Research Reinvented: Forrester on why researchers won’t be replaced by AI

This is the last article in our five-part series based on the webinar we hosted with Forrester and Quadrant Strategies, Research Reinvented: How to Master GenAI and Ensure You’re Not Left Behind. This post focuses on why researchers will remain essential, with AI as a collaborator.

The fear in the room

Go to any research conference right now and you’ll probably hear someone half-jokingly refer to whether AI will replace them. The expo halls are lined with “AI-powered everything,” and the message is hard to miss.

Robin Lindberg of Quadrant Strategies put the concern on the table during our webinar:

“An immediate worry… is my task or my role going to be replaced by AI? We’re not there, and I don’t think we’re going to get there either. What I do think is that you will be left behind if you don’t utilize it.”

That’s the key distinction. AI is here to change the way the work gets done. You still have important – human – work to do. 

Lessons from search engines

Robin drew a useful parallel. When Google launched in the late ’90s, people worried that instant access to information would make certain roles obsolete. Decades later, search is still evolving, and humans are still needed to frame questions, interpret results, and decide what to do with them.

AI is following the same pattern. It’s powerful and constantly improving, but it depends on people who know how to ask the right questions, validate outputs, and translate results into action.

Where humans add irreplaceable value

AI is built for repetition, speed, and scale. It excels at:

• Coding transcripts.
  Generating baseline summaries.
• Handling manual data work.
  

But it can’t replicate human judgment. People bring the skills AI can’t touch:

• Defining the right research questions.
• Reading cultural and emotional nuance.
• Turning insights into strategies that move organizations.

As Robin put it: “Save your brainpower for the most vital tasks. Is it copy-pasting? Probably not. Is it the higher-level objectives of the project? Yes.”

Why adopting AI matters for your career

If replacement isn’t the threat, irrelevance is. Clients now expect AI strategies. Stakeholders expect faster cycles. Organizations are building AI into workflows.

Here’s the upside: embracing AI can make roles more rewarding. Quadrant found that automating repetitive work didn’t just speed projects up. It also reduced burnout. Teams stayed more engaged when they spent time on thinking, not tedium.

Forrester’s perspective: strategy over shortcuts

Rowan Curran, Principal Analyst at Forrester, cautioned leaders against using AI as a blunt instrument for cost-cutting. Some companies tried replacing people outright and quickly walked those decisions back. Short-term savings came at the expense of long-term value.

The smarter move? Use efficiency gains to fund growth, whether that’s expanding research, trying new methods, or delivering more impact.

“The AI tools themselves make work easier, but they still need human operators. What matters is how organizations apply the gains, whether they reinvest them to make the work better, or simply cut headcount.” — Rowan Curran, Forrester

Beyond the feature list: choosing tools wisely

Another challenge is the flood of tools in the market. Go to an industry event and you’ll see dozens of platforms, all claiming to be the “AI solution.”

Robin’s advice: start with your process, not the product list. Map how your team works today: where the bottlenecks are, where time is lost. Then look for tools that address those pain points.

“Don’t look at what’s available first. Look at your process. Where do you spend the most time? That’s where you’ll get the most value from AI.” — Robin Lindberg, Quadrant Strategies

And if you can consolidate multiple tools into one platform? All the better. Less training, less friction, and more consistent results.

Rowan added that the most successful organizations take a platform-based approach. They may use point solutions, but they prioritize tools that integrate with their broader ecosystem. That flexibility lets them experiment without painting themselves into a corner.

The Discuss perspective

At Discuss, we see this play out daily. Thanks to AI, researchers are being freed. Freed from hours of setup, freed from transcript drudgery, freed from hunting for insights.

That’s why we’ve built agents to handle the repetitive work and leave the meaning-making to humans:

• Project Agent trims hours off setup by drafting guides and helping recruit participants.
• Interview Agent scales conversations with AI-moderated sessions that probe naturally but allow researchers to step in where nuance is needed.
• Insights Agent takes transcripts and delivers themes, reels, and quotable moments in minutes.
  

These tools protect the role of researchers by giving them back the time to think strategically and tell the human stories that AI can’t.

Wrapping up this blog series

Over five posts, we’ve followed AI’s impact on research:

1. Defining the agentic revolution.
2. The two types of agents that matter most.
3. How AI has already transformed research.
4. Scaling qual globally without losing empathy.
5. Why researchers won’t be replaced by AI.
   

The message is clear: AI expands what’s possible, but human understanding still guides the work.

Your next step

Want to hear Rowan and Robin’s full take on why researchers aren’t being replaced, but why they must adapt? Watch the webinar recording.

This is the last post in our “Research Reinvented” series with Forrester. Read the full series to learn how to scale qualitative research with AI while preserving human understanding.