Eelko Lommers

AI has the potential to improve productivity, customer experience, and employee effectiveness, but success depends on applying it thoughtfully. Rather than deploying AI everywhere, organisations should focus on high value use cases, establish clear governance, and recognise that specialist expertise remains critical to delivering quality outcomes at scale.

• Establish the governance, guardrails, and accountability needed to ensure AI is deployed responsibly, consistently, and in ways that build customer trust.

• Identify where AI can improve employee experience and CX quality by reducing repetitive tasks, streamlining workflows, and accelerating access to insights and knowledge.

• Set realistic expectations around AI adoption by balancing investment, operating costs, and the specialist expertise required to achieve sustainable business value

Retailers have access to more customer data than ever before, but determining which insights genuinely help understand customer needs and deliver relevant personalised experiences remains a challenge. By defining what data CX teams should use, how permission is earned, and what value customers receive in return, retailers can create more meaningful customer interactions while maintaining privacy, trust, and long-term loyalty.

• What customer data is genuinely needed to understand customer needs, preferences and intent?

• How can retailers balance customers' growing expectations for personalised experiences with increasing concerns around privacy and data usage?

• Where should retailers draw the line between useful personalisation and interactions that feel intrusive, unexpected or difficult to explain?