AI Can Be the Medicine Businesses Need, But Only If We Prescribe the Right Dose

We’re an industry whose gaze is fixed on generative AI – its novelty, its promise, its limitations. But when I sat down with John Kirk, chief strategy officer at Inspired Thinking Group (ITG), it felt like a moment of clarity amidst the chaos. For John, the real value of this technology doesn’t lie in flashy, sparkly outputs, but in the transformative power of operational AI. “AI at its best isn’t about solving old problems – it’s about solving old problems in new ways,” he tells me.

John has spent nearly 14 years at ITG, shepherding the company from a 100-person startup to a global enterprise of over 1,500 employees. But his path into this world was far from straight. Starting out as a physiotherapist, he later moved into NHS management before deciding to pursue an MBA. That choice set him on a new trajectory. “The MBA was life-changing,” he says. In fact, his final project on defining the strategy for ITG after its first technology acquisition, ended up being the highest-graded strategic management project in the MBA’s 35-year history.

That same drive for innovation fuels his thinking about AI. “It relies on massive amounts of organised data,” John explains. “But too often, businesses try to slap AI on top of broken processes. It’s like putting a fancy roof on a crumbling house – it’s just not going to work.”

Beyond the Generative AI Hype

Generative AI has its fans, but John isn’t one to be swept up in the hype. While he acknowledges its potential, he’s quick to point out the limitations. “It’s great for sparking ideas or breaking down complexity,” he says. “But it’s not a silver bullet. Right now, it’s the novelty that’s impressive, not the creative output.”

He references Gartner’s “hype cycle” and its “trough of disillusionment,” where inflated expectations crash into reality. “By 2026, we’ll have a much clearer picture of what generative AI can actually do,” he predicts. “But today, it’s often overhyped.”

That’s where operational AI comes in. John argues that its value lies in transforming processes and delivering tangible results. “Think of it like moving from petrol cars to hybrids and then fully electric vehicles,” he explains. “Operational AI is the next step in that evolution.”

For John, it’s less about creating something entirely new and more about streamlining and enhancing existing processes. For him, the critical distinction is that while generative AI dazzles with its ability to create, operational AI delivers measurable, repeatable value. 

“Generative AI has its place – overcoming procrastination, sparking ideas, or breaking down complexity. But operational AI is where businesses can achieve true transformation. It’s not just about flashy solutions; it’s about embedding AI into workflows, creating efficiencies, and solving real problems,” says John.

Unifying the Approach

A great example of this is ITG’s work with Haleon (formerly GSK Consumer Health). “Since 2020, we have helped Haleon with a global marketing transformation using Storyteq,” John explains. “They execute simple, scalable, and sustainable projects extremely well, including AI, avoiding the pitfalls of indecision or half-measures. That’s what operational AI can do – move businesses from manual processes to fully automated ones.”

John is also a big believer in flexibility. “Many organisations anchor their strategy on one AI model or tool, which is risky,” he warns. “AI evolves so quickly that a single-model approach is outdated almost immediately.” Instead, he sees AI as a tool for bringing together fragmented systems. “Businesses are drowning in siloed tools,” says John. “We position ourselves as the unified layer that integrates these silos, enabling seamless operations. This isn’t just about technology integration – it’s about creating a foundation that allows organisations to evolve with AI.”

The Challenges of Getting It Right

While operational AI offers significant potential, John is candid about the challenges. “It requires a structured, logical approach, which isn’t always natural for marketing and creative teams,” he says. “It’s a blend of creativity and technology, and getting those two to work together can be tough.”

One of John’s key observations is the behavioural shift required for AI adoption. “Left-brain thinkers – logical and structured – are often better equipped to build the frameworks that operational AI depends on. But once those frameworks are in place, right-brain creatives can thrive within them,” he explains. “It’s about creating a balance between structure and freedom.”

Generative AI, meanwhile, faces its own set of issues. “Hallucinations, misinformation, or bias can be big problems,” says John, referring to AI’s tendency to generate false information. “Then there’s the very important question of trust – where the data comes from, whether it’s accurate, and whether it’s even legal to use. Those are hurdles operational AI can sidestep because it’s built on solid data foundations.”

Looking ahead, John envisions a future where AI acts as an assistant, enabling marketers to focus on strategy and creativity. “Imagine an AI asking, ‘What can I help you with today?’ The marketer might reply, ‘I’d like to launch a new campaign.’ The AI would then handle everything – from content origination to automation and delivery,” he says. “That’s where we’ll be in the next two to three years.”

He’s not worried about AI replacing the human touch. “AI frees humans to have pure creative thoughts, rather than bogging them down with repetitive tasks,” he argues. “It’s about augmenting human input, not replacing it.”

John also sees a clear divide between the short-term and long-term potential of AI. “Generative AI will become a staple for specific tasks, but operational AI will drive the broader transformation,” he predicts. “The idea of artificial superintelligence – machines surpassing human intelligence across all areas – is still a long way off, maybe 10 to 20 years. For now, AI’s role is to amplify human capabilities.”

A Strategic Prescription

John spent his early career as a physiotherapist looking at human anatomy, finding the source of the problem, and fixing it. Nowadays, he’s analysing a different anatomy. Dissecting businesses, finding the source of the problem, and fixing it.

“AI can be medicine for business. But like medicine, it needs to be prescribed properly – the right solution, for the right problem, at the right time, and at the right dosage.”

John reminds us of a broader truth about technology adoption. “You wouldn’t use a hammer to fix every problem,” he says. “Similarly, AI isn’t a one-size-fits-all solution. It’s about tailoring the tool to the task at hand."

As businesses navigate the complexities of AI adoption, John reminds us that AI’s true value isn’t in its novelty. It’s in its ability to solve real-world challenges.