Insights
The value shows up in what you route, what you measure, and where your data is allowed to live, not in the launch. We work across Western and Chinese model ecosystems and write down what actually moves the number for the companies adopting this.
How we see AI adoption
Two years of pilots taught the market that a demo is easy and a deployment is not. The gap between them is not model quality. It is routing, measurement, cost discipline, and data governance: the unglamorous operations layer where the money actually leaks. This is the lens we bring to every piece below.
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of enterprise AI still runs on frontier models
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price spread between cheap and frontier tiers
A 50× spread between commodity and frontier tokens turned routing from an optimization into the single biggest cost lever most teams have, and the cheap tier that makes it possible is now mostly Chinese open weights. Adoption in 2026 is a portfolio decision, not a single-vendor bet.
CEO’s Opinion
Most of this library is team-reviewed analysis. This shelf is different: a first-person position from our CEO, written from his own P&L, argued in his own name, and revisited in public when the facts move.
Cyril Drouin
CEO · BearingBridge
The library
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AI hasn’t destroyed jobs yet, but after building agents across six business functions, I see companies quietly freezing hires instead of firing anyone at all.
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Organic clicks fell while AI referrals started converting better. What AEO and GEO each buy, who should own them, and how an executive measures both.
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AI work is moving from bespoke builds to assembled platforms. What that changes for buyers, what it does not, and what to ask before signing.
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Beijing is turning AI inference into a metered export commodity. Five assumptions underpin that strategy, and only one of them survives contact with available data.
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One model rarely ships. Orchestration coordinates specialized models and tools, then adds decision points you should govern before you build.
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The assistants are becoming the front door to your market, and a citation is the only click that still leaves. How those citations actually work.
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The demo worked. Now: build it in code, or run it on a platform? Four questions, ordered so the first hard answer ends the discussion.
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Routing across cheap and frontier models is now table stakes, and China supplies most of the cheap tier. What that means for your stack.
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Most people give NotebookLM lazy prompts and get book reports back. Twelve our team uses to pull real work out of it instead. Each prompt included in full and formatted to copy.
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Tap a topic to filter the library above. Empty ones are on the way. We ship when it is tested, not when the calendar says so.
Talk to us
A conversation with the senior team about your markets, your data, and where AI would actually pay back for you. No slides, no obligation, and if the honest answer is that AI is not your next move, you will hear that too.
Prefer email? hello@bearingbridge.com