Human Leadership in an AI World: Insider Views from Top CIOs
On the 19th of June 2025, our CIO Search practice had the great pleasure of hosting a night of exquisite dining and engaging conversation at the memorable Masonic Temple at Andaz London. This invite-only dinner brought senior technology executives, digital transformation leaders, and board-level innovators together for an evening of dialogue and insight, hosted by Mayank Prakash CBE, Board Director at Uber UK & Evelyn Partners and NED at Softcat plc.
The evening was packed with lively debate and tech leadership wisdom, consistently circling around to AI and the constantly shifting sands of enterprise IT. Following Chatham House Rules, no individuals or organisations in attendance have been identified, though we thank all in attendance for their input and presence.
So, let’s unpack some of the talking points that inspired us on that balmy June evening in the capital.
Machine Learning Needs a Human Teacher
Machine learning is arguably one of the most well-embedded branches of AI, with numerous established use cases well before the Earth-shaking November 2022 release of ChatGPT. After all, data-led deep learning technology began to thrive as far back as the 90s.
Machine learning applications found themselves particularly at home alongside robotics, automation, and machine vision. This firmly cemented deep learning tech within verticals like manufacturing and logistics, enabling them to streamline functions like quality control, order fulfilment, and exception detection. It was a fairly natural progression over a number of years, going from highly supervised models to less supervision once the tech developed and learned.
However, one topic that kept coming back time and time again during our dinner was the level of sheer hype that is now inseparably infused into anything related to the field of Artificial Intelligence. Though I think you’ll agree, hype never makes good business decisions.
In chasing increasingly independent AI models, some organisations might be wasting money and resources that might be better served by integrating smaller model, high-supervision machine learning tech. Yes, these are now a little “boring,” “unsexy” even, but independent AI adoption (i.e., with weak supervision) overlooks an essential corporate resource: human minds.
Our brains are highly efficient in terms of context and long-term contextual memory - things that aren’t a computational strong suit. Higher supervision offers the opportunity to inject this essential insight into ML models as they are used.
New Tech Adoption Anxiety is Nothing New
Though we are currently riding the wave of the AI hype curve, AI fears are also higher than ever. However, as with many things in tech, we’ve been here before.
You can draw significant parallels between the dawn of cloud computing and where we are today with AI. There were fears that chucking all of your business data into the cloud was inherently insecure and you were at the mercy of your chosen cloud vendor to carry out even basic tasks.
Yet now this stance has matured. Cloud computing is generally favoured for its flexibility, its lower costs, its business continuity prospects, and its compatibility with hybrid working. AI just happens to be the next big, scary thing. But this too shall pass.
Data Governance vs. AI Growth - A Balancing Act
Both data governance and AI-powered growth are essential in businesses nowadays. Yet the two concepts often butt heads.
For example, a business might initially wish to keep its own AI models locked down and on-premises due to data security concerns. Yet what happens when the business needs to grow beyond the capabilities of that on-premises AI solution? Do they risk their data security and sovereignty in moving to a broader, more powerful, cloud-based model? Or do they stick with the smaller model, limited in their ability for innovation?
AI adoption also puts regulators into a tricky spot. AI tools can undoubtedly present a “Pandora’s Box” of data security and sovereignty issues, and regulators need to stick firmly to their codes of conduct for data handling. Yet how do you regulate a technology whose capabilities grow every single day? How do you develop rules for data handling without stifling AI adoption and innovation at the organisations who look to you for guidance?
Technological developments won’t wait idly by while regulators decide how to proceed. The longer organisations go without receiving regulatory guidance, the more they will be burdened with retrofitting a technology that is already the norm elsewhere.
Getting to the Core of New Tech Resistance
In business, resistance to change is nothing new. If you’ve ever managed a team, you’ll know that individuals are often highly uncertain and anxious about change. It’s understandable - change can be uncomfortable and rouse unpleasant emotions.
Yet with technology constantly shifting and improving, organisations are increasingly making iterative, agile improvements to workflows and processes - often enabled by AI. This much more mutable, changeable, “design thinking” approach has the potential to improve the way we all do business for the better.
This incrementally shifting approach is going to change workplace dynamics, especially over time. Organisations are likely to see business functions merging, unlikely departmental alliances forming, and maybe even certain roles becoming a thing of the past. It’s obviously going to change the lives of everyday workers, but it inevitably stands to change things for leaders too.
How will leaders lead when the scope of their department shifts? Many leaders who have put their lives into a career tied to a specific business function won’t want to see their function, their team, and even their power base decimated.
But let’s not beat around the bush: leaders who are open to change; have the flexibility to adapt; and the humility to learn are going to be the ones who flourish in this new, uncharted territory.
A Message for Those Hesitant About AI
Yes, change is scary. Not least the change presented by AI. But uncertainty is the only certainty in life - in business, doubly so!
Artificial intelligence presents a new and uncharted landscape for businesses, but it also presents countless revenue-boosting, competition-gaining opportunities. And in a world where your competitors are likely already adopting AI, it makes business sense to grab the bull by the horns and start cautiously considering use cases for it in your own business.
Competitors who are more open to new tech adoption will wipe the floor with organisations who are set in their ways. The next generation of companies simply won’t be encumbered by the comfortable inertia of “how we’ve always done things.” Organisations fearing this change must learn from the mistakes of Xerox, Netscape, and Blockbuster. Businesses need to adapt and adopt when faced with new technologies and new ways of operating or they'll be left behind!
The Ever-Changing Trials & Tribulations of IT Leadership
As enterprise IT has developed over the years from a mere tool to an outright business enabler, the role of the IT leader has grown and matured to suit. It only seems like yesterday that the IT team was seen purely as the “fix it when it breaks department,” yet now, IT leaders are increasingly being called upon for their strategic guidance.
Yet this new, ever-changing role is not without its own, unique challenges.
Firstly, the world of IT never stays still. Contrast this with more established areas of business like finance, HR, or sales. Accounting fundamentals don’t change. HR still operates in the same role as it has had for decades. And the sales playbook is still focused on relationship building - just like it has been for centuries! Not so with IT. The tech landscape is always shifting, requiring IT leaders to continually adapt.
Secondly, IT functions are most buffeted by hype cycles. AI is the hot topic at the moment, but many of us don’t have to cast our minds too far back to remember anxious boardroom murmurings about “the cloud,” “big data,” “SaaS,” “Web 2.0” - heck, even the Dot Com boom!
Thirdly, titles like CIO, CTO, and CISO are the newest on the C-Suite block. Given their newness, there's subtle pressure on individuals in those roles to justify their presence in a lot of organisations. The likes of sales, marketing, and finance have seen changes over the years, but they also have a more established seat at the table.
And lastly, there’s the fact that no business function sits outside of IT nowadays. This gives the IT department, but especially IT leaders, a unique view of the business that transcends the boundaries of their departmental silo unlike any other business function. This can be a weighty responsibility, but also incredibly enlightening!
With these unique challenges in mind, there is one skill that tech leaders need to build more than ever: their ability to influence. This includes building essential interpersonal skills like active listening, building relationships, and self-examination.
Related Reading: The Insights Don't Stop Here!
Why not check out some essential reading from our virtual bookshelf? Grab our free e-book, Mastering AI Success: Your Comprehensive Roadmap to Strategic Value Creation; nab your copy of our whitepaper, Data Security as a Foundation for Secure AI Adoption, or browse our AI-focused blogs here.
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