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Does the value of your insights, analytics, or automated intelligence product sometimes feel invisible to buyers and users? Does your product have impressive analytics and AI technology, but user adoption and sales still are not where you want them to be?
While it has never been easier to build data-driven products, why does it still seem so hard to build indispensable data products that users can't live without—and will gladly pay for?
I’m Brian T. O’Neill, and on Experiencing Data — a Listen Notes top 2% global podcast — I help founders and B2B software product leaders close the Invisible Intelligence Gap through solo episodes and interviews with leaders at the intersection of product management, UX design, analytics, and AI.
If you’re building analytics, BI, or automated intelligence (AI) products, this non-technical show will help you better connect your product to outcomes, value, and the human factors that still matter — even in the age of AI.
Subscribe today on all major platforms or browse the episode archive.
Get 1-Page Episode Summaries:
https://designingforanalytics.com/experiencing-data-podcast/
About the Host, Brian T. O'Neill:
https://designingforanalytics.com/bio/
Does the value of your insights, analytics, or automated intelligence product sometimes feel invisible to buyers and users? Does your product have impressive analytics and AI technology, but user adoption and sales still are not where you want them to be?
While it has never been easier to build data-driven products, why does it still seem so hard to build indispensable data products that users can't live without—and will gladly pay for?
I’m Brian T. O’Neill, and on Experiencing Data — a Listen Notes top 2% global podcast — I help founders and B2B software product leaders close the Invisible Intelligence Gap through solo episodes and interviews with leaders at the intersection of product management, UX design, analytics, and AI.
If you’re building analytics, BI, or automated intelligence (AI) products, this non-technical show will help you better connect your product to outcomes, value, and the human factors that still matter — even in the age of AI.
Subscribe today on all major platforms or browse the episode archive.
Get 1-Page Episode Summaries:
https://designingforanalytics.com/experiencing-data-podcast/
About the Host, Brian T. O'Neill:
https://designingforanalytics.com/bio/
Episodes

Wednesday Mar 04, 2026
189 - The Invisible Intelligence Gap
Wednesday Mar 04, 2026
Wednesday Mar 04, 2026
I’ve worked with a lot of teams building analytics and insights products and decision-support systems. The pattern I keep seeing isn’t that the math is wrong or the ML / AI models are weak. Much of the time, the technology is fine.
The challenge is that all that [not always artificial!] intelligence is not surfacing as value to your customer. Dashboards look impressive. AI features demo well. Pilots get strong reactions. And then… usage stalls. Sales cycles drag. Teams quietly revert to spreadsheets. Buyers, or rather, prospective buyers, say they “like the vision,” but deals don’t move into the “closed” stage.
If your gut tells you the primary blocker is not your sales process, pricing/packaging, procurement, data quality, or risk/compliance, then you may be suffering from what I call the Invisible Intelligence Gap.
Your product’s intelligence simply isn’t visible to them. Three forces tend to amplify this gap. First, the value translation gap, which is when buyers and users can’t easily connect insights to their own goals. Second is the workflow alignment gap resulting from the product not fitting how work actually gets done. Third, the trust and control gap involves users lacking confidence in how the system reaches conclusions. My frameworks like CED, FOWA, and MIRRR are designed to close these gaps by making value obvious, workflows smoother, and AI more trustworthy.
Highlights/ Skip to:
- The challenge of insights not providing value to buyers, end-users, and stakeholders (3:20)
- How the invisible intelligence gap manifests itself (6:42)
- Common symptoms of the invisible intelligence gap (8:10)
- Examples of how changes in human behavior cause the gap (10:00)
- The (3) amplifiers of the invisible intelligence gap (11:47)
- The CED framework for addressing the intelligence gap problem (18:28)
- Addressing the invisible intelligence gap with FOWA (20:14)
- Using MIRRR to solve the invisible intelligence gap (21:25)

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