AI Speeds Up Market Research, but Human Insight Still Wins the Day

As artificial intelligence continues to redefine marketing, MarketCast Co-President Amy Fenton believes that the future of market research lies in speed, precision and balance. In a conversation with Jon Watts, managing director of the Coalition for Innovative Media Measurement (CIMM), Fenton detailed how her team is implementing AI across its research ecosystem while preserving the human instinct that keeps campaigns authentic and effective.

For marketing leaders, Fenton’s experience offers a model for modernizing insight delivery without compromising the strategic thinking that underpins strong brands.

AI as an Accelerator, Not a Replacement

“We’re embracing AI in a big way, especially across ad effectiveness and market measurement,” Fenton said. “The goal is to help our clients keep up with the rapid pace of change by delivering predictive insights and enabling faster decision-making.”

Rather than seeing AI as a threat to creative roles or brand strategy, Fenton views it as a tool to increase velocity and clarity. MarketCast uses large language models trained on human data to predict how ads will perform before they ever go live. This means marketers can course-correct or double down with speed and confidence.

Yet, she emphasized, AI is an enabler and not a substitute for human judgment. Even the most advanced models rely on the experience, empathy and contextual understanding of seasoned professionals. It’s a reminder that AI should be integrated to enhance the marketer’s instinct.

Precision Requires Purposeful Integration

When MarketCast began exploring AI applications, the initial impulse was to apply it across all operations. “At first, we wanted to put it everywhere, but that didn’t scale,” Fenton said. “So we took a modular approach, embedding AI where it could create real value, like in brand effect studies or product placement analysis.”

This targeted deployment allowed MarketCast to realize AI’s potential incrementally. Over time, these modules evolved into a more connected ecosystem. For marketers, this illustrates a practical path to AI adoption: begin with focused, measurable use cases, and expand once the impact becomes clear.

Data Depth Is the New Advantage

Fenton pointed to the company’s In-Program Brand Placement (IBP) service as an example of how AI is delivering more detailed insights. “We can detect every brand or product that appears in a show or event, like a PGA tournament with multiple sponsors, and measure the effectiveness of each placement,” she said.

These granular data points help brands not only understand exposure but calculate real return on investment. In fast-moving markets, being able to quantify impact at that level gives marketers an operational edge, particularly when defending spend or reallocating budgets.

Speed Without Compromising Trust

AI’s potential for fast insights comes with a caveat: data integrity must remain uncompromised. “We use AI to detect fraudulent responses in real time, flagging and filtering bad data before it even hits our systems,” Fenton said. “If the data is off, the insights will be too and that can derail an entire campaign.”

That kind of built-in quality control is vital. It reinforces that AI is only as good as the data it analyzes. For communicators, this is a call to prioritize data hygiene alongside innovation.

Readiness Varies and Transformation Takes Time

Not all clients are prepared to act on these faster insights. According to Fenton, there are two stages to the AI transformation journey. “One is speeding up access to existing data. The second is integrating new data types to make smarter decisions. That requires major operational changes,” she said.

Some advertisers, she noted, are planning two- to three-year transformations just to build the infrastructure needed to support more agile, data-driven decision-making. For marketers, this means aligning AI adoption with realistic timelines and organizational capacity.

Human Creativity Still Matters Especially at the Top

One of the most important messages from Fenton’s interview was about the irreplaceable value of human creativity. “There’s pressure to use AI to reduce costs, but authenticity still matters,” she said. “AI can’t replicate human connection, and that connection is what drives ad effectiveness.”

She distinguished between low-risk executions, such as programmatic display ads, where AI can generate dozens of variations efficiently and high-stakes creative, like Super Bowl spots, which require emotional intelligence and cultural sensitivity.

In other words, while AI can help scale the mundane, the most impactful work still requires human authorship. For senior marketing and communications leaders, this means investing both in advanced analytics and in the creative talent who can bring those insights to life.

Call for Industry Standards

Looking ahead, Fenton believes collaboration will be key. “We need shared best practices, especially around data quality, and a shared understanding of how far AI should go in the creative process,” she said.

As a member of CIMM, MarketCast is advocating for ethical, transparent standards that guide how research firms and marketers use AI responsibly. In a world where both innovation and skepticism are rising, such clarity benefits the entire ecosystem.

Conclusion: AI With a Human Core

Fenton’s roadmap is a glimpse into the future of research and a framework for responsible innovation. By adopting AI with clear objectives, prioritizing data integrity and knowing when to lean on human instinct, marketers can move faster without sacrificing strategy.

“At the end of the day,” Fenton said, “authenticity still matters and AI can’t deliver that on its own.”