You Already Have the Asset

Bloor Research’s argument starts from a fact, not a pitch: the asset already exists. It’s the accumulated frameworks, decisions, and judgement sitting inside the organisation, in the heads of its senior people and subject matter experts, unstructured. The gap isn’t expertise, it’s that the organisation hasn’t gone through the Capture step yet. That’s a starting-point problem, not a from-scratch one, which is exactly why the delay costs more than it looks like it does.

Every Day You Delay, Someone Else’s AI Gets Smarter

Bloor’s argument is blunt about the cost of waiting: every day an enterprise delays is a day someone else’s AI is learning from its people’s prompts. That’s no longer a hypothetical. A September 2026 Harvard Business Review piece describes a pattern it calls “AI Sherlocking” – platforms absorbing not just a company’s data, but the logic behind how its people solve problems, through ordinary feedback loops and everyday prompt use. The risk isn’t limited to what’s in a contract; it extends to “shadow AI” use, where employees running personal AI accounts train tomorrow’s competitors without anyone at the company deciding that should happen.

It’s the same asymmetry the Fusion Economy argument makes about rented productivity: nothing that happens inside someone else’s platform compounds for the organisation using it. Left uncaptured, a team’s own reasoning doesn’t just fail to compound, it actively compounds for whoever’s model is on the other end of the prompt.

Data Ownership Is Becoming the Default Expectation

This isn’t a fringe concern. In a survey of more than 2,000 executives, research by EDB, published by MIT Technology Review Insights in May 2026, found that 70% of global executives said they need a sovereign data and AI platform to succeed – a reversal of the earlier bargain enterprises struck of “capability now, control later”, trading proprietary data for third-party model power and losing governance over it in the process.

Bloor’s analysis anticipates the same shift from the individual’s side too: data ownership is becoming regulation, citizen digital assets and sovereign AI are converging, and first movers own the standard rather than adapting to one set by someone else.

This Is an IP Programme, Not a Technology Project

The reason this can’t be delegated to a one-off software purchase is structural: a Digital Me℠ is an ongoing programme of intellectual asset development, not a system you buy once and leave running. Capture, codify, deploy, compound, own – each stage keeps producing value only as long as the programme continues, the same way institutional knowledge only stays useful while someone keeps maintaining it.

Treated as a technology project, it’s evaluated on a purchase timeline: is this the right budget cycle? Treated as an IP programme, the only real question is how much longer the underlying knowledge goes unstructured while someone else’s model gets better at sounding like the person who should have captured it first.\

Who Needs to Move First

For an enterprise, the cost of waiting concentrates in specific people, the ones the personas this framework was built around already describe: the senior executive whose pattern recognition is locked in one diary, the consultant whose methodology is still undocumented, the founder who is currently the entire brand. For all of them, the structural advantage goes to whoever captures first, not whoever captures best eventually.

“The question is no longer whether you build a Digital Me. It is whether you build it before everyone else in your market does.”

— Bloor Research International

Frequently Asked Questions (FAQs) 

1. Why does timing matter for building a Digital Me℠?

Because the underlying asset, an organisation’s captured knowledge, only compounds once it’s structured, and every day it stays uncaptured is a day it’s either lost to attrition or fed, unstructured, into someone else’s AI instead.

2. What is “AI Sherlocking” and why does it matter here?

It’s the pattern Harvard Business Review describes of AI platforms absorbing not just data but the logic behind how people solve problems, through routine prompt and feedback use – a real, current risk of using generic AI tools without capturing an organisation’s own knowledge first.

3. Is this really urgent, or is it a compliance nice-to-have?

Yes, research by EDB, published by MIT Technology Review Insights, found that 70% of executives already say they need a sovereign data and AI platform to succeed. That describes a competitive and regulatory shift already underway, not a future hypothetical.

4. What’s the first step?

Capture: structuring the frameworks, decisions, and reasoning a person or team already has, before it’s built into any system at all.

Sources

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