In the first issue of this newsletter, I introduced a framework for thinking about AI business value across three buckets: Boosting Productivity, Creating New Value, and Driving Disruption. We've explored the first two in depth over 21 issues. Now it's time to dive more into the third bucket: Disruption.
This is the bucket many leaders find most uncomfortable. Productivity feels safe — you're making existing work better. New value creation feels exciting — you're enhancing what you offer. But disruption means questioning whether the way your industry operates will still make sense in three years. It means asking whether your own business model might be the thing that gets disrupted.
I look at disruption through two lenses. In this issue, I'll introduce both at a high level. In the next two issues, I'll take each lens apart in detail with deeper frameworks and case studies.
Lens 1: Value chain compression
Every business operates through a value chain — a sequence of activities from sourcing to delivery that creates value for the customer. The first disruption lens asks: which links in your current value chain are vulnerable to AI-driven compression, unbundling, or replacement?
Saying that AI will not affect your industry is like burying your head in the sand. AI commoditizes activities that were previously high-margin because they required specialized knowledge, manual effort, or institutional scale.
In healthcare, over $1 trillion in U.S. spending waste comes from administrative overhead. AI scribes achieved widespread adoption in 2–3 years, compared to 15 years for electronic health records. The administrative links in the healthcare value chain are compressing fast.
In legal services, the disruption is happening from two directions simultaneously. Up to 74% of hourly billable tasks are now automatable. But what's accelerating the shift isn't just the technology — it's competitive pressure. As Max Junestrand, CEO of Legora (a legal AI platform that just raised $550M at a $5.5B valuation), described recently: if the firm down the road offers the same venture financing at $75,000 instead of $100,000 with twice the turnaround because they leverage AI, the equilibrium breaks. And now the big banks, insurance companies, and pharmaceutical firms are starting to demand that their outside counsel leverage AI.
In financial services, AI-powered fintechs are moving faster than incumbent banks — receiving 49% of total equity funding despite raising less per round. They're attacking specific links in the value chain rather than replacing the entire chain at once.
The strategic question for Lens 1 is: Map your value chain. For each link, ask: could AI compress this activity's cost by 50% or more within three years? If yes, will you be the one doing the compressing — or will someone else do it to you?
Lens 2: New actor emergence
The second lens shifts perspective. Instead of looking inward at your existing chain, you look outward and ask: who are the non-actors — the people, companies, or even non-human agents — that AI now enables to participate in value creation that was previously closed to them?
This is inspired by Blue Ocean Strategy's concept of non-customers. But instead of asking "who isn't buying our product?", I'm asking "who isn't participating in our value chain — and what happens when AI removes the barriers that kept them out?"
AI removes several barriers simultaneously: cost, expertise, language, scale, and speed. When multiple barriers drop at once, new actors emerge.
In healthcare, solo practitioners and small clinics — previously unable to compete with large consolidated health systems — can now access AI diagnostic tools, automated administrative workflows, and telehealth infrastructure that levels the playing field.
In legal, solo attorneys using AI for prior art searching, contract drafting, and case research can now deliver quality that previously required a mid-size firm's resources. The American Bar Association reports that 72% of solo practitioners are already using AI tools. And individual partners at large firms are using AI to scale their personal capacity — serving more clients with the same 14–16 hours in a day, encoding their expertise and institutional knowledge into systems that work alongside them.
In education, individual teachers and course creators can now reach global audiences with AI-personalized instruction — competing with institutional tutoring programs without institutional infrastructure.
What's interesting is that some of the new actors might not even be human. Stripe and Ramp recently launched infrastructure that gives AI agents their own credit cards — transaction-scoped, spend-limited, fully auditable. AI agents are becoming autonomous economic participants, capable of purchasing services, executing trades, and managing budgets independently.
Applying both lenses to your business
When I work with leaders on disruption strategy, I ask them to run both lenses on their business:
Lens 1 audit: List every link in your value chain. For each, rate the AI compression risk (low / medium / high) and your current response (leading / following / ignoring).
Lens 2 scan: Identify three categories of non-actors in your value creation landscape — individuals, smaller competitors, and non-human agents — and ask what happens when they gain access to capabilities that were previously yours alone.
In the next two issues, I'll take each lens apart in detail — with deeper frameworks, more industry-specific analysis, and practical tools you can use to assess your own disruption risk and opportunity.
Your action step
This week, draw your company's value chain on a single page — every major activity from sourcing to customer delivery. For each link, write one sentence answering: "If AI could reduce the cost of this activity by 50%, who benefits — us or a competitor?" Then identify one non-actor category (a solo practitioner, a smaller competitor, an AI agent) that could enter your market if barriers dropped. That's your disruption map — and the starting point for a strategic conversation your leadership team needs to have.
Sources:
For a ground-level view of how AI disruption is playing out in one of the most traditional industries, I recommend the interview with Max Junestrand, CEO of Legora, on the Unsupervised Learning podcast. Max walks through how competitive pressure between law firms — and increasingly from enterprise clients — is reshaping the legal value chain in real time.