Issue 6: The New Role AI Insights Firms Will Need to Win and Retain Clients

For years, the insights industry has leaned on technology to cut what are fundamentally people costs. Initially, these costs were operational and process related. The current shift is different. AI is now taking aim at two substantive things we always assumed required humans.

1. Replacing the people who participate in market research
2. Replacing the people who design market research

The assumption is that, trained with specialist knowledge on vast datasets, AI will have the knowledge needed to scale and substitute technology for humans at key points in the value chain. But what happens if that assumption is flawed?

What Do Clients Want from Research?

One piece of advice I give to my advisory clients is that, to paraphrase Clayton Christensen, clients are not “hiring” market research to learn: they are hiring it for reassurance.

In this light, the use of AI for substantive elements of the research process creates new ways in which clients must satisfy themselves that the work they are hiring out will be defensible.

Will synthetic respondents provide “accurate” information? Is an AI research bot "smart” enough to support strategic decision-making? AI does okay with routine tasks, but even talented humans struggle with context and client-specific needs that heavily nuance the usefulness of our work product—and, for now at least, generalized AI struggles with mightily.

These trust issues will first emerge in the sales process. Companies selling to sophisticated clients with complex needs will surely face skepticism early. But let's assume they do and the client buys in. What happens when they have questions about outcomes? What kind of support will they need? What's the role of CS?

Customer Success Can’t Do Both

Historically, CS teams have handled different aspects of execution, like onboarding, technical troubleshooting and operational support. Some even doing the work for the client. They generally do not do more strategic work for an obvious reason.

As I regularly write and tell my clients, combining operational support with more substantive or strategic work in single person or team is a recipe for failure. The skills, time commitments, and expertise required differ too sharply. Operational excellence demands efficiency and responsiveness, while strategic advisory work requires domain expertise, client-specific understanding, and nuanced interpretation. Operational work is time-bound. Strategic work is generally not.

How then will firms support clients with substantive questions?

A New Kind of Researcher

I am convinced there will still be a place for CS in firms with AI products that is very much focused on the operational work needed to ensure the product delivers on its promise. I expect this role will shrink over time as AI capabilities grow, too.

A new role has to emerge, though, to advise clients. These new advisor-strategists will be people with two skill sets. One will be applied AI, meaning that they will understand how AI agents and models produce outputs so that they can advise clients on how to use data and training to maximize the relevance and usefulness of the output. The other, naturally, will be domain specific, so they know which data to use and which outcomes are important.

We can expect these people to become critical to a firm’s GTM as well, as their knowledge can be used to create mid-funnel buyer- and sales-enablement materials. This also implies that the firm has clearly defining Ideal Customer Profiles (ICP). Clients with complex strategic needs will benefit from a sales-led conversation around trust and credibility, whereas other clients may not need (or be able to afford) the same handholding. These advisor-strategists will help build brand equity and close and retain business, and will thus become a competitive advantage.

Now What?

If yours is a business that is increasingly leaning on AI, consider how you deploy resources to help customers down the funnel and maximize usage. Your Customer Success teams will continue to address operational issues, as they always have. But you will need to build a new kind of asset, namely people who, by knitting together AI and strategic competence, can give what clients really want: confidence that they are making good decisions.