Better packaging decisions begin with understanding what consumers recognise, what they need and what will give them a reason to choose. This was a theme I took away from our Building Distinctive Brands event on 24 September at The Goldsmiths’ Centre in London, where we brought together senior leaders from Brand, Insights and Innovation to explore how AI can strengthen teams and help established brands evolve.
We were joined by Suprio Banerjee from Unilever and Jonathan Oakeley and Elle Atton from PepsiCo. The afternoon explored two questions facing many CPG businesses: how can we make the most of AI while maintaining independent thinking, and how can we modernise familiar brands without weakening the equity that makes them distinctive?
Suprio highlighted a paradox that is relevant to how we use AI. Activities that once took weeks can now happen almost instantly, raising the quality of work available to everyone. Yet when organisations draw on similar models, information and best practices, their thinking can also become more alike. As the standard improves, producing something better than yesterday’s average becomes a less reliable source of competitive advantage.
Jonathan offered a complementary perspective: across the industry, access to similar AI tools and inputs will not, on its own, determine competitive advantage. Organisations will continue to differentiate through how effectively they interpret ideas, make choices and translate both the efficiencies gained through using AI and promising thinking into action.
For me, both perspectives reinforce the importance of human judgement. AI can gather information and accelerate initial analysis, but we must determine what the findings mean for the business and which opportunities deserve investment. We also need to recognise where a model performs well and where its answers are unreliable. A confident answer should never become a substitute for evidence.
Jonathan’s experience embedding new capabilities highlighted the importance of making adoption practical. Giving teams access to AI does not automatically transform how they work. Learning appropriate guardrails and trusted information all matter, alongside processes that enable teams to apply new capabilities effectively and responsibly.
Another useful point was how we can use AI to challenge ideas. Jonathan described its value as a sparring partner: asking it to argue against a proposal or identify where it might fail can expose assumptions and prompt deeper thought. Suprio’s approach to perspective-based creativity similarly involves seeking specific expert or unconventional viewpoints, helping teams explore beyond the most predictable answer.
The discussion also raised a longer-term question: how will the next generation develop judgement if AI takes over the work through which previous generations learned? Jonathan’s mountain-climbing analogy captured the challenge. Reaching the summit by helicopter does not build the experience gained on the climb. Simulation may offer opportunities to practise decisions, but Suprio questioned whether it can fully replicate learning through doing real work. It is a question we need to keep in mind as we adopt faster tools.
Elle brought these themes into the challenge of evolving Walkers. A redesign of an iconic brand begins with a clear commercial purpose and an understanding of the assets consumers already remember. Marketing, Insights, Design, Commercialisation and Packaging all have a role in shaping the brief and ensuring that change supports the brand’s growth ambitions.
One practical example was asking people to draw the pack from memory. This helps reveal the logos, colours and shapes that have become embedded in consumers’ minds. For me, it is a useful reminder that the starting point for a redesign should include understanding what already works. Those assets provide a foundation for development, helping the brand retain recognition as it evolves.
Elle described three stages in the design process: Inspire, Narrow and Optimise. Early consumer understanding feeds the brief; exploration then identifies what works across different routes; final validation assesses the strongest designs against the current pack and clear action standards. Mocking up designs on shelf early can also identify problems before substantial testing investment.
Her perspective on AI was grounded in the decision being made. AI can help organise information, identify themes and stimulate ideas, but consumer understanding and decision-making still require human judgement and interaction with real consumers. Final validation needs to capture how people respond in the relevant shelf and choice context. She also highlighted the need to avoid exaggerating small differences in results and focus recommendations on what materially affects the decision. Learning should continue after launch, including how materials and different retail environments influence the pack’s reception.
My colleague Paul Markovic, Behaviorally’s VP of Behavioral Qualitative, extended this thinking by showing how earlier qualitative learning can sharpen design direction. His starting point was practical: what should the pack make easier to find, understand, trust or use? The answer helps establish which recognised cues to protect and which aspects of the experience to improve.
Paul illustrated how AI can organise consumer reviews to distinguish a product issue from an expectation gap that packaging might address. He also explored semiotics: the visual language through which packaging signals meanings such as efficacy, purity, authenticity or self-expression. Changing those cues can change the promise consumers perceive, so interpretation needs to inform the design brief.
Across this process, qualitative researchers observe choices, probe motivations and follow unexpected responses. AI can help prepare focused areas of exploration, summarise learning and make potential design directions tangible. Human understanding and creative expertise guide what happens next.
I came away from the afternoon with a clear priority: make packaging change purposeful. Protect the assets that help consumers recognise a brand, use evidence to identify what could work harder, and apply AI where it improves exploration and learning. As we use these tools, our role remains to challenge the output, understand the consumer and turn insight into a distinctive brand experience.
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