Embedding AI for Success: Why People Power Drives Technology Transformation

TL;DR: AI is not a silver bullet—it’s a powerful enabler. But without people at the heart of the transformation journey, organisations risk stagnation. As CIOs, we must champion a human-centric approach, embedding AI strategically while empowering teams to lead change.

I was recently invited to share my perspectives at a CIO forum on the effective integration of AI within organisations. Here are my thoughts on how AI should be incorporated. While there are often discussions about disappointments with AI, I believe it is clear that AI should not be treated as an add-on but rather integrated to unlock its full potential.

Artificial Intelligence (AI) is no longer a fringe innovation or distant promise—it is woven into the operational DNA of leading organisations. From predictive analytics and intelligent automation to conversational AI and decision-support systems, AI has rapidly evolved from experimentation to enterprise-grade execution. And yet, even the most sophisticated AI will fail to deliver meaningful transformation if organisations overlook their most critical asset: people.

As a Global CIO, I’ve seen firsthand that embedding AI for success is less about algorithms and more about alignment—of vision, capability, and culture. This article explores why people power is the ultimate driver of technology transformation and how CIOs can create the right environment for AI to thrive.

1. AI is a Tool, Not the Transformation

Let’s debunk a common misconception: AI isn’t the transformation—it enables transformation. Technology is only one part of the equation. True, AI can optimise workflows, personalise customer experiences, and surface insights at scale. But without a clear business strategy and empowered teams to apply and scale it, AI risks becoming an isolated initiative rather than a catalyst for change.

In my work across global enterprises, the most successful AI transformations were those where technology was embedded into cross-functional teams, processes, and decision-making structures—not bolted on. We must move beyond AI labs and pilots into full integration—led by people who understand both the tech and the business context.

2. Culture Eats AI Strategy for Breakfast

Organisational culture is the foundation in which AI must grow. No matter how advanced your models or infrastructure, without a culture that embraces curiosity, learning, and change, AI initiatives will flounder.

At the heart of this is trust. Teams must trust the data, trust the AI outputs, and trust each other. Transparency in AI models, explainability, and ethical considerations are not just compliance checkboxes—they are trust builders.

As CIOs, we must lead by example: communicate clearly about what AI can (and can’t) do, involve employees early in transformation programmes, and celebrate small wins that build momentum. AI adoption is not just a technical rollout—it’s a cultural evolution.

3. Digital Skills Are the New Currency

For AI to be embedded successfully, digital fluency must extend beyond IT. Yes, we need data scientists, machine learning engineers, and cloud architects. But we also need business leaders, product managers, marketers, and operations teams who understand how to work with AI, interpret outputs, and act on insights.

This is where upskilling becomes critical. It’s not just about training for tech roles—it’s about democratising AI literacy across the organisation. In several global programmes I’ve led, we implemented “AI Champions” networks—embedding experts in business units to support change and act as conduits between tech and teams.

AI fluency must be treated as a core competency—on par with financial or operational literacy. Without it, organisations will struggle to move beyond surface-level AI adoption.

4. From Pilot to Scale: Empowering Teams to Lead

Many organisations are stuck in AI pilot purgatory—an endless cycle of proof-of-concepts with no clear path to scale. Why? Because pilots are often designed and run in isolation from the business. Embedding AI means breaking down these silos and empowering cross-functional teams to take ownership.

In practice, this means embedding AI capabilities directly into delivery teams, co-creating solutions with users, and giving teams the autonomy to iterate and improve. One of our key successes came from decentralising AI—allowing teams closest to the problem to drive experimentation while ensuring central governance and ethical oversight.

This hybrid model—central guidance with decentralised execution—is a powerful enabler of scalable, sustainable AI transformation.

5. The CIO’s Role in Human-Centred AI Transformation

As CIOs, we are uniquely positioned to bridge the gap between business ambition and technological capability. But to do so effectively, we must embrace a people-first mindset. Our role is not just to deploy AI platforms—it’s to create the conditions in which AI can be applied meaningfully by our people.

This means aligning AI with business value, building trust through transparency, investing in digital skills, and embedding AI into the way teams work—not just the tools they use.

We must also be the ethical stewards of AI, ensuring responsible design, fair data usage, and governance that respects human rights. As the influence of AI grows, so does our duty to lead with integrity.

In Closing: Technology is the Enabler—People Are the Change

AI is a game-changer—but only when coupled with human ingenuity, collaboration, and purpose. The real transformation happens when people use AI to solve problems, innovate faster, and make better decisions. It’s not about replacing people—it’s about augmenting them.

As we embed AI deeper into our enterprises, let’s remember: people power drives technology transformation. And as CIOs, our legacy will be defined not just by the tools we implement, but by the human potential we unlock.

Richard Keenlyside is a Global CIO for the LoneStar Group and a previous IT Director for J Sainsbury’s PLC.