From AI hype to human-centered insight and organizational readiness
Editor’s note: Kate Woodward is COO of Sharpr, a knowledge management platform based in Chicago. She joined the company as employee nine and has spent over a decade at the intersection of SaaS operations and the insights industry. Find her on LinkedIn.
"Raise your hand if you think AI is going to replace you."
And reader? Not a single hand went up.
I was in the audience at a Quirk's Chicago session when a presenter posed that question and I've been thinking about it ever since. Not because the answer surprised me. It didn't. But because of what it reveals about where this industry is and where it's heading.
AI and insights: Three years, three phases
If you've attended Quirk's since OpenAI and ChatGPT rocked our world in November 2022, the shift is hard to miss. In 2023, generative AI was the story. Every session, every vendor booth, every hallway conversation orbited it. Even if in some cases it felt slapped on after just to meet the moment!
In 2026, the conversation has matured. AI is still everywhere, but it's no longer the headline – maybe the sub-header. It's being woven into workflows, products and platforms. The message across sessions this year was notably consistent: AI makes researchers faster and more productive, but human judgment is still what makes insights meaningful. I believe that and I think the researchers in that room believe it too!
But by 2029? My prediction is that AI likely won't have its own track at this conference. It will be infrastructure. Invisible, load-bearing, expected. Like broadband. Like mobile. The "sent from my iPhone" footer used to signal something. Now it just means you have a phone.
When a technology stops being the story, something else has to be.
What becomes the differentiator?
After Quirk’s, we ran an informal LinkedIn poll to our followers: If AI is table stakes, what's the actual differentiator? The vast majority said, "the human layer" – judgment, synthesis, storytelling, the things that require understanding context and stakes. A smaller group said trust and provenance: knowing where the information came from and whether you can rely on it.
The researchers in those session rooms are doing genuinely good work. But in too many organizations, that work lives in inboxes, hard drives and individual memories. It's brilliant … and it's invisible. When the researcher isn't in the room, the knowledge isn't either.
That's the gap AI is actually exposing. The question is no longer: “Will a machine do your job?” It is now: "Is your organization set up to use what your research team already knows?"
This isn't hypothetical. As many of you probably read, in March 2026, Anthropic published labor market research showing that market research analysts rank among the most AI-exposed occupations in the U.S. economy, at 64.8% observed exposure. That's not a future risk. That's based on how AI is being used right now. (Source: Anthropic, "Labor Market Impacts of AI," March 2026.)
The organizations that come out of this well won't necessarily be the ones with the most sophisticated AI tools. They'll be the ones where knowledge is organized, findable and actively working for the business (not locked inside individuals).
The question the industry needs to sit with
Nobody raised their hand in that session because it's a loaded question in a room full of peers. I get it, no one wants to admit that they might be replaceable! But the more interesting version of that question isn't really about replacement, it's about readiness.
If the best researcher on your team left tomorrow, would the knowledge they've built stay? Would anyone know where to find it? Would the knowledge base keep on working for your business?
For most organizations, the honest answer is no. And by 2029, when AI is infrastructure and the tools are table stakes, that organizational readiness, not the technology itself, will be the actual differentiator.
AI is making that gap more visible. By the time it becomes infrastructure, the organizations that treated knowledge management as an afterthought will feel it acutely. The ones that built the systems to capture and use what their teams know will be positioned to use AI as a genuine multiplier, not just a productivity tool. That's the arc I was watching at Quirk's this year. And it's the one I think will define the next few years for this industry.