High Tech, High Touch: Why the Future of Insights Will Be AI and Human

“The more high technology around us, the more the need for human touch. High Tech / High Touch.”

That observation comes not from a contemporary observer, but from futurist John Naisbitt, writing in his worldwide bestseller Megatrends, published in 1982. Naisbitt’s argument was simple yet prescient: technological acceleration does not eliminate the human need for connection, judgment, and meaning, but rather it intensifies it.

More than forty years later, this principle offers a remarkably clear lens through which to view the current moment in market research and insights.

Only a year+ ago, much of the conversation in our industry was framed in existential terms. In 2024, the dominant question was whether AI would replace researchers, analysts, and insights professionals altogether. Fast forward to 2025, and the narrative shifted decisively. The conversation was no longer AI versus humans, but AI plus humans.  This is a recognition that technology alone cannot deliver deep insight, trust, or impact.

This rapid evolution in thinking reflects exactly what Naisbitt anticipated: as AI becomes more powerful, more accessible, and more embedded in our workflows, the value of human judgment, context, and responsibility becomes not less, but more.

AI Is Not the Insight. It’s the Infrastructure

Gen AI is rapidly transforming how insights work gets done. It excels at pattern recognition, speed, and scale. AI can process massive datasets, surface relationships humans would perhaps never see, at least in a timely fashion. automating tasks that once consumed weeks or months of effort. From survey design and open-ended coding to synthetic data and automated analysis, the productivity gains are real and accelerating.

But consumer insight, no less business impact, is not the output of an algorithm.

Insight is relevance. It is interpretation. It is knowing what to look for, which findings matter, why they matter, and being able to recommend what should be done next. Insight answers not just what is happening, but what it means for consumers and ultimately for the business.

That leap from information to meaning and being able to influence decision makers to take the recommended action steps requires humans now more than ever.

AI is becoming essential infrastructure for the insights function, much like computing power or data availability before it. Infrastructure enables progress, but it does not create value on its own. Value is created when experienced professionals apply judgment, context, and accountability to what technology produces.

Senior leaders don’t simply want faster answers. They want confidence. They want to understand risk, trade-offs, and implications. They want insight partners who understand their business realities, can challenge assumptions, and can translate analysis into decisions. Those expectations are fundamentally human.

Ironically, as AI takes on more technical and mechanical aspects of the work, the distinctly human dimensions of the insights role become more visible and more valuable.

Augmented Intelligence, Not Artificial Replacement

This perspective was articulated clearly by Vijay Raj, EVP of Consumer & Market Insights at Unilever, in a recent episode of MRII’s Insights & Innovators podcast. Raj framed AI not as a substitute for human intelligence, but as an extension of it:

“I define AI as being augmented intelligence, which is human intelligence, augmented by artificial intelligence. AI will not take away our jobs. If we do not work with AI, then somebody else working with AI will take away our jobs. And while AI can do a lot of things, it cannot do things like empathy with people — understanding people as people in the cultural context in which they live.”

That distinction of augmentation rather than replacement gets to the heart of the matter. AI can reveal patterns, optimize processes, and increase efficiency. But it cannot empathize. It cannot fully grasp cultural nuance. It cannot weigh ethical implications or take responsibility for decisions. Those remain human obligations.

The risk for our industry is not that AI will advance too quickly. The real risk is that we allow AI to define insight too narrowly, namely as output rather than understanding, as efficiency rather than effectiveness.

Why Humans Must Remain in the Loop

If AI is to elevate the insights profession rather than commoditize it, humans must remain intentionally and visibly in the loop—especially in five critical areas:

• Framing the right questions. AI can optimize within a problem, but humans decide which problems are worth solving.
• Ethics and governance. Bias, representativeness, transparency, and consent are not purely technical issues; they are matters of judgment and responsibility.
• Interpretation and synthesis. Correlation is not causation. Signal is not strategy.
• Narrative and influence. Insights only matter if they change minds and behavior, which requires storytelling rooted in empathy, and the ability to influence key stakeholders including those in the c-suite.
• Accountability. Ultimately, people and not algorithms are accountable for decisions and outcomes.

These are the core skills that will be vital to a robust future for our function. They are future-critical capabilities.

The Leadership Mandate Ahead

Naisbitt’s insight has endured because it speaks to a recurring truth: technology does not diminish the human role but rather it clarifies it. Each wave of innovation forces us to decide what we will automate, what we will accelerate, and what we will protect as uniquely human. AI is simply the latest test of that judgment.

The future of insights as a function will be shaped by leaders who deliberately integrate high tech with high touch, thus ensuring that as our methods become faster and more automated, leaving more time for our thinking to become more rigorous and focused on what actions our companies can take that will drive better results.  And to build trusted relationships with clients and stakeholders that help us to drive impact.

These are the vital skills that we need to train our teams to excel in. That means investing not only in tools, but in the human capabilities that give those tools meaning: critical thinking, ethical stewardship, contextual understanding, the ability to translate analysis into confident action, and the building of trusted relationships.

AI will not determine the future of insights, even as it transforms the function.  Rather, leaders  build teams that know when and how best to apply human judgment will.