo of Emma Atkins. She has coloured hair in shades of dark blue and purple and is wearing glasses. She wears a floral white top.
                Emma Atkins
                Apr 29, 2025

                The more public services are provided online, the more digital accessibility becomes a fundamental design principle for public sector organizations. So, why are so many disabled people and those with neurodiverse conditions still encountering barriers?

                The European Union has a for key public services to be 100% online by 2030. While this is an admirable ambition, it is important that no-one is excluded from these digital services due to a disability. Additionally, the more accessible government and local authority websites and mobile apps are for everyone, regardless of their visual, hearing, motor, and cognitive abilities, the more effective and cost efficient the delivery of public services becomes. .

                In the following interview, Emma Atkins, software engineer and accessibility expert at 乌鸦传媒 UK, gives her personal perspective on the current accessibility picture in digital public services.

                Is the EU鈥檚 2030 digital target realistic for disabled people and those with neurodiverse conditions?

                No! At least not yet. Of course, it is good to have an ambition to include everyone but, in my opinion, it is beyond the realm of current technology. It doesn鈥檛 consider those so severely disabled they cannot speak, leave their bed, or even tolerate light 鈥 how would they access these services? So, while I welcome the EU鈥檚 2030 digital target, that ambition is only the start. The most disabled people with the most complex needs will be those for whom the most work needs to be done. To create citizen-centric services that work for everyone, government bodies must think accessibility first, design second.

                What digital access barriers do disabled people and neurodivergent citizens still face?

                They face numerous access barriers every single day, in both the digital and real world. This can be anything from a visually impaired person unable to use a screen-reader with a website to a neurodivergent person facing inaccessible language in an app. Or it might be someone with access needs who is completely digitally excluded being asked to make a phone call to get accessible information, ignoring the fact that many people can鈥檛 easily use a phone!

                What impact can digital accessibility have on government policy, as well as on the inclusivity of public information and services?

                It鈥檚 all about money really! Digital accessibility could save governments a lot of money in the long term. How? By allowing citizens to self-serve information and services, rather than needing direct contact with an advisor to do the same thing. Not to mention that inclusivity allows for greater reach of government information to the wider community, thus maximizing the impact of policies, as well as complying with digital inclusion laws.

                What needs to change 鈥 e.g. what鈥檚 stopping investment in digital accessibility?

                Personally, I feel it鈥檚 mostly down to ableism! Either intentionally, or out of ignorance. Some people are unsure of how to make their services accessible and believe it to be more difficult than it is. Others simply don鈥檛 care, believing disabled people to be unimportant, subscribing to rhetoric along the lines that we don鈥檛 work, or do not contribute to society in any way. There is an urgent need to educate non-disabled people about the value of more inclusive thinking and approaches. To achieve the EU鈥檚 2030 target, government and public service agencies should promote an inclusive workplace culture where staff are trained in digital accessibility and the topic is anchored in the department鈥檚 mission statement.  

                Can you give us some real-life examples of accessible design and co-creation?

                The HMRC Mobile App on which I worked achieved full compliance with accessibility standards for two years in a row. This was achieved by putting accessibility first and design second. Simply put, if it wasn鈥檛 accessible, we didn鈥檛 include it.

                For example, we intended to introduce a component to the app that allowed part of the screen to be hidden and revealed at the push of a button, but I had concerns that this would not be suitable for screen reader users. I found ways to ensure this was fully accessible, and we did not include it in the app until it was. As well as drawing on my own expertise as an accessibility expert, we took feedback from disabled users before a professional audit was undertaken by the Digital Accessibility Centre (DAC).

                How are AI and other technologies creating new possibilities?

                The key difference AI is making to me, and disabled programmers like me, is making programming more accessible. More disabled programmers can only be a good thing, as this is likely to lead to more awareness of accessibility needs, a greater focus on accessibility and thus, more accessible services! Not to mention, for non-technical people with access needs, the ability to convert language into plain, easy to understand language for themselves at the push of a button.

                More broadly, AI and other GovTech solutions are beginning to create a more inclusive public sector. For example, there are technological tools available, such as screen readers, magnification software, image description tools, apps that convert text into speech, and AI-supported solutions that interpret visual content and convert it to text or speech. All of these are designed to empower citizens through digital accessibility to public services, creating new possibilities for inclusive citizen-centric government.

                What one digital accessibility action do you want all governments to take right now? 

                To listen. Listening to disabled people and understanding our needs is the only way change will happen. Understanding that we are real individuals, with real lives, dignity and rights, that deserve equal access to services. And then, of course, acting on that.

                So, what action is needed right now? I鈥檝e co-authored a point of view on this, called Public means everybody. We offer recommendations on how to make digital public services work for everyone. We draw on monitoring and research exercises across the EU public sector and show how GovTech is being used to address inaccessible online content and website structures. From proactive engagement with disabled citizens to working with innovative startups in the GovTech sector, we set out a systematic, scalable approach to transforming online government services.

                For more, read Public means everybody: Accessibility first, design second in citizen services.

                Author

                A photo of Emma Atkins. She has coloured hair in shades of dark blue and purple and is wearing glasses. She wears a floral white top.

                Emma Atkins

                Software Engineer and Accessibility Expert
                “Accessibility and inclusion are important for good business, but more than that: they are a design for life. Everything should be accessible to everyone everywhere regardless of individual differences, and I have always been dedicated to the cause of making that ideal a reality. Until that day, I鈥檒l be here doing my bit and refusing to take 鈥榥o鈥 for an answer.”

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                  Online visibility: brands facing the great AI upheaval /fi-en/insights/expert-perspectives/online-visibility-brands-facing-the-great-ai-upheaval/ /fi-en/insights/expert-perspectives/online-visibility-brands-facing-the-great-ai-upheaval/#respond Fri, 25 Apr 2025 12:10:48 +0000 /fi-en/?p=545233&preview=true&preview_id=545233 As highlighted in our Top Tech Trends of 2025 report, generative AI remains a critical focus for businesses today and through its application brands are now able to provide ultra-personalized and contextual responses to their clients.

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                  Online Visibility: Brands facing the great AI upheaval

                  Maxime Girardeau
                  Apr 25, 2025

                  Notably, we are seeing its profound impact on purchasing behaviors as well as a shift from traditional SEO to Generative Engine Optimization (GEO).

                  Online search is shifting from traditional search engines to systems based on generative AI

                  After heavily investing in SEO (Search Engine Optimization), brands are venturing into a new era: GEO (Generative Engine Optimization), where content is optimized for generative artificial intelligence. Is this a liberation or an additional constraint for them?

                  This is a quiet revolution, but one that promises to make a big impact. Having already transformed productivity at work, large language models (LLMs) are profoundly changing purchasing behaviors. According to a , a quarter of French consumers already planned to use AI for their Black Friday and holiday shopping.

                  If consumers are turning away from the search engines, they have relied on for so many years, it is because generative AIs, such as ChatGPT, Gemini, or Perplexity, go further. They no longer simply provide a list of results but offer ultra-personalized and contextual responses based on individual preferences, usage context, and purchase history.

                  A radical change for brands

                  To support this profound transformation in purchasing behaviors, brands must now shift from SEO, focused on keyword optimization for search engines, to a new paradigm: GEO. In this emerging model, a brand’s visibility depends on how its content is integrated into the corpora of generative AIs.

                  Consider the concrete example of a consumer looking for an evening dress. With traditional SEO, results depend primarily on generic keywords such as “luxury evening dresses.” The most well-known brands, which invest the most to be well-referenced, naturally occupy the top positions.
                  In a world dominated by GEO, the response provided by an autonomous agent will more comprehensively integrate the user’s complete profile: their age, measurements, tastes, and social context. The response will no longer be just a well-referenced brand but a statistically optimal and personalized answer.

                  GEO: A new dynamic for brands

                  Is this shift to the GEO era a liberation or an additional constraint for brands? The answer is nuanced.

                  Certainly, this evolution allows brands to escape the hegemony of search engine players and to become known to their target audiences by sharing ultra-personalized information with autonomous agents. A new brand, for example in the cosmetics sector, would benefit from focusing its digital investments directly in GEO, thus bypassing the astronomical costs of traditional SEO which is already dominated by industry leaders.

                  However, for brands in other sectors, the advent of GEO necessitates a complete overhaul of their content production processes. They will first need to define their personas with unprecedented precision, creating extremely detailed customer profiles to meet the specific expectations of autonomous agents. Beyond traditional keywords, brands will need to provide comprehensive responses rich in contextual and comparative data. Finally, they will need to continuously test their visibility within GenAI tools and the relevance of their content within the results generated by LLMs, to constantly adjust and improve their strategy.

                  Towards new performance indicators

                  For brands historically anchored in intensive SEO strategies, this shift represents a new budgetary and technical constraint, requiring new skills in data analysis, content generation, and cloud technology.

                  With GEO, the number of page views will gradually lose its importance in favor of success indicators related to the effective and relevant presence of a brand in the recommendations generated by LLMs.

                  In the coming years, specific tools and common benchmarks should emerge, allowing brands to precisely measure their “AI visibility score,” thus facilitating rapid adaptation to this new information economy. The shift from SEO to GEO marks a decisive turning point in the evolution of the web and how brands reach their consumers. Only those capable of anticipating these changes will be able to stand out

                  Meet the author

                  Maxime Girardeau

                  VP | Head of AI Strategy & Transformation for Southern Central Europe, 乌鸦传媒
                  As Head of AI Strategy & Transformation at 乌鸦传媒, he leads the charge in revolutionizing marketing strategies for enterprise clients through cutting-edge AI technologies. With over 20 years of experience in digital marketing and advertising, he blend strategic insight with expertise to guide organizations through the complexities of AI-driven customer experiences.

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                    From pilots to production: Overcoming challenges to generative AI adoption across the software engineering lifecycle /fi-en/insights/expert-perspectives/from-pilots-to-production-overcoming-challenges-to-generative-ai-adoption-across-the-software-engineering-lifecycle/ /fi-en/insights/expert-perspectives/from-pilots-to-production-overcoming-challenges-to-generative-ai-adoption-across-the-software-engineering-lifecycle/#respond Thu, 24 Apr 2025 12:08:04 +0000 /fi-en/?p=545228&preview=true&preview_id=545228 Discover how generative AI can best be used in the software engineering lifecycle, what its key challenges are, and how to overcome them.

                    The post From pilots to production: Overcoming challenges to generative AI adoption across the software engineering lifecycle appeared first on 乌鸦传媒 Finland.

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                    From pilots to production
                    Overcoming challenges to generative AI adoption across the software engineering lifecycle

                    Keith Glendon
                    Apr 24, 2025
                    capgemini-engineering

                    Generative AI is rapidly revolutionizing the world of software engineering, driving efficiency, innovation, and business value from the earliest stages of design through to deployment and maintenance. This explosive development in technology enhances and transforms every phase of the software development lifecycle: from analyzing demand and modeling use cases in the design phase, to modernizing legacy code, assisting with documentation, identifying vulnerabilities during testing, and monitoring software post-rollout.

                    Given its transformative power, it’s no surprise that the 乌鸦传媒 Research Institute report, Turbocharging Software with Gen AI, reveals that four out of five software professionals expect to use generative AI tools by 2026.

                    However, our experience and research find that to fully realize the benefits, software engineering organizations must overcome several key challenges. These include unauthorized use, upskilling, and governance. This blog explores these challenges and offers recommendations to help navigate them effectively.

                    Prevent unauthorized use from becoming a blocker

                    Our research indicates that 63% of software professionals currently using generative AI are doing so with unauthorized tools, or in a non-governed manner. This highlights both the eagerness of developers to leverage the benefits of AI and the frustration caused by slow or incomplete official adoption processes. This research is validated in our field experience across hundreds of client projects and interactions. Often, such issues arise from an overly 鈥榚xperimental鈥 versus programmatic approach to adoption and scale.

                    Unauthorized use exposes organizations to various risks, including hallucinated code (AI-generated code that appears correct but is flawed), code leakage, and intellectual property (IP) issues. Such risks can lead to functional failures, security breaches, and legal complications.

                    Our 乌鸦传媒 Research Institute report emphasizes that using unauthorized tools without proper governance exposes organizations to significant risks, potentially undermining their efforts to harness the transformative business value of generative AI effectively.

                    To mitigate unauthorized use, organizations should channel the curiosity of their development teams constructively and in the context of managed transformation roadmaps. This approach should include consistently explaining the pitfalls of unauthorized use, researching available options, learning about best practices, and adopting necessary generative AI tools in a controlled manner that maintains security and integrity throughout the software development process.

                    Upskilling your workforce

                    Upskilling is another critical challenge. According to our 乌鸦传媒 Research Institute findings, only 40% of software professionals receive adequate training from their organizations to use generative AI effectively. The remaining 60% are either self-training (32%) or not training at all (28%). Self-training can lead to inconsistent quality and potential risks, as nearly a third of professionals may lack the necessary skills, resulting in functional and legal vulnerabilities.

                    A consistent observation from our field experiences is that alongside the issue of training is a correlated barrier to making sufficient time available for teams to apply training in practical ways, and to evolve the training outcomes into pragmatic, lasting culture change.  Because generative AI is such a seismic shift in the way we build software products and platforms, the upskilling curve is about far more than incremental training.

                    Managing skill development in this new frontier of software engineering will require an ongoing commitment to evolving skills, practices, culture, ways of working and even the ways teams are composed and organized.   As a result, software engineering organizations should embrace a long-term view of upskilling for success.

                    Those that are most successful in adopting generative AI have invested in comprehensive training programs, which cover essential skills such as prompt engineering, AI model interpretation, and supervision of AI-driven tasks. They have begun to build organizational change management programs and transformation roadmaps that look at the human element, upskilling and culture shift as a vital foundation of success.

                    Additionally, fostering cross-functional collaboration between data scientists, domain experts, and software engineers is crucial to bridge knowledge gaps, as generative AI brings new levels of data dependency into the software engineering domain. 乌鸦传媒’s research shows that successful organizations realizing productivity gains from AI are channeling these gains toward innovative work (50%) and upskilling (47%), rather than reducing headcount.

                    Establishing strong governance

                    Despite massive and accelerating interest in generative AI, 61% of organizations lack a governance framework to guide its use, as highlighted in the 乌鸦传媒 Research Institute report. Governance should go beyond technical oversight to include ethical considerations, such as responsible AI practices and privacy concerns.

                    A strong governance framework aligns generative AI initiatives with organizational priorities and objectives, addressing issues like bias, explainability, IP and copyright concerns, dependency on external platforms, data leakage, and vulnerability to malicious actors.

                    Without proper governance, the risks associated with generative AI in software engineering 鈥 like hallucinated code, biased outputs, unauthorized data & IP usage, and other issues ranging from security to compliance risks, can outweigh its benefits. Establishing clear policies, driven in practice through strategic transformation planning will help mitigate these potential risks and ensure that AI adoption aligns with business goals.

                    Best practices for leveraging generative AI in the software engineering domain

                    Generative AI in software engineering is still in its early stages, but a phased, well-managed approach toward a bold, transformative vision will help organizations maximize its benefits across the development lifecycle. In following this path, here are some important actions to consider:

                    Prioritize high-benefit use cases as building blocks

                    • Focus on use cases that offer quick wins to generate buy-in across the organization. These use cases might include generating documentation, assisting with coding, debugging, testing, identifying security vulnerabilities, and modernizing code through migration or translation.
                    • 颁补辫驳别尘颈苍颈鈥檚 research shows that 39% of organizations currently use generative AI for coding, 29% for debugging, and 29% for code review and quality assurance. The critical point here, however, is that organizations take a 鈥榰se case as building blocks鈥 approach. Many currently struggle with what could be called 鈥榯he ideation trap鈥. This trap comes about when the focus is too much on experiments, proofs of concept and use cases that aren鈥檛 a planned, stepwise part of a broader transformation vision. 
                    • When high-benefit use cases are purposely defined to create building blocks toward a north star transformation vision, the impact is far greater. An example of this concept is our own software product engineering approach within 乌鸦传媒 Engineering Research & Development. In late 2023 we set out on an ambitious vision of an agentive, autonomous software engineering transformation and a future in which Gen AI-driven agents autonomously handle the complex engineering tasks of building software products and platforms from inception to deployment. Since that time, our use cases and experiments all align toward the realization of that goal, with each new building block adding capability and breadth to our agentive framework for software engineering.

                    Mitigate risks

                    • All productivity gains must be balanced within a risk management framework. Generative AI introduces new risks that must be assessed in line with the organization’s existing risk analysis protocols. This includes considerations around cybersecurity, data protection, compliance and IP management. Developing usage frameworks, checks and quality stopgaps to mitigate these risks is essential.

                    Support your teams

                    • Providing comprehensive training for all team members who will interact with generative AI is crucial. This training should cover the analysis of AI outputs, iterative refinement of AI-generated content, and supervision of AI-driven tasks. As our 乌鸦传媒 Research Institute report suggests, organizations with robust upskilling programs are better positioned to improve workforce productivity, expand innovation and creative possibilities, and mitigate potential risks.

                    Implement the right platforms and tools

                    • Effective use of generative AI requires a range of platforms and tools, such as AI-enhanced integrated development environments (IDEs), automation and testing tools, and collaboration tools.
                    • However, only 27% of organizations report having above-average availability of these tools, highlighting a critical area for improvement.  Beyond the current view of Gen AI as a high-productivity assistant or enabler, we strongly encourage every organization in the business of software engineering to look beyond the 鈥榗opilot mentality鈥 and over the horizon to what .  The first wave of Gen AI and the popularity of these technologies as assistive tools will be a great benefit to routine application development tasks.
                    • For the enterprises that are building industrialized, commercial software products and platforms – and for the experience engineering of the next generation, we believe that the value and even the essentials of competitive survival depend on adopting and building a vision of far more sophisticated AI software engineering capability than basic 鈥榦ff the shelf鈥 code assist tools deliver.

                    Develop appropriate metrics

                    • Without the right systems to monitor the effectiveness of generative AI, organizations cannot learn from their experiences or build on successes. Despite this, nearly half of organizations (48%) lack standard metrics to evaluate the success of generative AI use in software engineering. Establishing clear metrics, such as time saved in coding, reduction in bugs, or improvements in customer satisfaction, is vital.
                    • We believe that organization-specific KPIs and qualitative metrics around things like DevEx (Developer Experience), creativity, innovation and flow are vital to consider, as the power of the generative era lies far more in the impact these intangibles have on the potential of business models, products and platforms than on the cost savings many leaders erroneously focus on. This is absolutely an inflection point, in which the value of the abundance mindset applies.

                    In conclusion

                    Generative AI is already well underway in demonstrating its potential to transform the software engineering lifecycle, improve quality, creativity, innovation and the impact of software products and platforms – as well as streamline essential processes like testing, quality assurance, support and maintenance. We expect its use to grow rapidly in the coming years, with continued growth in both investment and business impact.

                    Organizations that succeed in adopting generative AI as a transformative force in their software engineering ethos will be those that fully integrate it into their processes rather than treating it as a piecemeal solution. Achieving this requires a bold, cohesive vision, changes in governance, the adoption of new tools, the establishment of meaningful metrics, and, most importantly, robust support for teams across the software development lifecycle. 

                    At 乌鸦传媒 Engineering Software, we are ambitiously transforming our own world of capability, vision, approach, tools, skills, practices and culture in the way we view and build software products and platforms.  We鈥檙e here for you, to help you and your teams strike out on your journey of transformation in the generative software engineering era.

                    Download our 乌鸦传媒 Research Institute report: Turbocharging software with Gen AI to learn more.


                    Gen AI in software

                    Report from the 乌鸦传媒 Research Institute

                    Meet the author

                    Keith Glendon

                    Senior Director, Generative AI and Software Product Innovation
                    Keith is an experienced technologist, entrepreneur, and strategist, with a proven track record of driving and supporting innovation and software-led transformation in various industries over the past 25+ years. He鈥檚 demonstrated results in multinational enterprises, as well as high-tech startups, through creative disruption and expert application of the entrepreneurial mindset.

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