Imagine being responsible for making sure market intelligence reaches the right decision-maker before a call gets made without it, at a global technology company that manufactures, delivers services, and funds serious R&D all at once. Now imagine doing it with a team of two. For years, that’s held up. It just doesn’t scale.
That’s the team the company’s Head of Information Management runs. Her group doesn’t produce research. It makes sure the research that already exists, inside the company and from partners like IDC, gets used. “We try and make information available and findable as easily and quickly as possible,” she said, “so that if somebody’s in a meeting, they can get to it quickly, or they can come to us and we can get to it quickly.”
Two people can stay close to maybe the top few hundred decision-makers in a company of that size. But everyone else is on their own. That is exactly the gap the company is trying to close with AI and tools like IDC Quanta.
A decade of using IDC to pressure-test decisions, not just source data
Long before AI entered the picture, one of the company’s regional strategy teams built a standing cadence with IDC analysts: a call every six weeks, with her team submitting the questions two days ahead so IDC could weigh in before the conversation even started.
That extra step mattered more than it sounds. “A lot of times what would come back is, ‘No, that’s not the questions you should be asking,'” she said. Her team would come in wanting data on one topic; the analysts would redirect them to a different one entirely. On numbers the company couldn’t break out itself, IDC analysts walked through the reasoning behind a breakdown, stress-tested the logic with the team, and told them plainly when their assumptions didn’t hold up.
It’s a pattern that shows up across the company’s engagement with IDC. The relationship delivers a second opinion sharp enough to change the question being asked, well beyond data on demand.
That’s the foundation IDC Quanta had to build on, and, as the company has found, a foundation that turns out to matter a lot once AI tools start competing for the same job.
The real cost of AI answers nobody can verify
As general AI tools spread across the organization, a new problem showed up alongside the old one: getting an answer got faster, but trusting it got slower. When a leader asks for information on a topic, her team has watched colleagues turn to whatever open AI tool is on hand, then come back with a case to make.
“I have to waste time going in and looking at who the analyst is, where they work, who they work for, is it a credible firm,” she said. “I can’t just say no, it’s not credible. I have to explain why.” In one recent instance, the firm behind numbers a colleague had pulled couldn’t even spell the company’s own name correctly.
For her, that verification tax, the time spent fact-checking an AI’s sources instead of using its answer, is the exact problem IDC Quanta removes. Because IDC Quanta’s answers are drawn from IDC’s own verified research and cite the report behind every response, her team no longer has to relitigate credibility before anyone can act on what it says.
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That’s where firms like IDC will really excel, being able to leverage the credibility you already have, so people don’t have to question whether they can trust the number.
The other detail that stood out to her: what IDC Quanta does when the answer isn’t fully available. Where some AI research tools simply decline to answer a question outside a client’s subscription, IDC Quanta tells her what it can share and names the specific reports that would close the gap. “That to me is so much more helpful,” she said. “If we’re working on a key strategic topic, well then let’s buy those two reports, and use IDC Quanta to keep pulling the data out from there.”
A partner, not just a provider
The company sees AI extending its analyst relationships further than two people could ever reach on their own. When the company rolled out AI internally, the number of questions landing on her personally dropped by half, because AI could get people most of the way to an answer without waiting on her team. She expects IDC Quanta to do the same for her own workflow: fewer questions she has to chase down herself, and more time for the harder problems that still need her judgment.
What she’s watching for next is smaller and more practical: a tool that can recognize an outdated chart she drops in and pull the updated version automatically, so she spends less time hunting for the right version and more time using what she already knows is true.
For her, that’s the real value of the relationship. “I think that’s what you need to be,” she said. “A partner, and not just a provider.”
