Why AI adoption stalls on the shopfloor — and how retail leaders can fix it

There’s no shortage of big promises about AI and digital transformation across the retail industry. New tools, smarter data, better decisions.

For many retail businesses, the goal is to improve operational efficiency, streamline operations and deliver better customer service - but that only happens when tools work in real retail operations, not just in theory.

But the real test is much simpler: do those tools make life better for the people running stores day to day?

To explore that, we partnered with Retail Week on the Talking Shop 2026 report, based on a survey of 500 UK frontline retail workers across multiple sectors. You can read the full findings in the report.

The results show how AI and wider digital change are landing on the shopfloor today and what needs to change if they’re going to work in practice.

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Frontline workers aren’t anti-technology

Where digital change is stalling 

AI on the shopfloor: curiosity and concern

Where digital and AI are already working

Predictive workforce planning: where AI meets everyday reality

Fixing the gap between AI strategy and frontline adoption

The next phase of AI in retail: people first 

Frontline workers aren’t anti-technology 

One message from the research is clear: frontline teams want technology, when it’s done well.

62% of frontline workers agree that having the right technology in place would improve store operations, while 87% expect the amount of technology in stores to grow in the future, rising to 92% in fashion.

When we asked where technology could make the biggest difference, colleagues focused on practical needs: stock availability, staff training and learning, access to rotas and employee scheduling, and the ability to secure hours.

This includes better ways to manage schedules, improve employee availability, and support flexible schedules that reflect personal commitments, evening shifts and work-life balance.

In other words, they want tools that fix real operational problems. The right stock on shelves. The right skills in the building. The right people, in the right place, at the right time.

Where digital change is stalling 

Despite this appetite, many frontline employees feel digital change isn’t landing well in stores.

From the Talking Shop 2026 data:

• 40% say there isn't much digital change in their store, or that it is happening too slowly
• 44% say digital change is driven from the top, without frontline input, rising to 51% among workers aged 16-35

17% say the technology introduced so far hasn’t meaningfully improved how they do their job 

Why current scheduling practices and systems fall short 

In anonymous comments in the survey, similar themes come up again and again. Frontline staff often feel new tools arrive with little explanation or training. They perceive that decisions are made centrally, with limited discussion of what will actually work in busy stores. Different roles have different levels of access to systems, creating friction and workarounds across retail operations.

In practice, this often leads to inefficient scheduling processes, manual data entry and disconnected workforce management systems that don’t reflect how retail stores actually operate.

The message isn’t “we don’t want technology.” It’s “we want technology that reflects how stores really work - and is built with us, not just for us.” For retail leaders, this highlights a clear opportunity to rethink how digital change is introduced and embedded in stores.

AI on the shopfloor: curiosity and concern

AI is a priority for many retail leaders. Our research suggests frontline teams are open to the idea, but still unsure what it means in practice.

When asked about AI in daily store operations:

• 30% believe AI would help their store’s daily operations
• 41% are unsure about AI’s impact
• 34% worry technology could replace parts of their role

Yet, when AI is applied to a clear, familiar problem in-store, that level of frontline trust looks very different.

AI, retail scheduling software and shift schedules

76% of frontline staff say they would trust AI or intelligent retail scheduling, in some form, to manage their store rota.

This contrast matters. Many employees are wary of abstract AI projects, but when it’s applied in a visible, practical way - such as building fairer, more accurate rotas - confidence increases. This is especially true when it helps managers adjust schedules, reduce conflicts and better balance business needs with employee preferences.

The lesson is straightforward. Framing and use case matter - especially when AI supports core workforce management activities like scheduling, staffing and day-to-day decision-making.

If AI is presented as a black box or a way to track efficiency, it creates fear. If it's positioned as a way to solve everyday problems that store teams already recognise, it can gain traction quickly.

Where digital and AI are already working

The Talking Shop 2026 report highlights several examples of workforce management technology helping, not hindering, frontline teams.

Currys – making data usable for store leaders 

Currys launched Action AI, a tool that makes business-critical data easier for store managers to find and use.

Instead of wading through spreadsheets, a sales manager can log in, see which product categories are underperforming, drill down into root causes using real-time transaction data, and compare performance with top-performing stores across the estate.

As Currys’ Chief Operating Officer, Lindsay Haselhurst, put it, the tool “cuts through the mountain of data,” so managers can focus on helping customers with their tech needs, not chasing reports.

This is AI and analytics as a combined enabler - giving store leaders access to the same quality of insight used at head office and supporting better decisions on the ground. It also helps store managers save time, reduce reliance on spreadsheets, and improve business performance through faster, more informed decisions.

The Entertainer – intelligent workforce management

Toy retailer The Entertainer uses Rotageek’s intelligent workforce management platform that combines AI-powered forecasting with smarter employee scheduling.

Managers get real-time visibility of labour demand versus spend, while colleagues can swap shifts, request shifts, manage employee hours and submit preferences through a mobile app, often with manager approval built into the process.

This mix of better forecasting and more flexibility has strengthened the relationship between senior teams and the frontline. Scheduling becomes a shared process rather than a source of friction, supporting wider job satisfaction and employee retention.

Boden and Debenhams – AI-powered pricing

Fashion retailer Boden, and later Debenhams’ online business, have used AI-powered pricing to move away from blanket markdowns.

By analysing real-time demand, sell-through and margin data, AI helps identify which products need deeper discounts, protect margin where demand is still strong, and reduce waste and excess stock.

Here, AI is focused on one specific commercial problem. It isn’t trying to run the whole business - and that’s exactly why it works.

Predictive workforce planning: where AI meets everyday reality

One of the clearest themes from Talking Shop 2026 is the pressure created by reactive retail scheduling.

71% of frontline workers describe scheduling in their store as reactive, with last-minute changes, under or over-staffing, and unpredictable rotas. When staffing is wrong, colleagues say they struggle most with keeping shelves stocked, completing back-office tasks, and taking sufficient breaks — all of which directly impact service, availability and overall store performance.

For retail leaders, this doesn’t just affect day-to-day operations — it has a direct impact on the bottom line, from lost sales and reduced productivity to increased labour costs and turnover.

This is where predictive workforce planning has real impact. It plays a critical role in improving operational efficiency by aligning staffing levels with real customer demand, rather than relying on reactive scheduling practices.

Aligning staffing levels with customer demand

By forecasting demand and aligning labour accordingly, retailers can:

• Prevent understaffing, with adequate staffing during peak business hours and seasonal uplifts in demand
• Reduce overtime by cutting last-minute fixes and emergency shifts
• Improve customer experience by having the right people available at the right time
• Support store teams with more stable rotas and fewer surprises

Done well, this shifts workforce management from reactive firefighting to a more proactive, strategic approach. It improves employee satisfaction, supports wellbeing and creates a better work-life balance for hourly workers — while enabling retail leaders to run more effective, productive operations with greater control over cost and performance.

It also shows frontline teams what “good” AI looks like. The inputs are clear - footfall, transactions, events and promotions. The outputs are tangible - better rotas, fewer gaps, less pressure. And colleagues remain involved through preferences, availability and shift swaps.

Fixing the gap between AI strategy and frontline adoption

The Talking Shop 2026 findings point to four practical shifts for retail leaders.

1. Start with store reality, not strategy slides

Anchor AI and digital initiatives in everyday challenges: stock availability, rotas, training and customer queues. Use employee feedback to prioritise where to focus.

2. Bring colleagues into the design process

Move from “announce and rollout” to “co-design and pilot”. Involve store teams early, test in real environments, and iterate based on feedback. Encourage employee input from team members early on, and refine scheduling tools based on real store feedback to support continuous improvement.

3. Make AI explainable and visible

Be clear about what data is used, what decisions are supported, and what will change in practice. When people understand how a system works, trust increases.

4. Use workforce planning as a foundation

If you’re looking for a starting point, workforce management - and specifically predictive workforce planning - is one of the highest-impact use cases. It directly affects wellbeing, service and day-to-day store performance, and the benefits are easy to measure.

The next phase of AI in retail: people first

The reality on the retail frontline doesn’t always match how it’s represented in strategy.

Frontline workers are open to new technology. They see where it could help. They trust AI when it’s applied to clear, everyday problems like retail scheduling.

They are far less positive about top-down change that adds pressure without adding value.

The choice for retailers isn’t between more tech and less tech. It’s between digital and AI that are designed around real store operations - from scheduling and staffing to day-to-day decision-making -and solutions that remain abstract projects, disconnected from how stores actually run.

The Talking Shop 2026 report suggests that people-centred change is achievable and that predictive workforce planning is one of the best places to start.

By combining better forecasting, smarter scheduling and genuine colleague involvement, retail leaders can turn AI from something the frontline endures into something they actively support.

Ultimately, the goal isn't just efficiency, but enabling retail employees to deliver outstanding customer service, improve customer satisfaction and create memorable shopping experiences in physical stores.