How AI is changing the roles and required skills of researchers

AI isn’t going to take your job — but it is changing your day-to-day responsibilities. Technology is advancing rapidly, and expectations on research and product teams are following suit. Fortunately, AI-powered tools can help you do your job faster and more efficiently.

Over the past year, the Marvin team chatted with some of our favorite research leaders about how they’re rolling AI into their workflows.

Here are a few skills we identified to help you scale your impact in the new year.  

Delegation

Tasks that used to take hours, like transcribing interviews, taking notes, and gathering quotes, can now be done in minutes with AI. Start delegating tedious or time-consuming tasks to AI so you can focus on strategic, high-priority work.

Susana La Luz-Hawkins, Senior Director of Research Enablement at Best Buy, recommended using AI to automate the first pass of repetitive tasks. “It allows us to check the work a lot easier,” she said. “AI can speed up those individual steps rather than replace the entirety of the process.”

AI can also help structure files, identify key findings, and analyze large amounts of data. If you’re looking for a tool to identify common themes, Marvin’s Deep Research automatically analyzes unstructured files to generate cited reports and insights.

Strategic thinking and planning

Use the time you save for work that needs human creativity and empathy, like interviews, analysis, and stakeholder storytelling. Use your creative and problem-solving skills to get ahead of issues and get involved earlier in the product development process. With this foresight, you can provide guidance that informs the product roadmap.

Partner with your product, design, and engineering partners to find the through line between business objectives and user goals and pain points. Align your research initiatives directly to the organization’s goals for the year and start gathering KPIs that can be tied directly to them.

Collaboration

You can also scale your impact throughout the organization by collaborating with more teams. “AI empowers researchers to grow their reach and multiply their efforts,” said Daniel Gottlieb, Head of Research Operations at Microsoft’s CoreAI, in Scaling Research Without Losing Its Soul. “You're taking the impact of a researcher and multiplying it because you're making it easier to get the right tools, get your customers, and do the research.”

The more teams you help, the more visible the research team is — and the more advocates you have throughout the organization.‍

Leadership and education

As the industry shifts, demand for customer insights is growing. Luckily, AI makes research accessible for everyone in your organization. Research repositories with integrated AI tools, like Marvin, let you share research findings and customer feedback with stakeholders and other non-researchers. These team members can self-serve existing insights, which significantly reduces the workload of researchers.

You can also take it a step further and help non-research team members conduct their own research. Start with low-stakes projects, so you can focus on more strategic, high-priority work. Create templates and training materials to teach others how to use AI to help with research and do some basic analysis.

“It lightens the load of really intelligent humans that have expertise in research so they can focus on things that are more complex and strategic,” Susana said.

She also advised leveraging AI to simplify the process with training, guidance through the templates, or analysis. This way, “the researcher’s only role is assessing the work itself.”

Teaching non-research team members how to get involved makes gathering customer feedback a regular part of their process. And more demand for customer insights can mean more time and resources for the research team.

‍Analytical and technical skills

Involving others is beneficial, but it can run the risk of errors. As a trained research professional, it’s critical to flex your technical skills and own the translation of these insights. You’re the expert in the room; it’s up to you to make sure there are guardrails in place.

When enabling other teams to do research, Susana incorporates specific milestones and checkpoints to ensure the research and analysis are on track. Make sure the information gathered from the research is understood and acted upon correctly. Always contextualize research results for the team and validate findings to avoid hallucinations and biases, especially with AI-generated insights.

“We can train AI well, but at the end of the day, judgment calls are the sole realm of humans,” Susanna said.

‍Governance

You should also use this opportunity to develop ethical use frameworks and policies for responsible AI usage and distribute it throughout the team. As the expert, it’s your responsibility to make sure everyone participating in user research is aware of, and adhering to, these policies. As technology continues to advance, continue refining these guidelines and experimenting, innovating, and sharing as you go.

Want to learn how to use AI to scale your impact? Download our report, The Modern Research Workflow.