The Role of the Retail AI Leader: More Than Just Tech

Your company’s AI strategy will likely fail.

This may sound blunt, but it reflects a statistical reality. While AI is everywhere in today’s headlines, a recent survey of C-suite leaders painted a clear picture: 

For all the investment, only about one in five could say that generative AI had lifted their company's revenue by more than 5%. 

For the vast majority, the financial return is not yet there.

So what separates that successful minority from everyone else? It often comes down to a new type of leader: the "Head of AI." From my conversations with boards, it’s clear this leader’s success depends less on their technical skills and more on their ability to operate as a true business leader. This is especially true as powerful new tools like Agentic AI, which can automate entire workflows, raise the stakes even higher.

Their first and most critical task is to shift the conversation from potential to proof.

AI value must be proven, not promised

Boards are tired of hearing about theoretical potential. They need to see tangible results.

But the promise of real margin impact exists, but is often overlooked. For example, analysis from firms like Bain & Company suggests that when generative AI is scaled correctly in retail, it has the potential to reduce costs in support functions by as much as 20%. It can even trim 1-2 percentage points from the cost of goods sold.

So why do most companies never get there? They get caught in the hype cycle, launching generic chatbots or minor personalisation projects that ultimately go nowhere near that kind of result.

This is where the most effective AI leaders change the conversation entirely. They bypass the hype and go straight to the CFO or the Head of Supply Chain with one simple question: "What is your most expensive, inefficient, or frustrating problem right now?"

• Is it the cost of managing returns?

• Is it the inaccuracy of stock allocation to stores?

• Is it the high volume of low-value customer service queries?

By focusing on costly business problems first, they immediately prove the value of AI in a language the entire business understands: pounds and pence.

But this requires a leader whose skills go far beyond the purely technical.

The Real Work Happens Outside the Tech Silo

While most Heads of AI come from a data science background, their technical depth is only the starting point. The most effective leaders I've seen have a relentless "commercial curiosity." They understand that their primary job is to bridge the gap between the algorithm and the shop floor.

This means they spend their time very differently from a traditional tech leader. A high-impact retail AI leader does this:

• They listen first: They spend days with store managers to understand inventory frustrations, sit with merchandising teams during buying sessions, and listen to customer service calls to hear pain points directly.

• They build a network of champions: Armed with this real-world knowledge, they don't just push their own agenda. They find rising stars in other departments, like a data-savvy person in logistics, and empower them. They mentor these individuals and give them the tools to solve problems they care about.

• They share the credit: When that "champion" in logistics saves the company money on shipping routes, the AI leader ensures senior leadership knows who was responsible.

This approach of listening, empowering, and sharing success is how they build influence. They are no longer seen as an isolated tech expert. They become a trusted partner who helps other teams win. This creates a groundswell of support that pulls innovation through the business, rather than having to push it from the top down.

Communication is the differentiator

The ability to "decode" complexity is what separates a technical expert from a strategic leader. In a retail boardroom, no one needs a lecture on neural networks. They need a clear, compelling story about business outcomes.

A great AI leader can frame a project in three distinct ways for three different audiences:

• For the Board: "This project will reduce our inventory holding costs by 15% and improve margin by 2% within 12 months."

• For the Merchandising Team: "This tool will help you spend less time on manual forecasting and more time finding great products for our customers."

• For the IT Team: "We will be integrating a new API into our existing ERP system. Here is the technical roadmap and the support we will need."

Key Takeaway: The goal is not to make everyone a data scientist. The goal is to give everyone the confidence that the AI strategy is driving the business forward.

Strategy first, technology second

Finally, a great AI leader understands that AI serves the business strategy. It should never be a standalone initiative. Every project must be tightly aligned with the company's overarching goals.

Before committing to any new tool, they filter it through the most important business priorities by asking simple, powerful questions:

• Will this help us acquire more of our target customers?

• Will this make our supply chain more resilient to disruption?

• Will this create a customer experience that people are willing to pay a premium for?

As I often say, the best technology leaders in retail are the ones who align innovation with real, pressing business priorities. If a new technology doesn't support a core goal, they have the discipline to walk away, no matter how exciting it seems.

Closing Reflection

When you are ready to hire for this role, here is my single most important piece of advice: do not give the job to the person with the most impressive technical credentials.

Instead,

• Give it to the person who asks the best questions about your business.

• Give it to the person who has the courage to tell you which projects you shouldn't do.

• Give it to the leader who can explain their strategy to the board with the same clarity and conviction as they can to a warehouse operative.

You may find this person is not your lead data scientist. It might be a rising star from your commercial or operational teams who has a deep curiosity for technology and a proven ability to get things done.

So, I'll leave you with a final question to consider. When the board asks you in 12 months what the return on your AI investment has been, who do you want standing beside you to answer it? A technologist who can explain the process, or a business leader who can show them the profit? 

I’d be very interested to hear your thoughts on this, or to have a confidential conversation about what you’re seeing in your own organisation.