Artificial intelligence has become one of the biggest talking points in retail. 

From streamlining operations to personalising the customer experience, it’s hard to find a boardroom that isn’t exploring what AI could do for them. 

Yet for many, progress feels slower than expected. Projects begin with energy and optimism but end with confusion about what went wrong.

Some reports suggest that most AI initiatives never reach the goals they were meant to achieve. In a sector that runs on tight margins and shifting consumer habits, that can feel discouraging. 

It also raises a deeper question. If AI can do so much for retail, why is it proving so difficult to get right?

“AI has so much potential, but it’s not the technology that’s holding it back. It’s the way retailers approach it. When you stop chasing shortcuts and start focusing on process, real progress begins.”
- Matt Sherwen, Managing Director, Sherwen Studios.

The rush to keep up

Retail moves fast. Trends change overnight and new technology seems to appear every week. 

When AI became the latest must-have innovation, many businesses jumped in quickly to keep pace with competitors. It’s understandable. Nobody wants to be left behind while others claim to use AI to cut costs or improve service.

But when projects start with a need to look innovative rather than a clear sense of purpose, they often lose direction. 

The technology becomes the focus instead of the problem it was meant to solve. 

What begins as a bold step forward can quietly turn into another project that never quite delivers.

The people behind the process

Behind every AI initiative are teams trying to make sense of something unfamiliar. Technology plays a part, but people make or break the outcome. 

When employees don’t understand how a system works or what it’s meant to achieve, trust begins to fade. Some even worry that automation might replace them altogether.

Trust grows when communication is open. When people see how AI supports their roles rather than replaces them, attitudes shift. Collaboration replaces hesitation. 

The best projects are not built around machines but around humans who know how to guide them.

When data holds you back

Retailers generate oceans of data. Every sale, return, website click, and delivery adds to it. But many businesses find that having more data doesn’t automatically mean better results.

Poor data quality can quietly derail even the smartest initiative. 

Missing information, disconnected systems, or inconsistent formats make it hard for AI to find meaningful patterns. 

Before adding new layers of technology, it helps to step back and ask a simple question. Can we trust our data? 

Cleaning and connecting that foundation might feel slow, but it often saves months of wasted effort later.

The problem with one size fits all

AI tools have never been easier to buy. Off the shelf solutions promise instant insights and rapid transformation. 

The appeal is obvious, especially for retailers under pressure to act quickly. But ready-made software rarely fits the reality of day-to-day retail.

Every business has its own mix of products, systems, and customer expectations. What works for one company might not make sense for another. 

The retailers that see results usually tailor technology to match their own operations. 

The smartest choice isn’t always the newest or the flashiest one. It’s the one that fits naturally.

Start small to go far

Ambition drives innovation, but it can also trip it up. Many teams try to overhaul everything at once instead of proving value in one area first. The retailers who make AI work often begin small.

“Failure isn’t the end of innovation. It’s the evidence you’re trying something new.”
- Matt Sherwen, Managing Director, Sherwen Studios.

A single project with a clear goal is easier to manage and easier to measure. It might be forecasting demand for one product range or improving delivery scheduling in a specific region. 

Small wins build confidence and create momentum. Each success becomes a lesson that shapes the next step.

Turning setbacks into progress

Even the best-prepared projects can stumble. That doesn’t have to be a failure. The retailers that grow stronger from each attempt are the ones who see setbacks as part of the journey. 

Every wrong turn reveals something new about data, processes, or expectations.

What matters is reflection. Teams that review what went wrong develop a sharper understanding of what to try next. 

Over time, those lessons turn into genuine expertise. Failure becomes a sign of progress rather than defeat.

Rethinking what success looks like

AI isn’t something to finish and tick off a list. It’s an ongoing process of learning and improving. 

The retailers who see the most value are the ones who stay realistic about what AI can do and keep learning from each step.

Real progress happens when teams trust each other, set achievable goals, and remain curious. 

The path might not always be smooth, but each attempt brings the technology closer to solving real problems. 

That shift in mindset is what transforms AI from an exciting idea into something that truly works for retail.