AI Product & Business Strategy

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Updated Oct 17, 2026
AIU research department

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The lead

Oct 17, 2026

AI Product & Business StrategyUK Competition and Markets AuthoritymajorOct 16, 2026

UK regulator proposes designating Microsoft with strategic market status over its business software

On 16 October 2026 the UK's Competition and Markets Authority proposed designating Microsoft as having strategic market status in respect of its business software ecosystem, and invited comments on that proposed decision.

What it means for your work

A strategic market status designation would let the regulator set conduct requirements on how Microsoft bundles and licenses business software, which shapes the options for teams buying office and cloud tools.

△ vendor-claimed · gov.uk · added todayRead it at gov.uk

What today means

Our read on the items that move something. The reporting is everyone's; this part is ours.

  1. Coding platforms are among the largest model buyers. A public switch on cost grounds shows pricing pressure on frontier labs.Replit is no longer working with Anthropic, its CEO saysThe AI-Assisted Software Development beat · TechCrunch

  2. Investors are still putting large rounds into inference infrastructure, and a $1B run rate suggests serverless GPU platforms are now a significant business.Modal Labs raises $750M at a $15.75B valuation after passing a $1B revenue run rateThe AI Product & Business Strategy beat · Crunchbase News

  3. This is real production routing data, not a benchmark. Teams are switching labs often and sending most volume to cheaper open models, while frontier models keep a large share of spend.Open-weight models now carry 71.5% of Vercel AI Gateway tokens and 23% of spendThe AI Product & Business Strategy beat · Vercel

6 new findings here overnight. 117 here in all.

What this department watches

The charge

This department watches what AI is doing to product and business strategy: where durable value is actually landing, which business models survive contact with customers, and how teams position and measure AI features once they ship. It weights disclosed outcomes and shipped decisions over projections, because a roadmap slide and a retained customer are not the same evidence.

  • Business models that survive first contact with customers
  • Market structure — who is consolidating, who is being routed around
  • Product analytics, and the metrics teams actually steer on
  • Funding and acquisitions, and the capital behind AI product bets
  • Buyer behaviour in the enterprise and in self-serve
  • Outcomes companies disclose after an AI feature ships

The questions it keeps open

6 standing questions

These are the open questions this department works. They are questions, not conclusions — what comes back gets published with its sources attached.

  • What does a product manager actually own once agents draft the requirements, run the synthesis, and build the prototype — which parts of the role concentrate, and which disappear?
  • Which metrics still mean anything when a real share of usage is agent-driven? Activation, retention and seat counts were built for humans clicking.
  • How are AI products being packaged and charged for — by user, by outcome, by run — and which of those models hold up with real buyers?
  • What does discovery look like when you can build the real thing in a day? Does the customer interview still earn its place, or does the working prototype become the research instrument?
  • What is the smallest team that reaches product-market fit now — and what does that do to the org chart, the hiring plan, and the raise a founder is told to expect?
  • Which incumbent workflows — customer records, analytics, support, planning — are AI features changing in practice, not just in the announcement?

How the research runs

The process
1 · Read the real sources

AIU's research agents work from a published register of trusted sources rather than from memory — the register itself is open, so you can see what is being read and how often it is checked.

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2 · Carry the method and the source

A finding is only useful if you can check it. Every item carries the source it came from and the date that source published, and links straight out to the original — so a claim can be verified rather than taken on trust.

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3 · Feed the coursework

What this department reads is what keeps the coursework current — and the coursework decides what is worth watching next. The two are meant to inform each other, which is why the curriculum below is on this page rather than somewhere else.

The curriculum behind it

3 courses on aiuni.tech
The major

AI Product & Business Strategy

Lead products and businesses with the current AI toolset — the builder's alternative to an MBA.

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