Invisible Technologies buying intent
42 tracked signals — top 15 topics below — Engineering and Sales are carrying most of it.
Attention by team
taxonomy_intent_rollup × social_profile.roleEvery tracked signal from a Invisible Technologies employee, placed by the team they sit in and the theme they engaged with. Darker means more concentrated attention.
Topics being researched
30-day windowAll tracked topics, ranked by signal volume. Confidence is the classifier's certainty that the signal belongs to this topic.
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Need intent for a specific topic or industry?
We track the full taxonomy across every account in the graph — including themes not shown on this page.
Who to contact at Invisible Technologies
verified title on filePeople at Invisible Technologies whose own activity produced these signals. Names are withheld pending a consent decision; titles, seniority and topic are real and free to browse.
See everyone, not just the first 10
11 people across every department at Invisible Technologies, plus a LinkedIn profile link for each.
Top accounts researching Invisible Technologies
names withheld on the public pageCompanies whose people mention Invisible Technologies in their own activity. Account names are withheld here; not yet classified as implementation partner vs. genuine prospective buyer.
No buyer signal yet for this account
Nobody in the graph is currently discussing this company by name in a way we can attribute to a specific employer.
Buyer profile
company size · seniorityHow big those accounts are, and who inside them is senior enough to matter. Competitor products still not yet computed for this account.
What's been said
public posts mentioning Invisible TechnologiesReal public activity that surfaced Invisible Technologies in a tracked topic. Not a sentiment score — just what people actually wrote.
There's a growing body of research suggesting current enterprise AI usage is actually not improving organizational productivity. If you don't redesign the way work is done, and you just treat AI as a tool rollout into your current process, then everyone produces more work but there is no organization-wide improvement in time or productivity.... The data is worth understanding, and this is the problem sitting on the desk of every CEO, COO, Chief AI Officer, and CTO right now. 𝗧𝗵𝗲 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵: (i) An NBER study surveying 6,000 Executives across thousands of firms found that 80%+ reported no measurable productivity impact from AI over the past three years. At the individual level, workers saved roughly 3% of their time on average, an improvement level that suggests helpful assistance but not transformation.... (ii) An Upwork survey of 2,500 workers found that 77% said AI tools decreased their productivity or increased their workload. 39% cited time spent reviewing or fixing AI outputs. 23% cited time learning the tools. (iii) An 8-month study from UC Berkeley Haas tracked 200 employees at a tech company. The finding: "AI doesn't reduce work. It intensifies it." Task expansion, blurred boundaries between work and non-work, and more multitasking. Workers did more, but didn't feel less busy. 𝗧𝗵𝗲 𝗽𝗮𝗿𝗮𝗱𝗼𝘅: AI improves capability at the individual level. But it hasn't translated into firm-level productivity gains. Why? Because organizations haven't redesigned workflows, incentives, or job structures around it. AI gets layered on top of broken processes (especially in complex environments like healthcare), and then leaders wonder why it isn't delivering ROI. And it's not just a tech decision. The ROI case has to be built for finance and procurement. The operational case has to be built for the business. When those aren't aligned, even well-deployed AI stalls. 𝗧𝗵𝗲 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: This research isn't an argument against AI. It's an argument for treating AI adoption as an operating model change, not a tool rollout. The technology is ready. Most organizations aren't. The companies doing the redesign work now will be the ones that pull ahead. If your team is in this situation, this is exactly the problem we solve at Invisible Technologies , as we focus on transforming processes and infrastructure and making AI work.