By Aneesh Dhawan, Co-Founder and CEO, Knit
There’s no denying it – the research industry is in the midst of a transformation.
Insights teams are being asked to deliver more and do it faster, all while working with fewer resources. Naturally, AI has become the technology of the moment. Many of us have already experimented with it – perhaps in our personal lives, perhaps in our research workflows. And we’ve all felt the same thing: Wow. This is powerful.
But here’s the truth we risk losing in the noise: AI alone doesn’t create change.
It can’t connect the dots in ways that matter to a brand.
It can’t craft the kind of narrative that moves an executive to take a bold bet.
It can’t deliver the nuance that makes a recommendation both credible and actionable.
Researchers do that.
At Knit, we’ve believed in AI since before it was trendy – launching one of the first AI-native research platforms in 2022. But our conviction has never been that AI will replace researchers. Instead, we believe the most exciting future is one where human expertise is amplified, not automated away.
That’s the future we call Researcher-Driven AI – and I believe it’s the model that will define the next decade of insights work.
What Researcher-Driven AI Means
Researcher-Driven AI is a partnership model between human researchers and intelligent AI agents – one where the human stays in the driver’s seat.
Here’s how it works:
- You set the goals, methodology and context.
- AI handles the heavy lifting – organizing data, surfacing patterns, producing first-draft narratives – in minutes, not weeks.
- You then refine, interpret and elevate the output into insights that move the business.
This model doesn’t just optimize for speed. It optimizes for impact – turning research from a periodic deliverable into a constant source of clarity and direction.
Three Shifts Defining the Next Era of Research
1. Human + AI > AI alone
AI can generate something that looks like insight – but without human judgment, it’s often shallow, generic and risky. The real magic happens when researchers guide and refine AI’s work, creating outputs that are both scalable and deeply resonant.
2. Research becomes always-on
Historically, research was saved for the “big moments” because it was expensive and slow. Researcher-Driven AI changes that – making high-quality insight accessible to every function, every week. Insights stop being an episodic input; they become the connective tissue of decision-making.
3. Storytelling becomes the differentiator
As AI takes on more of the synthesis work, the role of researchers shifts toward interpretation and communication. The most valuable researchers will be those who can translate findings into narratives that inspire action across an organization.
Why This Matters Now
The insights industry faces a choice. We can lean into automation in a way that sidelines human expertise, risking relevance and quality. Or we can design our future so that AI serves as a force multiplier for human talent.
At Knit, we’re betting everything on the latter. Our vision is simple:
AI + Human Judgment > AI Alone.
That’s why we’re investing in:
- Embedded human expertise in every project we run.
- Customization so AI reflects your methods, not generic templates.
- Faster paths from data to story so insights aren’t just timely – they’re transformative.
- Global scalability with local context so research resonates anywhere it’s applied.
The Call to the Industry
If we get this right, research will evolve from being a reactive function to a proactive force – one that is always on, always connected and always driving change.
The question isn’t whether AI will change research. It already has.
The question is: Will we let it replace our craft, or will we use it to elevate it?
I know where I stand.