In a world where GenAI is no longer a novelty but a strategic imperative, the role of the CIO is undergoing its most significant transformation in decades. AI&Us, the web series from Dataiku, is back for its third season — Guardians of AI Innovation — and dives headfirst into this new reality, offering an unfiltered look at how top CIOs are not just keeping up with AI advances but using them to reinvent their businesses.
Alongside the web series — which features technology leaders from AXA UK, Catella, FLOA, the City of Los Angeles, Perdue Farms, and BCLC — we have partnered with The National CIO Review on a must-read paper for CIOs, “The Uncomfortable Truth About GenAI: Making Bad CIOs Worse and Great CIOs Even Better.” Together, these insights offer a roadmap for IT leaders ready to lead, not lag, in the GenAI era.
The GenAI Leadership Divide Is Real — and Growing
As The National CIO Review paper makes clear, GenAI isn’t just another tool in the CIO’s kit — it’s a leadership test. The gap between CIOs who harness AI to drive innovation and those who struggle to scale it is widening rapidly. By 2028, AI is expected to autonomously handle 15% of daily work decisions, signaling the rise of agentic AI — systems capable of executing tasks, initiating processes, and making decisions independently.
CIOs who fail to prepare for this shift will face fragmented initiatives, overwhelmed teams, and governance nightmares. Those who succeed will do so by mastering five critical areas:
1. Aligning AI with business objectives: Ensuring AI initiatives support key strategic priorities, optimizing processes, and unlocking new revenue opportunities.
2. Establishing scalable AI infrastructure: Building a tech ecosystem that enables seamless AI adoption across teams and functions.
3. Driving cross-functional AI adoption: Partnering with business leaders to integrate AI into operations, ensuring company-wide adoption rather than isolated experiments.
4. Building an AI-ready workforce: Equipping teams with the skills and understanding needed to effectively work alongside AI.
5. Ensuring robust AI governance and risk management: Balancing innovation with compliance, ensuring responsible AI development.
6. Measuring AI’s business impact: Defining clear success metrics and tracking AI’s impact on revenue, efficiency, and decision-making.
Check out a teaser of one of the Season 3 episodes:
Real CIOs. Real Challenges. Real Solutions.
The latest season of AI&Us brings these leadership themes to life through candid conversations with:
- Natasha Davydova, CIO at AXA UK
- Stephane Doublait, CIO at FLOA
- Sébastien Robert, Chief Transformation Officer at FLOA
- Martin Johanson, CIO at Catella
- Ted Ross, CIO of the City of Los Angeles
- Mark Booth, SVP & CIO at Perdue Farms
- Mark Goldberg, CIO at BCLC
- And more to come!
These aren’t theoretical discussions — they’re real-world accounts of navigating the complex, high-pressure realities of GenAI and agentic AI adoption.
Sebastian Robert, Chief Transformation Officer at FLOA, stresses the need for broad-based AI literacy:
GenAI is a tool that is going to be accessible and usable for everybody in the company, and we have to make sure that everyone will be able to use it with the right skills and the right mindset.
Meanwhile, Natasha Davydova, CIO at AXA UK, reminds us that technology is only part of the equation:
Don’t forget the human side of things, technology is just the enabler.
These leaders offer more than soundbites — they provide a vision for how CIOs can turn GenAI from a daunting challenge into a transformative opportunity. Also, if you missed it, check out the session featuring Perdue Farms and FLOA at Everyday AI New York (jump to 1:20:18), where Sébastien, Stephane, and Mark Booth discussed their journeys, strategies, and roles in today’s fast-changing landscape and, notably, how their teams are thinking about the next frontier: agentic AI.
From Hype to Impact: Making GenAI Count
Both the videos and paper from The National CIO Review hammer home a central point: AI initiatives must deliver measurable business value. It’s not enough to experiment with chatbots or deploy isolated predictive models. Success demands embedding AI into enterprise workflows, aligning it with corporate objectives, and continuously measuring its impact on revenue, efficiency, and decision-making.
Yet, the road to impact is fraught with pitfalls:
- Fragmentation: Without scalable platforms and interoperable tools, AI projects can become siloed, creating governance headaches.
- Lack of alignment: Technology for technology’s sake leads to wasted resources and poor ROI.
- Workforce readiness: Even the best AI tools are useless without a workforce equipped to leverage them.
Great CIOs tackle these challenges head-on by selecting scalable AI platforms, leveraging low- and no-code tools to empower business users, and building a robust data foundation to ensure AI models operate on accurate, business-critical data.
Governance: The Differentiator Between Leaders and Laggards
Governance isn’t a buzzword — it’s the linchpin of successful AI adoption. As AI systems grow more autonomous, CIOs must implement governance frameworks that provide control and transparency without stifling innovation.
The National CIO Review paper recommends a hub-and-spoke model that balances centralized oversight with decentralized AI development:
- The hub — led by IT, data, and governance teams — establishes security, compliance, and transparency standards.
- The spokes — business units and operational teams — develop AI solutions within these guardrails.
This structure ensures that AI initiatives remain aligned with business goals while mitigating risks related to security, compliance, and bias.
As Ted Ross, CIO of the City of Los Angeles, puts it:
The rise of GenAI is making tremendous changes in the role of the CIO. Probably the biggest is we now have to really focus on digital ethics and be able to help manage not just innovation in an organization but all the unintended effects of it.
The Uncomfortable Truth: Good Isn't Good Enough
Perhaps the most striking insight from the paper is that the age of the “good” CIO is over.
Good CIOs adopt AI and support experimentation. Great CIOs embed AI into the very fabric of their businesses, transforming governance into a competitive advantage and aligning AI strategy with board-level expectations. Those who hesitate — waiting for perfect data, clearer guidelines, or AI to “prove itself” — will not just struggle. They will be left behind.
The uncomfortable truth? GenAI and agentic AI will either expose leadership gaps or propel visionary CIOs to new heights. Which side of the divide will you be on?