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The 12-Month Land Grab: Why AI Market Share Is Being Decided Right Now

A decade of software adoption is happening in 18 months. The winners of the AI era will be decided by who moves fastest in this narrow window.

The 12-Month Land Grab: Why AI Market Share Is Being Decided Right Now

TL;DR: Enterprise tech markets have entered an unprecedented synchronized AI buying cycle. Companies are compressing 5-10 years of software adoption into 12-18 months. This creates a rare land-grab opportunity where market leadership will be determined by execution speed over the next year. After that, the window closes.

Every customer is buying right now

In a normal market, you spend years educating prospects, nurturing pipelines, and gradually building market share. Early adopters buy in year one. Fast followers in years two and three. Laggards take five to ten years.

Not this time.

In 2024-2025, practically every enterprise is implementing AI simultaneously. Legal firms that bought almost no new software in the past decade are all shopping for AI tools at once. Healthcare systems are rolling out clinical documentation AI to tens of thousands of physicians in months, not years. Customer support teams that would have taken years to adopt new platforms are running AI trials across the board.

Jason Lemkin of SaaStr puts it bluntly: "every law firm + legal department is looking for an AI tool in 2025" whereas "they barely bought any software the past 10 years." An entire decade of technology adoption has been compressed into a single buying cycle.

This synchronization is unprecedented. The market dynamics are fundamentally different when every potential customer is actively shopping in the same 12-month window instead of being spread across a decade-long adoption curve.

The numbers are absurd

The growth rates from this compressed cycle defy normal SaaS metrics:

Harvey (legal AI) went from $10M to $70M ARR in 15 months. By mid-2025, they'd crossed $100M ARR and captured the majority of top-tier law firms as customers.

Abridge (healthcare documentation) jumped from $50M to $117M ARR in five months, deploying to 25,000+ physicians across major health systems like Kaiser Permanente.

Cursor (AI coding) scaled from essentially zero to $300M ARR in roughly a year.

Lovable (dev tools) hit $1M ARR in 8 days, $10M in 2 months, and $60M within 6 months of launch.

These aren't outliers. They represent a new growth operating system where companies achieve in 12-24 months what previously took 5-7 years. One investor summarized it: "Traditional vertical SaaS might hit $100M ARR in 5-7 years. These AI-native companies are doing it in 1-2 years."

The reason? When every customer is buying simultaneously, the entire addressable market is in-market at once. There's no waiting for the next cohort of early adopters or late majority. Everyone is shopping now.

And here's the brutal truth:

if you're a B2B team that hasn't captured any of this AI spending wave by now, you've failed.

As Lemkin put it, "If your team didn't capture ANY of this massive spending wave by end of 2025, you don't need half your team. They had 18 months." The money was there. The opportunity was there. Teams that couldn't execute during this unprecedented demand surge have proven they can't compete.

The scale of money in motion

Before we discuss why this window is closing, understand the sheer magnitude of capital flowing into AI right now. This isn't a typical software upgrade cycle. This is a fundamental infrastructure build-out rivaling historical technology shifts.

The numbers are staggering:

  • OpenAI raised commitments for over $1 trillion in capex over the next 5 years
  • Microsoft committed $250 billion to OpenAI partnerships
  • Oracle committed $300 billion, Broadcom $400 billion
  • AI-related capital expenditures hit approximately 1.2% of U.S. GDP in 2025, exceeding the 1.1% peak of the dot-com boom[^6]

This investment level is unprecedented. As one analysis noted, "Perhaps the most thought-provoking moment came when discussing AI's seemingly infinite capital appetite."[^6] When does it end? The answer: soon. This pace of investment cannot be sustained indefinitely, which is precisely why the current window is so critical.

Why this window is closing

The synchronized buying frenzy cannot sustain itself. Here's why the opportunity is time-bound:

Budget cycles are already shifting. The 2024-2025 period saw exceptional AI budgets unlocked across enterprises. CFOs gave teams carte blanche to experiment with AI tools. By mid-2025, that's changing. McKinsey surveys show executives expect flat or reduced AI budgets going forward until ROI is proven. The "buy everything AI" phase is ending.

Pilot consolidation is happening now. Right now, many enterprises are running multiple AI tool pilots simultaneously. Legal firms are testing Harvey, LexisNexis+, and others in parallel. Support teams are trialing five different AI agent platforms. This phase boosts all vendors temporarily, but consolidation is imminent. Over the next 12 months, firms will pick winners and cut the rest. Once they've standardized on one or two solutions, new sales opportunities evaporate.

TAM capture is faster than anyone expected. In legal AI, Harvey already has the majority of AmLaw 100 firms as customers. In healthcare documentation, the largest health systems are signing. The accessible market is being consumed at 5-10× normal velocity. If you haven't landed a customer by the time they've chosen their AI stack, you've likely lost them for years.

The early mover advantage compounds brutally. Unlike traditional SaaS where customers might switch vendors every few years, AI tools that prove ROI will be deeply embedded in workflows. A law firm that builds Harvey into their research and drafting processes won't rip it out in 18 months. A health system that trains 10,000 doctors on Abridge won't churn easily. First movers are securing multi-year lockouts of their customers.

The legal AI consultant Zach Abramowitz warns that much of the revenue being booked today is pilot fees being counted as recurring revenue. "It's getting booked like recurring revenue," he notes, "but the reality is it's still mostly pilot programs." In the next 12-18 months, firms will "rally around the top tech performers, while other vendors watch their revenues decline." The separation between winners and losers is happening right now.

Investor Rick Zullo captures the dynamic perfectly: "If every single company in a category is working, that's probably the scariest thing that could happen, because that just means there's no alpha in the company that you're generating." Right now, all legal AI companies are growing. All customer support AI vendors are signing deals. That won't last. Once consolidation happens, the market will separate into clear winners and losers.

What execution looks like in the land grab

If you're building in a vertical AI space, your strategy for the next 12 months should look radically different than normal GTM planning:

Move fast on capacity. The bottleneck isn't demand, it's your ability to close and implement. If you're artificially constraining your sales hiring or deployment capacity because you're following normal SaaS playbooks, you're leaving market share on the table. This is the moment to over-invest in the machine that converts pipeline to closed-won to deployed.

Land logos, not just ARR. In a normal market, optimizing for deal size and profitability makes sense. Right now, capturing customer count matters more. If there are 500 target accounts in your vertical and 400 of them will pick a solution in the next 12 months, your goal is to be in as many of those 400 as possible. Discounting to win the logo is rational when the alternative is permanent market exclusion.

Speed to value beats feature completeness. Customers are buying fast and making decisions based on quick pilots. The vendor that can show clear ROI in a 30-day trial wins, even if their product roadmap is thinner. Optimize for time-to-wow, not comprehensive feature sets.

The Hopin precedent

This isn't theoretical. We watched this exact pattern play out with virtual events platforms during COVID.

Hopin, founded in 2019, exploded to a $7.8B valuation within two years as every conference, meetup, and corporate event went virtual overnight. The company scaled to 800+ employees and was one of the fastest-growing software companies ever. Then the window closed. By 2022, in-person events returned and virtual event demand collapsed. Hopin had to conduct mass layoffs (halving its headcount in 2022) and eventually sold off parts of its business for a fraction of peak valuation.[^9]

The critical insight: Hopin succeeded in capturing enormous market share during their window. They became the category leader in virtual events. Their failure wasn't in execution during the land-grab, it was in not recognizing that the window itself was temporary.

The AI buying cycle is different in one crucial way: AI adoption is permanent. Legal AI won't vanish like virtual events did. But the compressed buying cycle is the same pattern. Everyone is shopping now. The winners will be determined in the next 12-18 months. After that, most customers will have chosen their tools and the market will revert to normal, slow-moving replacement cycles.

The lesson isn't "don't be like Hopin." The lesson is: Hopin won the land-grab. They captured the category. If the virtual events market had remained even 30% of its peak size, they'd have built a massive sustainable business. They executed the land-grab correctly. The market shift was beyond their control.

The math is simple

Let's say your vertical has 1,000 potential customers. In a normal market, maybe 100 adopt in year one, 200 more in year two, 300 in years three through five, and 400 eventually become laggards who adopt slowly or never.

In the current AI cycle, 700 of those 1,000 customers are shopping in the 2024-2026 window. They're all in-market simultaneously.

If you capture 30% market share during this window, you land 210 customers. In a normal adoption curve, getting to 210 customers might take 5-7 years. You're doing it in 18 months.

But here's the key: once those 700 customers choose, they're off the market for 3-5 years minimum. The market reverts to maybe 50-100 customers per year being in-market (replacements, late adopters, new entrants). Your growth rate collapses from 3-5× annually to 20-30% annually.

The company that won 30% share (210 customers) in the land-grab has a massive structural advantage over the company that won 10% share (70 customers). They have 3× the revenue base, 3× the customer stories, 3× the word-of-mouth engine, and 3× the capital efficiency to invest in product and sales.

Important

That gap is nearly impossible to close once the window closes. The land-grab determines the market structure for years.

What happens in 2026

Lemkin predicts an "AI burnout wave" around 2026. The frenetic pace becomes unsustainable. CFOs demand ROI from all the pilots. Enterprises consolidate their AI tool stacks. Many vendors watch revenues plateau or decline as pilot fees don't convert to long-term contracts.

This isn't a prediction that AI fails or usage drops. It's a prediction that the compressed adoption curve completes and we return to normal market dynamics.

The winners will be the companies that captured significant market share during the 2024-2025 window. They'll have the customer base, the revenue scale, and the market position to sustain themselves through the normalization. They'll grow 20-30% annually instead of 300% annually, but from a much larger base.

The losers will be companies that stayed disciplined, grew conservatively, and optimized for unit economics during the land-grab. They'll have great margins but small market share. And they'll find that the doors they thought would be open for years have already closed.

The opportunity cost of caution

The biggest risk right now isn't moving too fast. It's moving too slow.

If you burn $20M to capture an extra 100 enterprise customers during this window, and those customers stick for 5+ years at $100K ACV, you've generated $50M+ in lifetime value from that spend. The ROI is obvious.

But if you stay lean, preserve your runway, and only capture 30 customers instead of 100, you've "saved" $20M in burn but lost $35M in future revenue. You'll be profitable sooner but permanently smaller.

The VCs who understand this are writing bigger checks into AI category leaders right now, often at high multiples. They're not betting that these companies will sustain 300% growth forever. They're betting that market share captured now will compound for a decade.

The founders who understand this are raising preemptively, hiring aggressively, and discounting strategically to win logos. They're optimizing for market capture, not near-term profitability.

The executives who understand this are approving AI budgets, running rapid pilots, and making vendor decisions in weeks instead of quarters. They know their competitors are doing the same thing, and lagging by 6 months could mean permanent competitive disadvantage.

This is not normal

One more time, for the people in back: the current AI buying cycle is not a normal market expansion. It is a time-compressed land-grab where 5-10 years of adoption is happening in 12-18 months.

Tip

If you're building in a vertical AI space, your next year will determine your next decade. Move fast!

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