HSBC's non-tech Chief AI Officer sparks debate on who should lead enterprise AI

Full text

As businesses race to operationalize AI, a growing number are creating dedicated AI leadership positions.

The appointment of HSBC’s first Chief AI Officer, for example, caused a stir when it was unveiled earlier this year.

When the financial services giant announced plans to build a bank for the future – and cited the key role that an enterprise-wide AI strategy will play – many people no doubt expected the new position to be filled by a technologist. Instead, the inaugural title was given to David Rice – a reported HSBC veteran of 20 years, who previously served as the bank’s Chief Operating Officer.

This became a hot topic of conversation, but in my opinion, for all the right reasons. Because, yes, HSBC’s decision may have come as a surprise, but I applaud it as the right one.

AI is not a tech silver bullet

C-suites are becoming increasingly energized about ever-intuitive technology and the potential to transform their organizations with capabilities such as agentic AI and advanced automation. The excitement is palpable and understandable.

But we must remember that like any technology, AI alone is not a silver bullet. After all, you can have the most sophisticated Formula One car in the world, but the vehicle alone doesn’t guarantee a podium finish. AI also doesn’t magically fix a messy business, it exposes it. So, simply investing six figures or more in cutting-edge technology will not automatically pave the way for positive strategic change.

That said, senior technology figureheads such as the CTO are often the most likely AI evangelists because they understand how AI can be utilized to achieve the transformational progress that is being sought.

They’re important advocates of the ‘art of the possible’. They can articulate the value, clarify what is and isn’t doable, help understand likely ROI, and if necessary, talk to department heads to help alleviate concerns.

They are an important voice in this entire conversation. But that doesn’t mean they have to lead it.

The role of the technologist

In large organizations, of course I believe the CTO should be ultimately responsible for the technology platform. We’re talking about something that will be used if not relied upon by potentially the entire workforce, so the build, deployment, security and governance considerations need to be safeguarded by someone experienced in managing business-critical infrastructure on this scale.

We also need to remember that although AI capabilities are changing rapidly, if you strip everything down, we’re looking at extremely smart code that should be written, tested, productionized, released, deployed, monitored and managed, with the same guardrails as other technology within the business.

At the very least, an AI leader therefore needs the CTO to be an ally, as the organization advances its digital maturity. And if such a technical specialist does not exist in-house, this level of strategic counsel must be sought from a trusted external partner.

Without this technical collaborator, the AI leader may quickly become unstuck. This is not about becoming a self-taught expert, however simple it seems nowadays to spin up a game-changing solution with vibe coding.

Alternative AI evangelists

But we need to remember some of the many other reasons that 95% of AI projects reportedly fail (MIT, 2025).

Often it is because large, complex initiatives have been kickstarted with significant budget, but a crucial stakeholder – such as operations – has only been brought in, at the final hour. When people feel excluded and their requirements unaccommodated, initiatives get blocked, projects stall and eventually things grind to a halt.

We must also realize that AI is only effective when you start applying it to particular workstreams, workloads and business processes – especially processes on a micro level. These micro-processes may seem inconsequential, when compared to the bigger picture.

However, if the AI evangelist can alleviate administrative pressure or a morale drainer that impacts a large number of people on a daily basis, the seemingly small productivity wins start to make a daily difference to colleagues who need to buy-in to AI for the longer haul.

Culturally, process orchestration is usually not something that a pure ‘techie’ understands or cares enough about. But for any AI initiative to be a success, the appointed AI leader is so dependent on unpicking, defining and if necessary refining every process and its interdependencies. An operations lynchpin – or another experienced and personable business analyst or transformation lead – is critical here.

If you want AI and the human workforce to augment one another, the AI lead also needs to understand people. For example, if you’re going to build an agent with a HR persona, which can sit inside that department to help address repetitive joiner, mover and leaver matters, it is firstly crucial to understand the role of a HR colleague. This extends far beyond the colleagues’ basic job description.

A transformative leader – whatever the role

The most successful projects need a senior stakeholder to direct departments, drive collaboration and unity, and confidently build, articulate, socialize, and enforce the AI strategy, among the people who’ll live and breathe the change. Even the most technologically gifted individual cannot do this alone.

That senior stakeholder could wear one of many hats, but whether they’re the CEO, CIO, CTO, COO, director of business transformation, or another change leader, they must have an innovation appetite, and the ability to articulate – perhaps with the help of their chosen partner(s) – what budget is required and why.

None of this is about ego. It’s about someone who can talk at level 5 to the layperson, and hold their own when talking at level 500 as the technical plans take shape. They know what they want to achieve, even if they don’t know how. They might not have a technical background, but they need to partner with someone who does.

Multi-disciplined responsibilities

In a perfect world, AI implementation is not anyone’s stand-alone problem – it is a multi-persona discipline. A talented AI engineer will always ensure you have the right configuration in response to the brief.

But the relevance and quality of the resulting solution depends on who has defined that brief in the first place, to what standard, and whether this truly reflects the strategic motivators of the business. If the AI lead can’t articulate what good looks like and how it links to the P&L, it will always be harder to get there.

To me, HSBC’s Chief AI Officer selection signals that this role is not simply about building new systems, but reframing how the business runs, for the benefit of customers and colleagues alike. And on the face of it at least, the bank appears to have covered all bases.

The Chief AI Officer is said to be working closely with the CTO, who will oversee the core technology foundations needed to support the necessary AI adoption initiatives. And I know the industry is watching with bated breath to see what unfolds.

Perhaps we need to all put job titles and skill-sets aside in favor of understanding the degree of change truly required, and the person – or people – best placed to lead the charge. I wonder how many enterprises will follow suit.

We've featured the best business computer.

This article was produced as part of TechRadar Pro Perspectives , our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit