By: Chris Oatey, Regional Director, 2CV
June, 2026

The biggest risk facing the research industry is not AI. It’s the belief that speed and efficiency alone create value.

At 2CV, we help organisations make better, bolder decisions when it matters most. That means helping clients navigate uncertainty, cut through complexity and understand not just what is happening, but what to do next.

That’s why one finding stood out to me when reading Asia Research’s latest AI in Consumer Insight 2026 report. The research industry may be having the wrong conversation about AI.

Much of the discussion today focuses on speed, efficiency and automation. How quickly can we analyse data? How much can we reduce costs? How many research tasks can be automated? These are important questions. But they are not the most important question.

The real question is: what happens when everyone has access to the same tools?

The Asia Research study shows that AI adoption is now almost universal. Nearly all suppliers (98%) are using AI in some form, while six in ten organisations (including 2CV) now have formal leadership, teams or strategies dedicated to AI development. AI is increasingly embedded across research design, analysis, reporting and quality control. The debate is no longer whether AI belongs in research. That debate has already been settled.

Yet alongside this widespread adoption sits another finding that deserves equal attention. While the industry’s primary perceived benefit remains efficiency and speed (89%), almost every stakeholder surveyed (95%) reported experiencing technical flaws or errors in AI outputs.

For me, this highlights a big misconception about AI in market research today: that AI is the answer to everything, and that good research automatically becomes cheaper, faster and just as effective.

It doesn’t.

AI can undoubtedly accelerate many aspects of research. It can help us process information faster, generate ideas more efficiently and automate previously manual tasks. But speed alone does not create value. Faster answers are only useful if they are the right answers.

In many ways, the challenge facing clients today is not a shortage of information. Businesses are surrounded by more data, more dashboards, more reports and more AI-generated outputs than ever before. In my experience, very few clients struggle because they lack information. More often, they struggle to identify what matters, build alignment around it and translate it into action.

What they increasingly need is clarity. They need help identifying the signal within the noise, understanding what truly matters and determining what action should be taken next.

This is where I believe the role of research is evolving.

Historically, research agencies were often valued for their ability to gather information and generate insights. Increasingly, those capabilities are becoming more accessible through technology. As that happens, the value shifts elsewhere.

The future competitive advantage will not come from producing more charts, more data points or more presentations. It will come from interpretation. From context. From understanding the human behaviours that sit beneath the surface. From connecting findings to commercial decisions. And from helping organisations build alignment and confidence around the actions they take.

In short, the value is moving from insight production to insight leadership.

This shift is likely to create increasing separation within the industry. The report points towards a future where low-cost, AI-enabled insight services continue to grow, while premium, strategically led expertise becomes increasingly valuable.

For many routine business questions, AI-enabled solutions will be entirely appropriate. If organisations can obtain 80% of the answer in a fraction of the time and cost, many will understandably choose that route. However, the remaining 20% is often where the greatest commercial value exists.

It is the nuance that changes a product launch decision. The cultural understanding that prevents a costly mistake. The unexpected behaviour that challenges assumptions. The outlier that reveals a new opportunity. These are precisely the areas where human judgement remains critical.

That does not mean resisting AI. The best researchers of the future will be those who embrace AI and learn how to use it intelligently. As the technology matures, I am optimistic that practitioners across the industry will become more effective, more productive and more capable than ever before.

But there is an important responsibility that comes with that optimism.

Research has always been an apprenticeship profession. That is why one statistic particularly caught my attention. Almost half of stakeholders (44%) expressed concern that junior researchers are shortcutting the fundamentals of research through AI.

As an industry, we have a responsibility to nurture the next generation of talent. Understanding methodology, critical thinking, behavioural science and the principles behind good research remains as important as ever. Technology can accelerate learning, but it cannot replace understanding.

Ultimately, I believe the future belongs neither to agencies that reject AI nor to those that apply it indiscriminately. It belongs to those that understand which problems AI can solve, which still require human judgement and how to combine both in service of better business decisions.

As AI makes insight production increasingly accessible, the real differentiator becomes the ability to transform understanding into action. Not simply delivering information, but helping clients know where to focus, what to prioritise and how to move forward with confidence.

At 2CV, that has always been our focus. Not simply generating answers, but helping clients make sense of complexity, uncover meaningful human understanding and make decisions that create lasting impact.

The agencies that thrive over the next five years will be the ones that apply the right AI tools and methods at the right moments, recognising that not every challenge requires the same solution. In research, as in business, success rarely comes from forcing square pegs into round holes.