AI, Acceleration and the 30-Year Legacy Challenge

July 10, 2025 | Deepan Sakthithasan

When James Emmett, our Group CEO, founded Hanover nearly 30 years ago, the business ran off a fax machine in a basement. Today, we’re operating across global markets, placing senior talent into some of the most complex and high-stakes environments in the world.

That evolution didn’t happen by standing still. Hanover has stayed competitive by embracing the pace of change and investing in the people who know how to harness it. It’s the same reality many of our clients across financial services are facing now.

Especially in the industrial technology sector, where I spend most of my time, the pressure to transform is intensifying. AI is no longer theoretical. It’s not on the horizon. It’s already embedded in how factories run, how supply chains move and how products are made.

I see an imperative for companies – across all sectors – to start viewing disruption as market tailwinds, not headwinds. Capitalising on these requires smarter systems and smarter people. In 2025, that means leaders who understand AI, not as a tool for efficiency, but as a catalyst for reinvention.

Manufacturing meets machine learning

Smart factories have existed for over a decade. What we’re seeing now is their evolution into fully autonomous, self-learning ecosystems. I wrote about this a few months ago: machines that recalibrate in real time, systems that optimise logistics without human input, quality control powered by computer vision with microscopic precision.

While the rapid expanse of AI adoption is set to increase global productivity over 40% by 2035, it’s also highlighting a leadership challenge. You can’t plug in AI and expect results. You need senior teams who understand how to implement it responsibly, how to translate it into value, and how to upskill the workforce around it. That’s where many firms are still struggling.

There’s also a hge talent gap in AI-related disciplines. You need engineers with digital fluency. Data scientists who can operate in industrial environments. Leaders who understand cybersecurity, compliance and innovation cycles. I’ve helped multiple clients rethink what good looks like in these roles, and in many cases, build entirely new leadership frameworks from scratch.

cto skills

What financial services can learn from this

Although my primary focus is technology, there are common threads across the FS market. The biggest is urgency. In financial services, AI adoption is now close to saturation point, but many firms are still playing catch-up when it comes to talent, reflected in a 35 percentage-point gap between the demand for AI-related capabilities and the available talent in UK financial services. Critically, the talent gap is most pronounced for specialist and leadership roles that drive AI strategy.

In response, we’re seeing leadership teams reimagine structure, adding Chief Data Officers, upgrading CIO roles, or hiring operational heads who can lead transformation programmes rather than just run them. Behind all of this, there’s increasing reliance on AI not just for customer service or fraud detection, but for shaping investment decisions, optimising portfolios and modelling long-term risk.

But it’s not a free pass. The more firms lean on AI, the more vital human oversight becomes. There’s a false confidence emerging from AI-assisted decision making. I’ve seen examples where automation created a performance uplift, but left firms vulnerable to compliance breaches and ethical blind spots. In both FS and manufacturing, the leaders who thrive will be those who keep AI on a leash and know when to trust human judgement over machine output.

The next 30 years starts now

If you want to ensure your business’ legacy lasts another 30 years, you need to be investing in the kind of leadership that isn’t just technically capable, but strategically future-proof.

Hanover’s evolution mirrors the challenge many of my clients are navigating: staying relevant by staying responsive. Whether I’m supporting an advanced engineering firm exploring predictive autonomy, or an FS firm building a data-led operating model, the brief is the same: find the person who gets it.

And fast.

If this is on your agenda, I’d be glad to share more of what we’re seeing in the market, what’s working, and how we can get you ahead. Let’s talk.