From Service to Software: How AI is disrupting the $140 billion market research industry

13 August 2025

The market research industry is on the verge of a seismic shift. For decades, it has operated as a slow, expensive, and manual service. Now, a technological catalyst—Generative AI—is set to rewrite the rules. We are witnessing the transformation of a $140 billion industry from a labor-intensive service to a scalable, software-driven model. 

This new era will be defined by three key factors. First, the market is historically fragmented and inefficient, making it a prime candidate for disruption. Second, AI's core capabilities are uniquely suited to the research workflow, unlocking unprecedented speed and scale. Finally, as technology becomes table stakes, the winners will be those who master distribution and build products that deeply embed into customer workflows, a dynamic that is already creating a vibrant M&A landscape.

A Market Ripe for Disruption

The traditional market research industry is a vast and fragmented landscape. The global market stands at $140 billion, yet the top ten firms command less than 30% of it. This leaves over $80 billion serviced by thousands of smaller agencies. This fragmentation exists because barriers to entry are low and client needs are incredibly diverse.

This structure has perpetuated a core problem for enterprises. Commissioning research is notoriously slow and expensive. A single project can take months to complete, limiting its use to only the most critical decisions. While other departments, like product and engineering, have embraced a new generation of software tools for continuous feedback, market research has remained stubbornly immune to this SaaS revolution. This has created a great frontier for software disruption, with billions in service spend ready to be converted.

The Catalyst: AI as a Foundational Shift

Generative AI is uniquely suited to automate the market research workflow. Its native ability to understand language, synthesize text, and identify patterns mirrors the exact tasks of a human researcher. This makes AI a foundational shift, not just an incremental improvement. We are seeing software effectively become labor.

The transformation is unfolding in two waves:

1. Wave 1: Augmentation and Market Expansion. This is the immediate opportunity. AI is making research dramatically faster and cheaper, unlocking new use cases. Tools can now automate everything from generating a discussion guide to moderating interviews and producing a final report in under 24 hours. This democratizes access to insights, allowing companies to move from infrequent, high-stakes projects to a continuous feedback loop.

2. Wave 2: Replacement and Simulation. This is the long-term vision. The next wave involves using AI to create synthetic "digital twin" respondents, potentially replacing human research panels entirely. Early tests are promising, with one study finding that conclusions from synthetic CEOs were 95% the same as those from their real-world counterparts.

This technological shift is creating a new competitive playbook.

The New Playbook: Distribution Over Technology

In an industry where the goal is to find the "truth," the outputs of competing AI platforms will naturally become more similar over time. This means that a pure technological edge will be difficult to sustain. The durable competitive advantage will shift from algorithms to the fundamentals of business execution: distribution and workflow integration.

The companies that win will not necessarily have the most advanced AI. They will be the ones that become most deeply embedded in their customers' operations. Many marketing leaders are comfortable with outputs that are "good enough"—for example, 70% as accurate—if they are delivered faster and at a fraction of the cost. This creates a massive window for agile startups to get into enterprise accounts, prove their value, and expand before incumbents can adapt. The result will likely be a multi-winner market, similar to the fragmented industry of today, where companies differentiate through vertical focus and superior customer service rather than a single technological moat.

The Players: A New Competitive Landscape

The field is currently composed of three main groups: traditional incumbents, software incumbents, and a new wave of AI-native challengers.

• Traditional Incumbents (Kantar, Nielsen, Ipsos): These giants have deep client relationships and domain expertise. However, they are built on service-heavy models and have been slow to innovate. Their primary path to acquiring new technology is through M&A, and they are now actively buying Al capabilities to avoid being left behind.

• Software Incumbents (Qualtrics, SurveyMonkey): These first-generation SaaS platforms made survey-based research more efficient. But they augmented traditional methods rather than replacing them.

• AI-Native Players: This new breed of company is built from the ground up on AI. They are challenging the status quo with products that are faster, cheaper, and more scalable. While many are emerging, a few have gained significant traction, including Bolt Insight, OutsetAI, and ListenLabs.

The Future of Insights is Here

AI is not just changing market research; it is democratizing it. The shift from slow, expensive projects to continuous, automated insight generation is already underway. This has ignited an active M&A landscape, with incumbents and advertising holding companies alike racing to acquire the next generation of tools. WPP is investing $400 million a year in AI, while Publicis has committed €300 million to its own platform. They see these AI-native research tools as mission-critical assets for survival and growth.

For investors, the opportunity is clear. The companies that succeed will be those that combine fit-for-purpose technology with a deep understanding of customer workflows and a robust distribution strategy. The future of market research belongs not to the company with the most complex algorithm, but to the one that makes actionable insights an accessible, indispensable part of daily business decisions.