Consumer expectations have changed dramatically in recent years. What are the most important developments you’re seeing, and how are businesses adapting?

Lisa Jaeger: What we’re seeing is a shift in the way customers engage, with brands, with platforms, with choices. The bar is unquestionably higher. Today’s consumers expect brands to understand their values and make every interaction intuitive. They’re more informed than ever before and won’t hesitate to take their business elsewhere after just one disappointing experience. What this means for companies is clear: waiting to react is no longer an option. The most responsive companies are using real-time data to track emerging preferences – sustainability, personalization, flexibility – and recalibrating their operations accordingly.

Ellen Kan: I see two major factors at work. First, value alignment. People want to feel that the businesses they choose share their commitments. Second, immediacy. They expect relevant offers and support exactly when they need it. Together, these forces create high stakes for businesses, requiring responsive processes underpinned by robust analytical tools.

Jaeger: And I’d add a mindset dimension. It’s no longer enough to collect feedback after a launch or campaign. The most forward-looking organizations are shifting toward continuous learning – testing, refining, and adapting in real time based on what they observe. Today’s pace of change means staying static, even briefly, can translate into lost market share. 

AI is often discussed as a way to “see around corners” in the market. In practical terms, how does it empower companies to decode consumer intent before it fully crystallizes?

Jaeger: AI is uniquely capable of detecting subtle patterns within vast data sets like social sentiment, purchase histories, and customer interactions, and translating these signals into actionable forecasts. Unlike traditional analytics, which may flag trends once they’re already underway, AI can surface early indicators. Subtle shifts in search queries or voice-assistant requests can hint at emerging needs, encouraging companies to adjust pricing or promotions proactively.

Kan: In fast-moving consumer goods, this can be transformative. AI-powered segmentation is enabling a shift from broad demographic buckets to dynamic, moment-based cohorts. Imagine an AI model that recognizes when a segment of health-conscious consumers is trending toward plant-based options and then delivers targeted offers based on early signals others might miss. That level of anticipation deepens engagement and drives loyalty.

Jaeger: This proactive capability explains why AI is increasingly integrated not just within analytics but throughout the entire customer experience lifecycle, from personalized marketing and dynamic pricing to tailored recommendations and subscription retention strategies. AI-powered decision engines can rapidly update offers and suggest services, continuously aligning interactions with consumer preferences and strategic business goals.

Implementing AI at scale can be challenging. How can businesses address the most common obstacles?

Kan: The biggest hurdle is a narrow focus on technology rather than transformation. Simply purchasing AI tools without aligning them to clear business objectives often leads to disappointing results. AI only delivers real value when it’s supported by smarter ways of working and the right expertise. Some of the most effective applications emerge when data scientists collaborate across teams, especially with those closest to product categories and customer experience. 

Jaeger: I’d also emphasize data quality. Garbage in, garbage out still holds. Trustworthy AI doesn’t start with the model. It starts with the data. Consistency, clarity, and quality still make the biggest difference.

Kan: Success requires leaders who champion experimentation, tolerate failure, and build a culture that continuously improves based on AI insights. In organizations where this mindset takes hold, performance improvements tend to last longer and scale more successfully.