2027 AI Research Ideas: What Businesses, Employees and Customers Really Think

Ask a business leader, an employee and a customer about AI, and you may be having three different conversations.

The leader might be thinking about investment. The employee may be considering a task they need to finish this afternoon. The customer could simply want an accurate answer and a way to reach someone when the situation becomes complicated.

That is why I would avoid building a 2027 AI study around one broad question about whether people feel positive or negative. There are more useful things to learn once we define the experience behind the opinion.

Choose the decision before the audience

Start with what your organization needs to understand. Are you considering a product feature, an internal rollout, a customer communication or an industry report?

Each objective points toward different participants. A study about budget approval needs people involved in that decision. A study about how work gets done needs people doing the work. Customers can describe their own service experiences, but they cannot reliably explain the organization's internal implementation.

Our B2B market research defines professional audiences around responsibilities and relevant experience. That is particularly helpful when a label such as AI decision maker could include very different roles.

Ask businesses about the choices in front of them

For business leaders, I would explore how proposed AI uses are evaluated. What problem needs solving? What evidence would justify proceeding? Who participates in approval, and what could delay a decision?

Make the question specific enough to answer. Evaluating a tool that drafts internal documents is different from evaluating a system involved in sensitive customer decisions.

This research path can reveal the criteria an organization uses, the information it still needs and where stakeholders disagree. It should allow participants to say that a proposed use is not a current priority.

Ask employees about tasks and support

Employees can help explain where AI fits into everyday work. Ask which tasks they perform, what tools they are permitted to use and where they need guidance.

Include people who do not use AI. They may lack access, see little relevance to their role or be uncertain about policy. Those explanations have different implications, so the questionnaire should give each a fair opportunity to emerge.

I would also explore how employees check outputs and what happens when they need help. A question about confidence becomes more informative when it is connected to a particular responsibility.

Ask customers about a recognizable situation

Customers should not need technical expertise to participate. Describe a concrete interaction in plain language, such as receiving help with an account question or getting a product recommendation.

Then ask what they would want to know, what they would be comfortable sharing and when they would prefer another route. Keep the description balanced. A scenario promising instant, flawless help will tell you little about a real choice.

If the scenario is hypothetical, report the finding as a stated preference. It is not evidence that people have already behaved that way.

I'm interested in where the AI conversation changes depending on who is answering. A leader approving the investment and an employee expected to use the tool may have very different questions. I want to hear both.

Bring perspectives together carefully

Comparing groups can be extremely valuable when they answer a genuinely shared question. Leaders and employees could both assess the clarity of organizational guidance, for example, using wording suited to their roles.

The comparison does not require asking everyone an identical questionnaire. It requires clear definitions, compatible measures and enough participants for the planned analysis. Our research methodology provides context for those decisions.

An AI study intended for public discussion also needs a communications plan. Our PR survey research connects the audience question to findings a PR team can explain and share.

For 2027, I would choose one question worth investigating rather than try to explain the entire AI market in one survey. If your team has several possible directions, let's discuss the decision behind them. That conversation is where a useful study begins.

About the author

Andrew Edwards is the founder and CEO of CITE Research. His background includes survey research at Nielsen and public relations at Edelman. He helps organizations use original research for business decisions, PR, marketing and thought leadership.