AI Success = Tech + Leadership. Miss One, Fail Both.

Professor of AI and founder of Informed.ai, Andy Pardoe, writes in his recent article The Dawn of a New Era – Our Quantum Future:

“AI powered by large-scale quantum computing will give us real AI—and at superhuman levels very quickly. The world’s first quantum processor (powered by topological qubits) leverages a new state of matter and appears to allow us to scale the number of qubits far beyond what has been possible so far. Heralding quantum AI…

The next generation of AI models will no doubt make today’s cutting-edge large language models look infantile. AI 2.0—or quantum—will transform our world more in the next 10–20 years than anything we’ve seen before. Humans will no longer be the highest form of intelligence.”

This is not just the next technological leap—it’s the final frontier. As Andy points out, this moment is not simply an evolution in computing, but a fundamental shift in how intelligence, decision-making, and value creation will operate in the decades ahead. The idea of artificial general intelligence—once speculative—is fast becoming a plausible near-term reality. And with quantum computing accelerating the trajectory, the timeline has collapsed from "one day" to "within our careers."

The Clock Is Ticking

In more immediate terms, entrepreneur and author Daniel Priestley offers a stark warning to business leaders:

“If you’re not doing something with AI now, you’ll regret it by 2030. You’ll look back and think: all the signs were there, I had the opportunity—why didn’t I take advantage of it?”

Daniel was speaking about today’s AI—the tools already available to businesses. That was before Prof. Andy introduced the dawn of a second, more disruptive wave. Many leaders haven’t even finished digesting their AI starter, and the main course has already arrived.

From Buzzwords to Boardroom Priorities

Already overcrowded boardroom agendas now have two urgent additions:

Adopt AI technology, and
Do it fast.

Watching from the sidelines is no longer a viable strategy.

At Informed.ai, we’ve been in deep conversations with executives across industries. The consensus? Most leaders (not all) understand that AI is a game-changer. But few fully grasp the scale of the change. The penny hasn’t dropped that this isn’t about marginal growth—it’s about existential survival.

“It’s no longer a question of ‘how do we grow?’ It’s: ‘will we still exist?’”

The Infrastructure Blind Spot

Our work has exposed some uncomfortable truths. Unless you’re a tech company, chances are you’ve dramatically underinvested in technology. For years, tech has been treated as a cost centre—not the essential lifeblood of a future-fit business. That mindset must change.

The recent cyber incidents at M&S and the Co-op are only the beginning. Legacy infrastructure is not just a performance risk—it’s a reputational and existential one.

Data Dreams vs Data Reality

Every organisation likes to talk about “data lakes” and “unlocking the power of data.” But in reality, most are dealing with data puddles—shallow, fragmented, and dirty. Systems don’t talk to each other. Silos abound. Clean, integrated, usable data is still the exception, not the norm.

And yet, AI success depends on the integrity, accessibility, and interoperability of your data. Without that foundation, everything else collapses.

Overcoming Inertia

What’s holding businesses back? A few core challenges:

Which tech stack to choose?
How to integrate AI without breaking existing operations?
What will the impact be on people, culture, and roles?
How do we balance automation with empowerment—freeing people to do more exciting, valuable work?

The promise of AI agents—automated digital coworkers—is real. But so are the organisational and ethical implications. Businesses need frameworks for adoption, not just ambition.

Right now, most companies are defaulting to “no-regret” moves—small, safe pilots. But what’s needed are bold, strategic leaps.

Mistakes to Avoid

Few organisations have a real AI strategy, let alone a roadmap for implementation. And among those that do, some common tactical missteps are emerging:

1. Relying entirely on off-the-shelf solutions.
These tools are a good start, but by definition, they’re generic. They won’t differentiate your business or provide a sustainable competitive advantage.

2. Trying to build everything in-house.
It’s tempting—your IT team is smart and eager to explore. But enterprise IT and AI development are two different disciplines. Recruiting top-tier AI talent is almost impossible unless you’re Google, OpenAI, or a top-tier university.

3. Don’t automate a bad process
Sometimes a review of the processes themselves should be done before looking to automate them, this will provide an opportunity to improve the overall end-to-end process and make it easier to fully automate the workflow.

Experience shows that in-house AI often fails to deliver impact. Worse, it can entrench bad practices and make expert intervention harder later.

The Path Forward

The path to AI success is paved with good intentions—and failed pilots. But it doesn’t have to be this way.

Informed.ai brings together technical depth, commercial insight, and strategic clarity to help leaders not just experiment with AI, but implement it with purpose. We work across: