AI, Consumers, and the Pursuit of Frictionless Experiences
Last week, I had the opportunity to participate in a Consumer Goods and Services panel as part of an INFORMS event hosted at UIC. It was a thoughtful, practical discussion with leaders who are actively applying data science and AI inside large, complex consumer-facing organizations. I was genuinely pleased to share the stage with this group and to engage with an audience that understands both the promise and the constraints of applied analytics.
The Core Question: Where Does AI Really Add Value?
A central theme of our conversation was not whether AI will matter in consumer goods and services—it already does—but where it should be applied deliberately.
My perspective is simple:
Consumers—and workers—are increasingly seeking frictionless experiences. AI is most powerful when it removes friction that does not add value.
Not all friction is bad. Some friction is intentional: it builds trust, ensures safety, or reinforces brand differentiation. But much of what frustrates consumers and employees alike—manual steps, rework, delays, inconsistencies—adds no value at all. That is where AI can, and should, play a meaningful role.
Frictionless Doesn’t Mean Human-Less
One point I emphasized during the panel is that frictionless does not mean impersonal or fully automated. In consumer goods and services, AI works best when it:
Anticipates needs rather than reacting to complaints
Simplifies choices without eliminating control
Augments employees instead of overwhelming them with tools
Operates quietly in the background, improving consistency and speed
When AI is visible only when it fails, and invisible when it succeeds, it is usually doing the right job.
Implications for Consumer Goods and Services
Across the discussion, several practical implications emerged:
AI should be embedded in workflows, not bolted on as a novelty
Use cases matter more than models—starting with clear consumer or employee pain points is critical
Operational data and behavioral data must work together to create meaningful experiences
Trust and explainability remain essential, especially when AI influences pricing, availability, or recommendations
The organizations making the most progress are not chasing the most advanced algorithms—they are systematically reducing friction at scale.
A Thoughtful Audience, A Timely Conversation
What made this panel especially rewarding was the level of engagement from the audience. The questions reflected a real-world understanding of analytics maturity, organizational change, and the gap between experimentation and impact.
AI in consumer goods and services is moving beyond hype. The next phase is about designing experiences—both for consumers and for the people who serve them—that feel simpler, faster, and more intuitive.
That is where AI earns its keep.
I’m grateful to INFORMS and UIC for hosting the discussion, and to my fellow panelists for a grounded, candid conversation. This is exactly the kind of dialogue the field needs as we move from possibility to practice.
