How Retailers Are Actually Using AI in 2026

We recently attended the Retail Innovation Council’s Retail Leaders’ Summit, a closed-door session where senior retail leaders came together to talk openly about what’s actually happening inside their organisations.

And honestly, those are usually the best conversations. When people step away from the sales pitches and polished presentations, you start hearing the real challenges, the real opportunities, and where businesses are genuinely starting to see value from AI.

A few themes came up again and again throughout the day.

Retailers Are Moving Past AI “Experimentation”

One of the biggest shifts we noticed was the conversation moving away from pilots and proofs of concept.

Not long ago, most discussions around AI in retail were still very exploratory:

“What could we do?”
“Should we test this?”
“Maybe we’ll run a small pilot…”

Now the conversation feels different.

Retailers are starting to ask:

Where can AI genuinely improve operations?
Where can we reduce manual work?
How do we make better decisions faster?
How do we create better customer experiences without increasing costs?

That shift feels important because it means AI is becoming less of an innovation project and more of a business conversation.

Connected Data Is Still One of the Biggest Challenges

Another topic that came up a lot was data. Not necessarily “big data” or complicated AI models; just the challenge of getting systems connected properly so businesses can actually see what’s going on.

A lot of retailers are still dealing with fragmented systems across ecommerce, stores, finance, customer service and operations. And when data sits in silos, decision-making becomes slower and harder.

One of the discussions around build vs buy touched on this really well. The point wasn’t that building your own systems is always the answer. It was more that organisations who have control of their data tend to move faster because everything is connected.

That’s something we see regularly at Ignite AI Partners too. A lot of the work we do starts with helping organisations create a single source of truth, because without visibility across the business, it becomes very difficult to scale AI properly or make confident decisions.

Agentic Automation Is Getting Serious Attention

Another thing that stood out was how much focus there is now on agentic automation. Retailers are actively looking at where AI can remove repetitive, manual work across areas like:

customer service
finance
reporting
operations
internal workflows

And it’s not hard to understand why. With rising labour costs, National Insurance increases, business rates and ongoing pressure on margins, businesses are looking for smarter ways to operate.

The interesting thing is that the conversation isn’t really about replacing people. It’s more about freeing people up from monotonous tasks so they can spend more time adding value, solving problems and making decisions.

A Really Interesting Point: “Comprehension Debt”

One of the most interesting ideas discussed during the event was something called “comprehension debt.” The concern is that organisations move so quickly with AI that eventually nobody fully understands how things work anymore.

AI writes the process.
AI builds the workflow.
AI generates the output.

But over time, ownership and understanding start to disappear. It’s a fascinating point because while AI is an incredible accelerator, businesses still need people who understand:

how systems work
where data comes from
why decisions are being made
what risks exist underneath the surface

That balance between speed and understanding felt like a really important takeaway from the day.

Transformation Still Comes Down to People

Even though the event focused heavily on AI and technology, one thing became very clear: Transformation is still mostly about people. Training, stakeholder management, communication and adoption are still some of the biggest barriers to success.

Because even the best technology initiatives can struggle if people don’t understand:

why change is happening
what the benefit is
or how they fit into it

That’s something we talk about with clients a lot. Technology is usually the easier part. Bringing people with you is the harder part.

Retail Is Starting to Rethink How People Use Data

There were also some brilliant discussions around how AI is changing the way people interact with data altogether. Instead of expecting teams to dig through dashboards and spreadsheets, businesses are starting to explore:

conversational reporting
natural language querying
visual AI interfaces
even audio-based reporting

Because realistically, most people don’t enjoy digging through reports. They just want answers. The idea of being able to “talk to your data” is becoming much more real, and it has the potential to make analytics far more accessible across organisations.

AI Use Cases Are Becoming Much More Practical

Some of the most exciting conversations were around practical applications of AI that are already speeding up workflows dramatically. Things like:

turning product images into editable concepts
using voice prompts to tweak designs
generating 2D and 3D renders within minutes
speeding up production and merchandising processes

Work that might previously have taken days or weeks can now happen in minutes. And that’s where AI starts becoming genuinely transformative; not because it sounds impressive, but because it changes how businesses actually operate day to day.