How to master data & AI to power the next generation of retail

In today’s fast-evolving retail landscape, data and AI are no longer optional – they’re existential. In our recent POV, ‘Five tried and tested operational principles for retail resilience’ we briefly highlighted how AI can enable dynamic decision-making at scale and act as a co-pilot to commercial, supply chain, and store operations teams. AI is not the silver bullet, but it goes beyond traditional analytics by explaining, recommending, and acting in a way that maximises product profitability.

The most forward-thinking retailers are already years ahead, leveraging these technologies to drive efficiency, profitability, and customer satisfaction. They’ve made conscious decisions to master all things data & AI to remain competitive.

But for those whose data & AI strategies aren’t quite as mature, how can they catch up?

Let’s unpack the top use cases for data & AI in retail and learn how to put in place the critical foundations to get there.

Top use cases for data & AI in retail

• AI-powered recommendation engines – Generative AI (Gen AI) can power commercial recommendation engines that automate millions of micro-decisions. These systems optimise product suggestions, pricing, and promotions in real time – boosting conversion rates and customer satisfaction.
• Demand forecasting & inventory optimisation – AI models can predict demand with high accuracy, helping retailers reduce overstock and stockouts. This leads to better inventory turnover, lower costs, and improved customer experience.
• Dynamic pricing – AI can be used to adjust prices dynamically based on demand, competition, and customer behaviour. This ensures competitiveness while protecting margins.
• Customer segmentation & personalisation – Advanced analytics enable hyper-personalized marketing by segmenting customers based on behaviour, preferences, and lifetime value.
• Supply chain optimisation – AI helps streamline logistics, predict disruptions, and optimise delivery routes – making supply chains more resilient and cost-effective.

To get to these levels of sophisticated granularity and speed of response, you need highly automated data, analytics, and execution capabilities.

This means:

• Solid, near real-time data foundations
• As automated as possible data & AI sitting on top of those foundations
• Considerations for where you might use agentic AI for decision-making and execution – for example, solving complex sales and customer service queries or deciding real-time pricing decisions in an online environment – with the right guardrails and human oversight

That’s the end goal. So, how do we get there?

• Improving data literacy and culture across the organisation

First, success in data and AI starts with a top-down belief in its existential importance. Data transformation isn’t just technical – it’s cultural.

Many organisations choose to move in the data foundations direction first before trying to advance their culture and literacy. But one of the characteristics right alongside data foundations is concerted efforts to raise the level of data literacy and confidence and belief in the data.

In our ‘Data-powered enterprises’ research, we found 80% of surveyed data executives in our ‘data masters’ category had defined a strategy to become a data-powered organisation, compared with 61% of others. Also, 81% of data executives in the ‘data masters’ category stated that all business areas in their organisation had a defined data/analytics strategy and roadmap, compared with 64% of others. For example, for a large grocery retailer currently undergoing a data transformation programme, a significant pillar is a dedicated central organisation with 100+ people dedicated to driving data literacy and culture, and data & AI enablement.

Of course, getting to this point requires building trust in data – closing the gulf that often exists between IT and business execs with a combination of data foundations and data literacy and culture. There’s no point spending time and money cleaning your data, building models and tools, then putting them into the hands of end-users and decision-makers who choose not to use them.

Overall, organisations that focus more on behaviours (culture, change management, leadership) and foundations together reap the most benefits.

• Strong end-to-end data & AI strategy framework

Without strong data foundations, AI cannot deliver value at scale, reliably or repeatedly. This strategy framework should include:

• Clean, governed, and secure data
• Fit-for-purpose data architecture
• Scalable data platforms
• Real-time data pipelines

Protecting your data as an asset is crucial. This covers all elements of your data foundations; protecting and securing data with your standards and governance, sufficiently good data quality and master data management processes. It’s implementing the right operating model, establishing structured approaches to data management and making sure that you’ve got modern fit for purpose, data architecture, and technology.

This is a key pillar in any data transformation. We see many of our clients getting stuck in the proof-of-concept (PoC) trap – spending vast amounts of money on ideas that they simply can’t scale. In fact, 75% of data executives surveyed by the Capgemini Research Institute cited large-scale deployment of generative AI PoCs as a major challenge.

Instead, we always recommend a proof-of-value (PoV) to demonstrate  that a solution not only works but also delivers measurable business benefits, such as increased efficiency, cost savings, or improved customer outcomes. Broader than a PoC, this will often include real data, user testing, and performance metrics.

Having good, consistent standard quality data foundations means you’re much more likely to be able to repeatedly and reliably scale more advanced analytics and AI applications that you build on top.

• Building AI models that operate with independence

As customer expectations shift toward seamless, real-time digital experiences, retailers are under increasing pressure to deliver instant, personalised interactions – especially in areas like pricing and promotions. This evolution demands not only robust real-time data infrastructure but also advanced analytics and AI systems capable of making autonomous decisions at scale. After all, when rolling out dynamic pricing for millions of customers, keeping a human in the loop becomes impractical. Impossible, even.

Therefore, you need to design AI models that can operate with a high degree of independence. This requires a carefully architected operating model where automation is governed by clearly defined rules, ethical boundaries, and oversight mechanisms. Strong governance frameworks are essential to ensure that these autonomous systems make decisions that are not only fast and scalable but also aligned with business values and regulatory standards.

Partnering for the AI-powered future of retail

Mastering data and AI is no longer a competitive advantage, it’s a necessity. But getting there requires more than just technology. It demands a cultural shift towards data-centricity, robust data foundations, and the ability to scale transformation across the enterprise. It pays to bring partners on board to help you navigate these complexities.

As your business and technology transformation partner, Capgemini’s team of data & AI and retail experts can bring:

• Deep retail industry expertise – With decades of experience working with global retailers, we understand the nuances of your business and the evolving expectations of your customers.
• Leading data & AI capabilities – From real-time data platforms to advanced AI models and Gen AI applications, we help you unlock value at every stage of your data journey.
• Scaled transformation delivery – We don’t just design strategies – we implement them at scale, embedding change across people, processes, and platforms.

Whether you’re just starting your data journey or looking to scale AI across your enterprise, Capgemini can help you build the foundations, culture, and capabilities to thrive in the AI-powered future of retail.

Get in touch to start that transformation today.