AI is moving faster than your data. What should retailers do next? 

New research from PMC and Retail Economics explores the challenges holding back unified commerce. In this blog, Andy Tudor, CEO of Clekt, shares his perspective on what the findings mean for retailers looking to scale AI and turn investment into measurable business value. 

From demand forecasting and inventory management to customer personalisation, AI offers significant opportunities for retail and consumer goods businesses. But adopting the technology is only part of the challenge. Turning that investment into meaningful commercial results requires the right foundations, people and processes. 

That was a key theme in a recent panel discussion featuring Clekt CEO Andy Tudor, exploring the findings of Winning the Race to Unified Commerce: The Hidden Economics of Enterprise Transformation

Drawing on decades of experience helping businesses turn data and technology into commercial outcomes, Andy explores what the research tells us about AI readiness, why transformation can stall and what retailers should prioritise next. 

AI adoption is outpacing data readiness.  

The research highlights a growing gap between AI adoption and the foundations needed to support it. 

While 69% of organisations surveyed have AI live or scaled, only 50% have connected data, systems and architecture fully in place. Just 44% describe their data foundations as highly ready, meaning they are governed, accessible and integrated. 

The challenge becomes clearer when organisations look to scale AI across the business. Data quality or unification is cited as a top three barrier by 40% of respondents, while 35% point to disconnected customer, product, order or inventory data. By comparison, only 12% identify their current commerce platforms or applications as a leading constraint. 

For retailers, this suggests the barrier is not necessarily a lack of AI tools or technology. It is often the ability to give those tools access to reliable information, connect them to existing processes and use them consistently across the organisation. 

AI can only be as useful as the data and business context behind it. Without that foundation, organisations risk creating more pilots and isolated use cases without achieving the wider benefits they set out to deliver. 

Andy explains: 

“For retailers, the significant benefits of AI are unlocked by creating the data backbone that merges customer lifecycle and product lifecycle data into one accessible place. Without the backbone, AI benefits will be constrained into functional siloes, uncoordinated and at risk of compromising the customer experience.” 

The scale of the challenge is significant. PMC and Retail Economics estimate that modernising core systems across UK retail would require additional investment equivalent to 5.3% of annual revenue, or £25bn across the sector. 

With investment on this scale, getting the priorities right matters. Retailers need to understand which foundations are holding them back, where investment can deliver the greatest value and how to ensure new capabilities translate into better business outcomes. 

The gap between ambition and business value 

The research also highlights a disconnect between transformation objectives and the ability to measure their impact. While 61% of organisations say they have clear transformation objectives, only 36% measure return on investment very effectively. 

That matters because implementing a new technology is not, in itself, evidence of success. Retailers need to understand what they want to improve, how they will measure progress and whether the change is delivering the intended commercial or operational benefit. 

That could mean improving stock visibility, reducing manual work, making trading decisions faster or delivering a more consistent customer experience. The right measures will depend on the business problem, but they need to be clear from the outset. 

The report also finds a strong association between execution readiness and ROI measurement. Among organisations with three or four key execution prerequisites fully in place, 61% measure ROI very effectively, compared with just 3% among those with none or only one in place. 

These findings do not prove that any single factor causes better results. They do, however, reinforce the importance of combining connected foundations with clear ownership, disciplined delivery and organisational adoption. 

For Andy, measuring AI’s impact means looking beyond technology costs and financial returns alone: 

“ROI from AI is, however, more than the technology spend and return. Arguably the harder aspect of the benefit equation is the human impact of AI deployment. For example, AI could be used to remove human involvement (and cost) or it could be used to enhance human impact. Both might improve financial business performance but with, potentially, very different cultural consequences. Success is being able to measure the impact of AI in the round using a blend of KPIs.” 

What should retailers prioritise? 

The findings point to four practical priorities for businesses looking to get more from their data and AI investment. 

1. Start with the business problem 

Before choosing a technology or launching a proof of concept, be clear about the outcome you want to achieve. Identify where the business is losing time, money or visibility, and prioritise opportunities against their potential commercial value. 

2. Get the data foundations right 

Review whether the data needed to support your chosen use cases is reliable, accessible and connected across the relevant systems. Address quality and integration issues that could prevent a solution from working effectively at scale. 

3. Plan for delivery and adoption 

Technology needs to work within the realities of the business. Establish clear ownership, bring the right teams together and consider how new capabilities will fit into existing workflows. Adoption should be part of delivery from the beginning, not an afterthought once the technology is in place. 

4. Measure what matters 

Define how success will be measured before implementation begins. Track whether the solution is delivering the intended improvements and use those findings to inform decisions about what to refine, expand or stop. 

For Andy, this work starts with aligning data and AI with the wider business strategy. 

“There is no AI strategy without a Data strategy. The Data strategy must be aligned completely with the Company strategy. The operational objectives needed to underpin the Company strategy will provide the priorities which inform the Data strategy.” 

He also emphasises the importance of bringing people, processes and technology together, with business leaders treating data as a company asset and ensuring employees have the skills and understanding to accelerate their AI adoption and business value creation. 

The aim is not to slow AI investment down. It is to make sure investment is directed towards the right opportunities and supported by the conditions needed to deliver value. 

From AI ambition to measurable outcomes 

The research makes one thing clear: transformation is not simply about how much technology a business adopts. It is about how effectively that technology, the data behind it and the people using it work together. 

At Clekt, we believe getting value from AI takes more than access to the technology. It requires dependable data, secure and well-governed implementation, and a clear connection between what the technology can do and what the business needs to achieve. 

That is the thinking behind our approach to Assisted Intelligence: helping organisations put data and AI to work in ways that support their people, improve how they operate and deliver measurable business outcomes. 

For retailers considering their next AI investment, the starting point is not necessarily another tool or use case. It is understanding what the business needs to achieve, what is holding it back and what needs to be in place to make progress. 

Andy believes retailers must also be prepared to embrace change: 

“From my experience, the only constant in Retail is change. Ignoring the need to change is the death knell for retailers who dare to retain the status quo. AI is transformative in the opportunities it brings to the Retail industry and, perhaps, its impact will be unprecedented when we look back in a few years’ time at who the winners and losers have been.  The biggest challenge to well-established retailers is to evolve the culture such that adoption is embraced, experimentation is encouraged and guard rails are introduced to ensure that neither customer experience nor brand identity are compromised. AI (ai) has always existed in the word Retail, and the time is now to unlock the potential for your brand with this powerful technology. Do not become the next Blockbuster.” 

Ready to explore how data and AI could deliver more value for your business? Arrange a call with Clekt. 

About the research: Winning the Race to Unified Commerce: The Hidden Economics of Enterprise Transformation was produced by PMC and Retail Economics. It draws on a survey of 100 senior decision makers across UK retail, FMCG and hospitality, all representing businesses with annual turnover of at least £100 million.