In a world where agility defines competitiveness, the traditional monolithic ERP is no longer enough. Enterprises are embracing an AI-first two-tier ERP strategy a transformative approach that blends centralized governance with localized innovation.

At the heart of this evolution is the AI-first two-tier enterprise core, co-developed by ÎÚÑ»´«Ã½ and Microsoft. This model empowers organizations to deploy a stable ERP at the corporate level while enabling business units to operate with tailored, agile systems. The result? Faster time-to-value, reduced complexity, and scalable innovation.

AI-driven ERP systems introduce autonomous agents and digital workers that automate routine tasks, orchestrate business processes, and deliver real-time insights across finance, supply chain, HR, and beyond. These systems are not just intelligent they are adaptive, touchless, and future-ready.

Whether navigating mergers, entering new markets, or consolidating legacy systems, this AI-first approach ensures cost efficiency, regulatory compliance, and customer-centric agility. It’s not just ERP reimagined it’s the enterprise core redefined.

Ready to unlock the future of enterprise transformation?

Download our full Point of View on The Future of AI-Driven ERP to discover how AI-first two-tier ERP strategies are reshaping agility, automation, and innovation across industries.

The transformative impact of gen AI and agentic AI in the automotive industry

Customer service in automotive is becoming much more than a support function. Soon, it will be a driver of loyalty, insight, and brand perception, according to automotive executives who participated in a recent multi-industry study by the ÎÚÑ»´«Ã½ Research Institute.

So how can automotive companies ensure they are ready to make the most of this transformation, and use AI in customer service for competitive advantage?

Our new infographic brings to life automotive industry findings and recommendations from the CRI study. It explores:

• Challenges with current customer service functions inefficiency, agent job satisfaction and retention, and failure to meet rising customer expectations.
• Expected benefits of gen AI and agentic AI, such as improved agent productivity, reduced costs, and more personalized and satisfying customer interactions.
• Steps that companies must take to close gaps in their current AI capabilities: adjusting the customer service model, deploying the right technology architecture, and setting continuous improvement in motion.

Download the infographic for practical steps that will streamline your journey to AI-powered customer service. And then read the CRI report for more detailed recommendations, and to see how automotive compares with other industries.

AI agents are no longer just a concept – they are becoming a core part of enterprise operations, reshaping business models, workforce dynamics, and competitive advantage.

Rise of agentic AI: How trust is the key to human-AI collaboration, a new report from the ÎÚÑ»´«Ã½ Research Institute, explores the emergence of AI agents as a transformative force in business. Drawing on insights from a survey of 1,500 senior executives across 14 countries, the report examines adoption trends, economic impact, trust dynamics, and the organizational shifts required to scale agentic AI effectively.

Key findings from the report include:

• A $450 billion opportunity: By 2028, AI agents could generate up to $450 billion in economic value through revenue growth and cost savings across surveyed markets.
• Adoption is accelerating – but maturity remains low: 2% of organizations have deployed AI agents at scale, 12% at partial scale, while 23% have launched pilots and 61% are exploring deployment. 15% of business processes are expected to reach semi- or full autonomy in the next 12 months. However, fewer than one in five organizations report high maturity with respect to data and technology infrastructure needed to implement agentic AI.
• Trust in fully autonomous AI agents is declining, dropping from 43% to 27% in one year. Ethical concerns, lack of transparency, and limited understanding of agentic capabilities are key barriers.
• Human-AI collaboration is the future: By 2028, 38% of organizations will have AI agents as team members within human teams. Blended teams – where humans and AI agents collaborate – will become the norm, driving productivity and innovation.

The report is a key resource for senior executives in data and AI, strategy, innovation, finance, IT, and risk and compliance functions, providing a roadmap for understanding the opportunities, risks, and organizational shifts required to scale agentic AI successfully. To unlock the full potential of AI agents, organizations must:

• Redesign processes and reimagine business models for agentic AI
• Transform workforce structures to support human-agent collaboration
• Balance autonomy with human oversight to build trust
• Strengthen data and technology foundations for scalability
• Align agent behavior with business goals, and ensure explainability
• Develop and integrate ethical AI to mitigate risks and build confidence.

As AI agents evolve from tools to teammates, organizations have an opportunity to lead the next wave of enterprise transformation. To explore how, download the Rise of agentic AI report today.

Harnessing AI for cyber resilience

Corence Klop, Chief Information Security Officer, Rabobank

Corence Klop holds almost 20 years of experience within Rabobank with leading roles in the areas of digital transformation, innovation and data & analytics. In her current role, as Chief Information Security Officer, Corence is responsible for setting the information security vision, strategy and priorities, develop and maintain the information security standards and frameworks, and representing Rabobank in matters of resilience within The Netherlands.

She also works as a non-executive board member of the Rabobank Pension fund and member of the supervisory board of a library.

Can you walk us through your journey at Rabobank and your current responsibilities as CISO?

I stepped into the role of CISO at Rabobank in September 2023. In this position, I hold global and group-level responsibility  for the security of the bank. This includes our central operations, as well as regional branches and subsidiaries. It’s a role that comes with immense accountability. If something goes wrong, the buck stops with me. But it also gives me the freedom to shape the bank’s strategic agenda for change.

Prior to this, I spent three years in the bank’s data and analytics division. I led, for example, a community of 600–700 professionals focused on data and analytics – a key area of expertise within the organization. My interest lies in analytics  and uncovering ways to extract value through actionable insights.

I have a background in innovation management, which fuels my passion for emerging technologies. I’m constantly on the lookout for new tools and techniques that can help us stay ahead, particularly in security and operational resilience.

Do you find there is friction between creating value with data and protecting it?

There is friction, but I think it partly comes from my personality. I’m opportunistic, always thinking about what can be done with data or certain technologies. At the same time, working in security means a strong focus on protecting privacy and assets and ringfencing sensitive data. Both aspects are important. Security isn’t just about preventing risk – it’s also about creating the greatest value for your organization and our customers.

Security isn’t just about preventing risk – it’s also about creating the greatest value for your organization and our customers.

The surge in cyberattacks

Since assuming leadership, have you noticed a rise in the number and nature of cyberattacks?

The increase has been exponential. In the first half of 2025 there has been a major increase in distributed denial of service (DDoS) attacks. March 2025 saw more denial requests entire 2024. Financial Services is the most frequently attacked industry (34% of all global attacks). In Q1 2025, we have seen more than 250k phishing attacks against Rabobank. That’s a staggering number and testament to how aggressive the threat landscape has become.

The attack maturity is also increasing, which has massive operational implications. We are talking about phishing, QR code scams, man-in-the-middle attacks and, increasingly, deepfake-based threats. What’s more concerning is that this trend is not plateauing. Rather, it’s escalating.

That’s why technologies such as AI are not just a strategic advantage, they’re a necessity. With threats increasing both in volume and sophistication, we need smarter, more scalable solutions to prevent and respond and to stay resilient.

In Q1 2025, we have seen more than 250k phishing attacks against Rabobank.

What do you see as the primary drivers of this surge in cyber threats?

A major factor is the volatile geopolitical environment. These dynamics have real consequences on the cyber landscape.

Nation-state actors and politically motivated threat groups are becoming more active. And even beyond state-driven actions, the general level of criminal sophistication has risen. Bad actors are evolving fast. They’re using AI themselves now. It’s no longer just lone hackers or small-time phishing scammers; there’s a whole ecosystem behind this.

Could you expand on the evolution of phishing and how attackers are adapting their methods?

Phishing remains one of the most persistent and effective forms of attack, but it’s evolving. It’s no longer just about fake emails with suspicious links. Phishing kits have added AI integration to simplify the process to build multi-language tailored phishing pages delivering much more sophisticated results.

Perhaps more alarmingly, deepfakes are entering the equation. Imagine receiving a video call or voicemail from someone who looks and sounds exactly like your boss, asking you to approve a financial transaction urgently.  Deepfake continues to be on the rise. Threat actors increasingly offer deepfake services claiming to be able to circumvent Know-Your-Customer protocols.

This evolution of threats makes it clear that conventional security measures are no longer sufficient. Attackers are using emerging technologies, and we need to keep up.

Deepfakes are entering the equation. Imagine receiving a video call or voicemail from someone who looks and sounds exactly like your boss, asking you to approve a financial transaction urgently.

Keeping up with the threat environment:

With such advanced threats, how is Rabobank preparing for the future?

Security is a core capability. We have an information security strategy with a solid foundation to defend against most future threats.

The sheer volume of attacks means we need systems that can prioritize, detect, and respond, often autonomously. This is where AI and automation come in. For example, automating the triage of security alerts can save thousands of hours of analyst time and ensure critical incidents are caught early.

Beyond that, the people and process part of our strategy are very important. All employees have a role to play and should have a minimum level of security maturity so they know how to behave in a secure way. Security is not the job of one department. It’s embedded in our IT, operations, and customer-facing units. Everyone has a role to play.  

We are not alone in this. We actively join forces with other major organizations in the Netherlands by sharing our experiences and knowledge, to stay prepared for future challenges.

Automating the triage of security alerts can save thousands of hours of analyst time and ensure critical incidents are caught early.

How do you align that long-term security view with agile ways of working?

As mentioned in our security strategy, we’ve defined a Foundation, which includes all essential security measures. But beyond that, we also prepare for emerging technologies such as AI and quantum computing.

Our strategy is translated into yearly priorities. Of course, we cover the basics that every organization needs, but we also explore how to prepare for developments that may arise in two or three years. I try to strike a balance in ensuring we have the technology we need today, while building for the future.

A good example is post-quantum cryptography. It might not be an imminent risk, but we know it’s coming. I push for topics like that to be included in our priorities. That means starting with an inventory of what we currently have, building internal expertise, and embedding these topics in the organization’s agenda.

Post-quantum cryptography. It might not be an imminent risk, but we know it’s coming.

AI and cybersecurity:

In your view, where does AI – and specifically generative AI (Gen AI) – hold the most immediate potential in cybersecurity operations?

In the short term, I believe the greatest potential for AI and Gen AI, lies within the security operations center (SOC). The SOC deals with a massive volume of alerts daily, and that’s precisely where Gen AI can be a game-changer.

One key use case is assisting analysts during the alert investigation process. Gen AI can streamline their workflows by quickly searching across multiple databases and offering recommendations for action. It essentially acts as an advisor, advising whether to escalate an alert, ignore it, or take specific action.

What approach are you taking to improve detection and response?

Since we didn’t find a reliable off-the-shelf solution, we’ve started building our own ML model specifically trained on our own data.

The advantage here is twofold. First, we control the dataset, which means we can fine-tune the model to our environment and threat landscape. Second, it allows us to embed domain knowledge directly into the model, which generic solutions struggle to do.

It’s still early days, but the results are promising. We can work better with high volume data sources and can better detect.

What are some of the challenges you’ve faced in building AI models for in-house cybersecurity?

One of the first challenges we encountered was the expertise gap. In cybersecurity, we traditionally don’t have data scientists embedded in our teams. Conversely, the data science teams at our bank, while very skilled – especially in areas such as fraud detection – aren’t familiar with the specifics of security data. This divide made collaboration difficult and our security team had to start learning the principles of AI.

Another major issue was tooling. Many of the standard tools we use in security, like Microsoft Defender, aren’t designed to handle large datasets or ML. You can’t just run Python or complex queries on these platforms. So, we needed an updated infrastructure to run and train models efficiently, which could handle the scale of data we were working with.

As you’re building AI models internally, how do you handle ethical concerns like explainability, transparency, and bias?

Our analytics teams follow a structured AI Way of Working (WoW)that guides them through every step of model development. The AI WoW ensures AI risk minimization and AI value maximization including ethical considerations. It emphasizes explainability, transparency, and documenting decisions. You can find out why a particular modeling choice was made, even years later.

At Rabobank, we make a Responsible AI building block available for teams. This is designed to be compliant and in control by translating AI related standards, guidelines and frameworks into technical components to embed in all use cases.

What advice would you give an organization just starting its AI cybersecurity journey?

My first piece of advice is to get your data in order. Before you build or even adopt an AI model, you need a clean, consolidated source. Our early modeling efforts were hampered by inconsistent and incomplete datasets.

Secondly, I recommend starting with what’s already available. Don’t try to build everything from scratch. Run experiments with available tools, understand their capabilities and limitations, and build internal expertise along the way.

Building a cyber-aware organization:

How do you balance AI tools with skill development in your team?

First of all, there is a strong focus on building AI skills, not only in the security organization but in the whole organization. DataWise is a global learning program for all employees. Rapid innovations in data and AI impact our work. Data and AI help us provide excellent customer service, improve efficiency and performance, and make the right decisions. This requires continuous skill development. DataWise supports employees in this development.

Also I’ve experienced that security analysts are fast in learning how to design, build and deploy detection rules and models in a short timeframe.

Finally, it’s about focus. AI tools will not replace a security analyst. It will augment their work. This also means you should be careful how to build up AI. The model should be validated since it should do what it’s supposed to do.

AI tools will not replace a security analyst. It will augment their work.

A big part of cybersecurity success depends on end-user behavior. How do you manage awareness without creating fatigue?

I focus on integrating attention-worthy topics into the daily routines of my users – or, in my case, colleagues – without making it feel like a burden. It’s about using small, everyday moments to raise awareness.

Phishing is a great example. We regularly send simulated phishing emails and monitor responses. Instead of following up with long training sessions, we provide micro learnings of one to two minutes to highlight what they could have checked, what they might have done differently, and offer additional resources to those who are interested. It’s all about keeping it simple and accessible, and finding creative approaches to keep them engaged.

Which trends do you see shaping the future of AI in cybersecurity?

One major factor will be talent. Finding people with the right blend of AI and cybersecurity expertise is only going to get tougher. These technologies will need to help teams do more with less.

Education is the foundation. You can have the best tools, but if your people fall for a deep-fake video or phishing attempt, those tools might never come into play. We stress critical thinking, skepticism, and adherence to process. My team works hard to keep everyone aware, not just of existing threats, but also of how they’re evolving.

From a technical perspective I see a few developments: 1) Identity fraud – onboarding fake customers, 2) Attacks will be harder to detect, faster and more convincing, and 3) More and better personalization in scams.

Finding people with the right blend of AI and cybersecurity expertise is only going to get tougher.

Quantum computing is advancing rapidly – and with it, the risk to today’s cryptographic systems.

As “harvest-now, decrypt-later� threats increase, quantum safety has shifted from a technical concern to a C-suite priority. Regulatory pressure, evolving technology ecosystem, and competitive advantage all favor early movers.

Future encrypted: Why post-quantum cryptography tops the new cybersecurity agenda, the latest report from the ÎÚÑ»´«Ã½ Research Institute, explores how organizations can prepare for a quantum-safe future, leveraging post-quantum cryptography (PQC) with crypto-agile architectures to protect critical assets and maintain trust.

The report’s insights are based on a global survey of 1,000 organizations with at least $1 billion in annual revenues, operating across 13 sectors and 13 countries in Asia–Pacific, Europe, and North America and in-depth interviews with 16 industry executives. Key findings include:

• Quantum safety is rising on the executive agenda: 70% of surveyed organizations (referred to as “early adopters”) are assessing or deploying quantum-safe measures. Yet only 15% of early adopters qualify as “quantum-safe champions,â€� with mature governance and technical execution.
• The threat is real – but still underestimated: 30% of surveyed organizations continue to downplay the urgency of quantum threats, risking future data exposure and regulatory penalties.
• PQC is the preferred defense strategy: Most organizations recognize PQC as the most viable path to quantum safety. However, skills gaps, budget constraints, and tool limitations are slowing progress.
• Pilots are underway, but complete transition remains a challenge: Around half of early adopters are running PQC pilots, often in partnership with cloud providers and specialist vendors. Yet few have a clear roadmap for enterprise-wide transition.
• Quantum-safe champions offer a blueprint: These leaders combine cryptographic inventory management, supply chain engagement, and hardware readiness to accelerate their transition.

The report is essential for CISOs, CIOs, CTOs, and heads of information security responsible for safeguarding critical infrastructure, sensitive data, and long-term digital trust. It provides a comprehensive view of the quantum threat landscape, offers a roadmap to assess quantum readiness, and actionable strategies for building quantum-safe organizations, including:

• Conducting quantum risk assessments and maintaining a live cryptographic inventory
• Driving enterprise-wide education and establishing a governance structure that keeps quantum security on the C-suite agenda
• Designing for crypto-agility to adapt as standards evolve.

To learn how organizations can protect against tomorrow’s quantum threats, download the report today.

Navigating tariffs and transforming MedTech for the digital future

In early 2025, the United States introduced sweeping tariffs that have shaken global industries—MedTech included. For a sector dependent on global supply chains and hardware-centric models, the impact has been immediate and severe both for U.S. companies and the global organizations that do business with them.

To navigate this storm, companies need to think not just tactically, but strategically.

In this new POV, Tariffs as a turning point ÎÚÑ»´«Ã½â€™s life sciences teams guide clients through these periods of turbulence by helping them transition to digital solutions that offer higher margins, reduced risks, and quicker responsiveness.

Being digital-first can make the difference in finding a route.

Navigating tech, geopolitics, and the big trends

Olaf Groth is Founder and CEO at Cambrian Futures.

Olaf Groth is an author, futurist, and strategist. His focus is the area where cyber, geopolitics, and geopolitics intersect and his primary interest is the AI-, data-, and compute-driven transformations of economies, industries, and organizations. Olaf is the founding CEO of advisory think tank Cambrian Futures and of concept development firm Cambrian Labs. He serves as professional faculty for strategy, policy, technology and futures at UC Berkeley’s Haas School of Business; Adjunct Professor of Practice at Hult Business School; and Honorary Adjunct Professor at Universiti Teknologi Malaysia. He has taught at institutions across the US, Europe, Middle East, Africa, and Asia.

The big trends

What are the biggest technological shifts happening currently?

One of the most significant shifts is toward human-like intelligence, achieved through a cluster of technologies. Large language models (LLMs) are just one piece of this puzzle. Others are emerging constantly.

Another major shift is around data, not just as a commodity, but as the fuel for everything. We’re heading into an era of data wars, as actors compete for the right data for specific compute interventions. There will be a push to sign global data accords aimed at channeling this data towards societal and economic growth.

We’re also seeing a sustained trend in sovereign compute. Expect nationalized or regionalized compute centers in the EU, the Gulf States, North America, and China.  This development is foundational to how nations will control and protect their digital infrastructure and computational power.

Crypto and the technologies that underlie it – blockchain and Web3 – are often dismissed as dead, but they have laid the foundation for a more balanced Internet economy, countering the centralization of Web2, which is dominated by a few global platforms. While Web3 may not replace Web2 entirely, it will gain traction in specific use cases that require decentralized ownership and governance. Crypto will also continue to thrive as a parallel financial system, with investors and innovators competing for power. Notably, the EU leads in regulation and adoption, while the US lags on regulation but leads in innovation.

In genomics, CRISPR is driving transformative change. The US leads here as well, propelled by both scientific innovation and pandemic-related demand. AI and data science will be indispensable in harnessing CRISPR effectively, and vice versa, pandemics provide the necessary biological data to fuel further scientific breakthroughs.

Brain-computer interfaces (BCIs) bridge the frontier between the biological and digital. With around 500 organizations in the space – ~330 in the US and China, and ~100 in Europe – this is a rapidly growing field. Applications range from treating blindness and paraplegia to enhancing memory, education and training, and potentially even augmenting our understanding of happiness. However, these benefits come with substantial risks that must be carefully managed.

Quantum computing is another game-changer. Microsoft’s Majorana One chip may represent a breakthrough. While its broad applications are still being determined, the near-term value lies in areas including chemistry and life sciences – domains where datasets are manageable but existing compute solutions fall short. Europe could play a leadership role here, drawing on its established chemicals and biopharma sectors.

Space tech is blossoming too, led by entrepreneurs such as Elon Musk, Jeff Bezos, and Richard Branson, as well as rising governmental ambition in China and India. We’re witnessing the emergence of a semi-privatized innovation ecosystem, especially in Silicon Valley. This also extends into air and ocean tech, all dealing with hostile environments and, therefore, requiring rugged technologies. Over the next 10–15 years, these may evolve into entirely new industries – an area where Europe can also assert leadership.

Lastly, defense tech is undergoing a renaissance, especially in Europe. While the US has always maintained a strong defense tech base, geopolitical tensions and real-world conflicts, such as that between Russia and Ukraine, are pushing innovation even harder. Even Silicon Valley, once resistant to this, as evidenced by the recent Google protests,[1] is now embracing this shift. Europe must commit a significant portion of defense spending to innovation, especially as defense overlaps with space and other tech domains.

“Expect nationalized or regionalized compute centers in the EU, the Gulf States, North America, and China”

What are the most underestimated forces shaping technology, politics, and society?

The single biggest underestimated force is the deficit of trust. There’s widespread distrust of governments, media and, to a lesser extent, businesses. According to the Edelman Trust Index, governments rank lowest in public trust across many countries. To paraphrase Deng Xiaoping, governments are no longer “hunting mice” – that is, they are failing to fulfill their basic role of enabling prosperity and stability.

This lack of trust is also why crypto is blossoming. At its core, crypto represents a trust revolution, not just a financial one. It’s built on blockchain, which diffuses power by replacing centralized platforms with decentralized protocols. How can we create new mechanisms for trust within and across communities? In countries such as the US, where tribalization is especially pronounced, rebuilding trust is more urgent than ever.

Meanwhile, geopolitics will continue to define the next two decades. It’s not a new force, but it’s acquired a new target: technology. Innovation is increasingly being shaped by geopolitics, whether it’s AI sovereignty, data sovereignty, or compute sovereignty. In the past, geopolitical concerns were limited to narrow tech such as nuclear arms. Today, military-civilian fusion means technologies like social media can be weaponized.

Finally, the fusion of technology and energy is a critical, often overlooked force. Cognitive technologies such as AI require vast computational resources, which, in turn, demand more energy. We may move from dedicating 1–2% of our energy budget to tech, to 20% or more. This will likely trigger a nuclear renaissance, possibly involving small modular reactors (SMRs) or even breakthroughs in fission energy, if we can commercialize them safely.

“Innovation is increasingly being shaped by geopolitics, whether it’s AI sovereignty, data sovereignty, or compute sovereignty“

Understanding the “six Cs� and techno-Confucianism

You’ve written about the tectonic shifts in our world and defined what you call the “six Cs.â€� Could you expand on these?

Absolutely. The six Cs frame the major global shifts we’re experiencing. First is climate change – ­­­­­an existential but also an economic threat. We’re looking at infrastructure impacts of over $7 trillion, with another trillion or two in lost economic activity. While some of that might transform into innovation and new industries, the negatives will outpace the positives over the next decade.

Climate change will also drive migration. Potentially 500 million to 1.2 billion people moving, mainly from the Global South to the North. That will bring significant political disruption as countries struggle to manage livelihoods, healthcare, and social systems under strain.

Second, there’s the China-US reset. Both countries are socially and politically volatile, but for different reasons. China’s dealing with what I call the “great wobble.” Xi Jinping is restructuring the national economy, shifting from digital services for consumers to enterprise services and more automated manufacturing. But this happens amid a looming demographic crisis. China’s population is projected to shrink from 1.4 billion to 800 million by the end of the century. That’s fewer mouths to feed, but also fewer workers to support an aging population.

China is also addressing fallout from the pandemic: economic hardship; limited digital infrastructure; a lower birth rate due to lack of privacy in multi-generational homes; and a burst real-estate bubble. Add to that energy security concerns and deeper ties with Saudi Arabia, plus geopolitical issues such as Taiwan, plus backlash to the Belt and Road Initiative, and you have a complex and delicate situation.

Meanwhile, the US is facing what I call the “Trump tornado.” It includes draining government agencies, limiting immigration, and increasing tariffs, while trying to reduce taxes. Immigration is especially tricky. One-quarter of US entrepreneurs are foreign-born, and much of the service industry relies on immigrant labor. There’s also a push toward advanced manufacturing and AI integration, but we lack the educational infrastructure to retrain tens of millions of workers. Both China and the US are in industrial transition while being locked in a competitive rivalry.