On January 29, 2026, software stocks posted their worst single day since the Covid crash. ServiceNow dropped 11% despite beating earnings. Microsoft lost $360 billion in market cap. The IGV index—tracking the software industry—entered bear market territory, down 22% from its highs.
The trigger wasn't a recession or a financial crisis. It was a growing realization on Wall Street that AI is making entire categories of business software obsolete.
As SaaStr founder Jason Lemkin wrote the following week: the crash isn't cyclical. It's structural. Enterprise budgets aren't shrinking—they're redirecting. Away from seat-based software licenses and toward AI-native tools that handle the same work at a fraction of the cost.
This isn't a technology story. It's a business model story. And it applies far beyond SaaS.
The Question Nobody Wants to Ask
Here's the uncomfortable reality that most leadership teams are avoiding:
What is your company worth when AI can deliver what you used to charge for?
If your margins depend on information asymmetry—knowing something your customers don't—that advantage is evaporating. If your value comes from expertise gatekeeping—being the only ones who can do a complex task—AI is democratizing that capability. If your business model relies on manual coordination—connecting people, data, or processes that couldn't connect themselves—AI agents are automating that layer entirely.
This isn't hypothetical. It's already pricing into public markets. Gartner fell 21%. S&P Global dropped 11%. Analysis firms whose entire value proposition was synthesizing information that was previously hard to access are watching AI do it in seconds.
The 34% Who Get It—And the 66% Who Don't
Deloitte's 2026 "State of AI in the Enterprise" report quantifies the gap. Of the 3,000 senior leaders surveyed:
- 34% are using AI to create new products, services, or fundamentally reinvent their business models
- 30% are redesigning key processes around AI
- 37% are applying AI superficially—layering it onto existing workflows with minimal structural change
That bottom 37% is doing what feels safe. They're using AI to write emails faster, generate reports more efficiently, summarize meetings automatically. And they're calling it transformation.
It's not transformation. It's optimization of a model that may already be expiring.
BCG's research describes what happens next: a "winners-take-most" dynamic where 60% of businesses risk stagnation. The organizations that achieve AI-native operations are realizing 25 to 35 times more revenue per employee than traditional peers. That's not a marginal advantage. That's a different category of company.
What's Actually Expiring
The business models most at risk share common characteristics. They monetize one or more of these:
Information asymmetry. You know something the customer doesn't, and they pay you for access. Financial advisory, market research, legal analysis, real estate brokerage—every industry built on "we have the data and expertise you lack" is watching AI flatten that advantage. Harvey.ai is already doing contract drafting for firms like Allen & Overy. AI-powered platforms offer instant property valuations. Financial analysis that once required teams of analysts takes minutes.
Expertise gatekeeping. Complex tasks require specialized knowledge, and you're the gatekeeper. Consulting firms are seeing 40% of their traditional tasks become automatable. Publicis Sapient reported cutting traditional SaaS licenses by roughly half, calling AI tools "10x faster" than the junior staff who previously handled those workflows.
Manual coordination. You connect people, processes, or data that couldn't connect themselves. Staffing firms, brokerages, project management consultancies—any business that primarily adds value by being the connective tissue between parties. AI agents are increasingly handling multi-step coordination across enterprise systems without human intermediaries.
If your business relies heavily on any of these, the clock is ticking. Not because AI will replace everything you do overnight—but because your competitors who reinvent around AI will offer your customers dramatically more value at dramatically lower cost.
The Reinvention Question, Answered
So how do you actually answer the question?
Not with a technology assessment. Not with an AI vendor evaluation. With a brutally honest examination of your value chain.
Start here: What do your customers actually pay you for?
Not what your sales deck says. Not what your mission statement claims. What specific outcome makes a customer hand you money? Strip away the delivery mechanism, the process, the people involved. What's the result they're buying?
A consulting firm's customers aren't buying hours of analysis. They're buying confidence in a decision. A staffing company's customers aren't buying resume screening. They're buying a productive employee starting on Monday. A software company's customers aren't buying features. They're buying a problem solved.
Then ask: Can AI deliver that outcome more directly?
This is where it gets uncomfortable. Because in many cases, the honest answer is yes—or it will be soon. AI can increasingly deliver decision confidence, match candidates to roles, and solve the problems that software historically required manual configuration to address.
The reinvention isn't about the AI. It's about the outcome.
The companies in that top 34% aren't just using AI tools. They're restructuring around the outcomes their customers actually want, using AI to deliver those outcomes in ways that weren't previously possible.
What Reinvention Actually Looks Like
McKinsey's research shows that high-performing organizations pursue organizational transformation 3.6 times more often than their peers. They're not optimizing existing processes—they're rethinking which processes should exist at all.
Here's the pattern:
From selling expertise to selling outcomes. Instead of billing for hours of analysis, you guarantee a result. AI handles the analytical work. Your team focuses on judgment, context, and implementation—the parts AI can't do well. Your margins shift from labor arbitrage to outcome delivery.
From gatekeeping information to curating intelligence. When everyone has access to the same AI-powered analysis, raw information becomes worthless. The value moves to interpretation—what does this data mean for this specific company in this specific market at this specific moment? That requires deep domain knowledge and human judgment.
From manual coordination to orchestrated ecosystems. Instead of being the middleman, you become the platform. You don't connect parties manually—you build the system that connects them intelligently, learning and improving with every interaction.
From selling seats to selling capability. The SaaS crash isn't happening because software is dying. It's happening because AI is changing what capability means. The winners, as Lemkin noted, will price on outcomes rather than seats, own the data layer, and build AI-native interfaces.
The Mid-Market Advantage
Here's what gets lost in the headlines about billion-dollar AI investments: mid-market companies may actually be better positioned for reinvention than enterprises.
Large organizations are paralyzed by complexity. They have legacy systems, entrenched processes, and organizational politics that make reinvention almost impossible without a multi-year, enterprise-wide program. BCG found that companies with over $5 billion in revenue are more likely to scale AI—but scaling isn't the same as reinventing.
Mid-market companies can move faster. You have fewer layers of approval. You know your customers more intimately. You can redesign a business model in months, not years.
The companies that will thrive aren't the ones with the biggest AI budgets. They're the ones that understand their customers deeply enough to know what outcome to reinvent around—and move decisively enough to do it before the market shifts.
This is fundamentally a human problem, not a technology problem. The leaders who understand how their customers actually talk about their needs, who can see past the current delivery model to the underlying value, who have the courage to cannibalize their own revenue before someone else does—those are the ones who will answer the reinvention question correctly.
The Window
The World Economic Forum reports that half of employers are actively reorienting their business models around AI in 2026. Deloitte shows company-wide AI transformation doubling year over year, now at 25%.
The window for reinvention is open. But it narrows quickly once competitors in your space start delivering outcomes that make your current model look expensive, slow, and unnecessary.
The question isn't whether your business model has an expiration date. Every model does. The question is whether you'll reinvent it on your terms—or wait until the market forces you to.
AI isn't coming for your job. It's coming for your value proposition. The companies that understand the difference will be the ones still standing in five years.
