Our retail expert, Zainab Hussain, is an e-commerce strategist with extensive experience in customer engagement and operations management. Today, she joins us to discuss the seismic shift AI is causing in the marketing world. We’ll explore how leaders can move beyond simple automation to create intelligent, human-centered growth systems, break down the organizational silos that hinder progress, and use advanced AI techniques like agentic platforms and synthetic audiences to build deeper, more meaningful customer relationships. This conversation will unpack the practical strategies for re-architecting marketing from the ground up in an AI-driven economy.
Many CMOs are now expected to use AI to connect product, data, and customer experience. What are the biggest organizational shifts required to break down these silos, and what is the first step you recommend for leaders to start this integration?
The most significant shift is moving from a departmental mindset to a connected system mindset. For decades, marketing, product, and technology have operated in their own lanes, with their own goals and metrics. AI doesn’t just automate tasks within those silos; it demands they be torn down. The entire organization wasn’t built for this level of integration, and it’s a challenging, often uncomfortable, change. The first step isn’t technological; it’s cultural. Leaders must bring their cross-functional teams together to create a unified vision for what an AI-powered customer experience looks like for their brand. It’s about establishing a practical, shared operating model that puts empathy and customer value at the core, ensuring everyone is working from the same playbook before a single new platform is implemented.
You’ve noted the risk of AI eroding emotional connection with customers. How do you design an AI-powered system to prioritize human-centered growth over pure efficiency, and what key metrics do you use to measure its success in building lasting relationships?
This is the central challenge. The temptation is to let AI optimize purely for speed and cost, which can make interactions feel sterile and transactional. To counteract this, we design systems where human insight is the starting point for every AI-powered experience. It means growth must feel considered, not just automated. We ensure the AI is trained on data that reflects empathy and nuanced customer understanding, not just purchase history. As for metrics, we move beyond short-term conversion rates. We focus on measuring long-term demand, brand differentiation, and the durability of customer relationships. This could include tracking customer lifetime value, repeat purchase rates, and even sentiment analysis to gauge emotional connection. Success isn’t just a sale; it’s a customer who feels understood and wants to return.
Your work with a major UK supermarket involved developing an Agentic Retail Media Platform. Can you explain how this type of platform moves beyond simple automation to orchestrate brand, commercial, and customer value, and what the impact was on their internal workflows?
An agentic platform is a huge leap from basic automation. Simple automation completes a predefined task, like sending an email. An agentic platform, on the other hand, can reason, plan, and execute complex, multi-step actions to achieve a goal. For the UK supermarket, this meant creating a system that didn’t just place ads but could intelligently orchestrate the entire retail media ecosystem. It could analyze real-time sales data, customer behavior, and brand objectives to make dynamic decisions that balanced commercial goals with a positive customer experience. The impact on their workflows was transformative. It rewired how teams collaborated, breaking down the walls between the commercial, brand, and customer data teams. They could now make faster, more coherent decisions because the platform provided a single, intelligent view of the entire operation.
The concept of using “Synthetic Audiences” to augment traditional research is fascinating. Could you walk us through how that process works in practice and provide a specific example of how it helps a product team bring a new offering to market faster?
Synthetic Audiences are a powerful way to accelerate the insights process. Instead of spending weeks or months on traditional focus groups, we use AI to create highly realistic, simulated consumer profiles based on vast datasets. These “synthetic” consumers can react to new product concepts, messaging, and designs in a simulated environment. For a global brand like Mars, this was a game-changer. Their product team could test dozens of new product variations with these AI-enabled audiences in a fraction of the time. They received immediate, nuanced feedback on everything from packaging to flavor profiles, allowing them to iterate and refine their offering with incredible speed. It doesn’t replace traditional research entirely, but it augments it, helping teams validate ideas and get impactful products to market much faster.
As you expand into North America, you’ll encounter leaders overwhelmed by fragmented AI pilots. What is your advice for creating a single, intelligent operating system, and can you describe the core components of the AI tool suite you built for Reckitt’s marketers?
The feeling of being overwhelmed by fragmented pilots is very common. The key is to stop thinking in terms of individual tools and start thinking about a unified operating model. My advice is to pause the scattered experiments and define a clear, central strategy for how AI will drive growth across the entire marketing lifecycle. For Reckitt, we built an integrated suite of AI tools that functioned as a single system for their 700-plus marketers. The core components covered every stage: AI-powered insights for planning, generative AI for content creation, intelligent commerce tools, and advanced measurement capabilities. By connecting these functions on one platform, we empowered their global teams to drive efficiency and consistency while still adapting to local markets, linking their marketing activities directly to tangible commercial outcomes.
What is your forecast for how AI will re-architect the core functions of marketing by 2026?
By 2026, the conversation will have moved far beyond efficiency. While 2025 was the year brands scrambled to embed AI into existing processes, 2026 will be the year that the next generation of leaders fundamentally re-architects marketing for orchestration. AI won’t just be a tool that assists marketers; it will be the central nervous system connecting insight, creativity, and execution. Consumer journeys will be compressed by AI search and agentic commerce, forcing brands to build systems that can respond with incredible agility and precision. The most successful marketing organizations will be those that have successfully built a single, intelligent platform where teams collaborate seamlessly, making decisions that protect brand differentiation and build genuine, long-term customer demand. It will be less about automating the old way of doing things and more about inventing a new, more intelligent way to grow.
