HyperFinity has warned that retailers are under growing pressure to adopt artificial intelligence without a clear enough view of how it will deliver commercial value.
New research from the Leeds-based retail actionable intelligence partner found that 91% of retailers feel either moderate or significant pressure to adopt AI in order to remain competitive, while only 46% say they have a well-defined AI strategy supported by clear value cases.
The study, based on 200 retail decision makers, shows how quickly AI has become a strategic priority in retail boardrooms. More than half of respondents, at 53%, described AI as one of the most important initiatives within their business, while 39% said competitor activity was influencing their roadmap.
Behind that urgency sits a more uneven picture of readiness. Some 42% of retailers said they had identified potential use cases but remained uncertain about the commercial value those projects would deliver. Only 27% said their teams were fully prepared for agentic AI deployment, while 25% described their workforce as only somewhat ready and 5% said they were not ready at all.
Thomas Hill, co-founder of HyperFinity, said: “This research tells us that, as AI adoption accelerates, retailers face increasing pressure to develop the skills, governance frameworks and operating models needed to support long-term success.”
Retail leaders increasingly expect AI to do more than analyse sales, stock, and customer behaviour. More than four in five respondents, at 83%, said AI would either lead decisions or automate them across retail operations within the next year. Half expect AI to lead operational decisions while humans provide oversight and strategic direction, while 33% believe AI will automate most trading, customer, and operational decisions with minimal human involvement.
Views differ sharply by function. eCommerce directors were the most cautious, with only 9% expecting AI to automate most decisions. That compares with 42% of chief data officers and 35% of chief customer officers, suggesting that the teams closest to customer journeys and commercial execution remain more guarded about handing over judgement to automated systems.
Hill added: “The conversation in retail has shifted dramatically over the past twelve months. Most retailers no longer need convincing that AI matters. The challenge now is building the capability to turn AI into measurable business outcomes.”
He said: “What we’re seeing is a growing divide between organisations experimenting with AI and those embedding it into their operating model. Success won’t come from deploying the most AI. It will come from having the strategy, governance and decision-making frameworks needed to create value from it.”
Retail technology spending is already being pulled into pricing, loyalty, fulfilment, store operations, and customer service. Tesco’s digital shelf-label rollout showed how data infrastructure, store operations, and margin management are becoming more tightly connected. AI investment now sits in the same operational territory: retailers are not only buying new tools, but redesigning how commercial decisions are made.
Customer service and inventory and replenishment were viewed as the most likely functions to adopt agentic AI first, cited by 42% and 37% of respondents respectively. Those areas lend themselves to repeatable decisions, where automation can reduce manual work, improve consistency, and speed up response times.
More complex judgement remains harder to automate. Pricing, loyalty, promotions, and customer engagement combine data, margin, stock flow, competitive positioning, and brand judgement. AI can recommend actions and model outcomes, but companies still need clear rules on when decisions should be automated, when humans should approve them, and how performance will be measured.
Hill said: “AI is exceptionally good at automating repeatable operational processes, whether that’s customer service interactions, replenishment decisions or inventory management. But the bigger opportunity lies in helping retailers make better decisions.
“Areas such as pricing, loyalty, promotions and customer engagement still require commercial judgement and context. The future isn’t AI replacing people. It’s AI providing recommendations, insights and reasoning that help people make better decisions faster.”
The next phase of retail AI adoption will be judged by outcomes rather than adoption statements. Companies that connect use cases to margin, retention, stock productivity, and customer trust will be better placed than those scaling automation without a clear operating model. The pressure to move quickly is real, but speed without governance risks producing a new layer of tools rather than better commercial decisions.
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