Building AI operating models that deliver

AI dominates today’s tech conversations, but the reality is sobering: many organisations seem unable to scale their pilot projects or achieve meaningful benefits. Chris Fisher, Director at Mozaic, argues that the key to unlocking value lies in rethinking operating models before investing in tools. Chris also shares insights on balancing innovation with risk, hiring for transformation and why the fundamentals of IT leadership still matter in an era of rapid change.

Why is it essential for organisations to look beyond technology when planning for AI adoption?

Many organisations think about change in terms of discrete programs or the latest technology trend, but they don’t always consider the full set of changes needed to truly capitalise on those investments. And yet, in today’s tech marketplace, you’ll see a lot of vendors marketing AI solutions as silver bullets.

People are shopping for tools without thinking about what else needs to change in their organisation to make those tools effective, or even scalable beyond a pilot. Before investing in tools, a complete assessment and redesign of your operating model is needed for AI to be integrated effectively. It’s not about just bolting on new tools and hoping for the best.

So, essentially, organisations should map out their end goal and work backwards before buying tools?

Exactly. I would encourage today’s business leaders to step back and consider both opportunities and risks before focusing on tools. My background is in the public sector, so I care deeply about delivering value for money, especially when public funds are involved. If you rush into buying new technology without keeping that front and centre, you’ve missed a critical step.

From a risk perspective, why should organisations be seriously considering developing effective policies and guardrails for AI?

This is a fascinating area, especially in government. We’ve seen some departments react with a knee-jerk approach, jumping straight to zero trust and trying to eliminate any shadow AI. They’re paranoid about risk, and while that’s understandable, it can stifle innovation. 

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Others are more forward-thinking. They start from the principle that data — especially citizen data — must be protected, but they take a common sense approach. They talk to people, understand their needs and use cases and then develop policies that enable responsible use rather than restrict everything.

That’s the sweet spot: enabling innovation while safeguarding what matters most.

When hiring or retaining key people, what skills do you look for?
I’m always proud to hire industry experts; people with 10 plus years of experience in senior IT roles or large-scale transformation programs. That means they can sit across the table from a client and say, ‘I’ve been in your shoes. I understand your challenges, and I can help you solve them.’ To retain those people, it’s about two things: giving them interesting, challenging work and rewarding them appropriately. If you get those things right, you keep great talent.

What challenges are you seeing in the market right now? Are there common themes?

Right now, everyone wants to do AI. The hype is enormous, and ‘fear of missing out’ is rampant. I hate that phrase, but it’s accurate here. Organisations are jumping on the bandwagon without considering the implications or how they’ll capitalise on AI. They’re worried that others are doing it and they’re not. At the central government level, that pressure is amplified by what they see in the private sector.

Companies are touting their AI initiatives because, if they don’t, boards and shareholders will demand answers. My advice to the government is: don’t be sucked in by the noise. The reality is, nobody is doing this particularly well yet.

What’s the one piece of advice you’d give to an IT professional looking to advance their career in today’s tech landscape?

First, I’d challenge the idea that this is a radical revolution. It’s not. It’s an evolution. We’ve seen this before — new technologies that supposedly change everything, wipe out roles and require new skills. This is just the next iteration.

The core skills that make people successful in technology haven’t changed. It’s about being a strong change manager and advocate. It’s also about understanding technology well enough to explain it clearly to non-technical audiences. If you lapse into jargon because you don’t really understand it yourself, you alienate people and create silos.

So, my advice is to be open to change and embrace new opportunities. That’s more critical than being an expert in the latest shiny tech. If you specialise in a single tool, you risk becoming redundant when the next big thing arrives.