Exclusive Contribution for The Executive Magazine by Will Lowe, Chief Data & AI Officer at Transform
“Are you an AI expert?” My honest answer is, ‘I’m trying.’
Not long ago, a new letter appeared in my job title. I went from being a Chief Data & Analytics Officer to a Chief Data & AI Officer. It’s a subtle change on paper that signifies a seismic shift in my daily reality. In my role at a transformation consultancy, I have a dual mandate: steer our clients through the AI whirlwind and simultaneously re-equip our own organisation for this new era. It gives me a panoramic view of the excitement, the anxiety, and the sheer velocity of the AI revolution as it unfolds across the private and public sectors.
The unprecedented pace of change
To say the pace is relentless would be an understatement. We’re in a period of unprecedented acceleration. Hyperscalers are doubling their annual AI investments to over $300 billion USD, and major product releases are now dropped on a weekly basis, no longer waiting for grand annual conferences. We see reports of OpenAI adding a billion dollars in recurring revenue each month and tech titans offering nine-figure salaries to secure top talent.
This creates a pressure on business leaders everywhere. The expectation is that AI will deliver transformative efficiencies and unlock growth, and the board wants to see it yesterday. In this environment, the hardest, and most valuable, thing to do is to find time for reflection. You have to carve out space to separate the genuine breakthroughs from the breathless hype. Then, just as your healthy cynicism takes hold, you use a new tool and are floored by its capability, and the cycle of awe and analysis begins again.
People, policy, and technology
AI isn’t new to us at Transform, but this new era has forced us to formally agree on what sort of company we want to be in an AI-driven world. We’ve established our ambition: AI should amplify who we are, not take over. We’ve updated our AI Policy and started asking clients for theirs (it’s amazing how many don’t have one). We have experimented with, and are now investing in, different enterprise-level tools for different roles, from research to coding. We’ve also built our own agentic tools for our own use cases, focussed on improving our efficiency and effectiveness.
This has led to the creation of new roles. We now have our first Agent Managers, complete with new job descriptions and guardrails for their AI Agent reports. We are supporting our people through this transition, facing into the mix of excitement and discomfort that such change brings. In this respect, AI transformation is like previous transformations around data and digital. It’s 30% about technology and data, and 70% about people and culture.
This, at least, is helpfully familiar. Right now, the signs are that AI is going to augment, rather than replace people, which could disappoint a lot of CEOs, CFOs, and Government Departments.
The governance gap
Every month seems to bring new guidelines and policies from governments and authorities around the world. They share broad guidance but often stop short of being specific or directive, trying to balance the need to protect citizens with the imperative for AI to drive economic growth and reduce public sector costs.
Meanwhile, development and adoption are accelerating at a staggering pace. At Google I/O in May, CEO Sundar Pichai shared that usage across Google’s services climbed from 9.7 trillion tokens in April 2024 to over 480 trillion tokens by April 2025 – an astonishing fifty-fold increase. The pace of AI adoption is far outstripping the checks and balances, increasing the risk of ethical and legal issues.
But it’s important to remember the benefits being delivered right now. I know several doctors whose extremely difficult work lives have been helped massively by the introduction of copilots. These tools take detailed clinical notes and provide patients with summaries, tasks they struggled to complete alongside their packed surgery timetables. It’s a perfect example of AI enabling valued workers by doing what it’s good at, while maintaining the critical human-in-the-loop, allowing doctors to focus on patient care.
From single tools to specialist AI teams
Despite the challenges, I remain an optimist, and that’s because I’ve seen what this technology can do when applied with purpose and creativity. Our most impressive breakthroughs have come from building multi-agent systems, essentially, creating a specialist team of AIs to tackle a complex problem. We have Moderator agents that push back on poorly formed questions, Orchestrator agents that break down tasks and manage workflow, and Consolidator agents that synthesise the outputs into a coherent whole.
We’ve used this approach to build AI Insight Analysts. Having started my own career in that field, I know the feeling of being buried under an avalanche of questions. Our AI analysts, however, can relentlessly crunch first-party data, enrich it with third-party market context, and keep digging until every possible answer has been surfaced.
This capability is a game-changer for our UK Government clients, who often manage vast libraries of complex, ever-changing documentation. We built a system for one department that can read, understand, and extract precise information from a body of text equivalent to the entire Lord of the Rings trilogy plus half of The Hobbit. For citizens and businesses trying to navigate tax codes, planning permissions, or licensing requirements, this power to get a clear answer instantly is transformative. It’s here you see the real promise: AI that not only cuts costs but genuinely improves public services.
Ultimately, my role feels less about having all the answers and more about asking the right questions. When someone asks if I’m an AI expert, I give them the honest answer: ‘I’m trying.’
About the Author: Will Lowe is Chief Data & AI Officer at Transform, a leading digital transformation consultancy. With extensive experience in data analytics and artificial intelligence, Will guides both clients and his own organisation through the complexities of AI adoption and implementation. He specialises in building multi-agent AI systems and has worked extensively with UK Government departments on AI-driven solutions for public services.