Cohere just crossed the inflection point enterprise software has been watching. The AI infrastructure startup hit its revenue targets this quarter, the same moment OpenAI and Anthropic are actively weighing IPO timelines. This isn't just another funding announcement. It signals the moment when three competing AI infrastructure platforms simultaneously demonstrate sustainable unit economics—the moment when enterprise AI transitions from speculative mega-round phenomenon to sector-wide readiness for public capital markets. For enterprises evaluating AI vendors, investors timing allocations, and professionals building careers in scaling AI companies, the calculation changes today.

Here's what shifted this morning. Cohere didn't just announce funding or promise future metrics—the company delivered on revenue targets, demonstrating that enterprise customers are paying for AI infrastructure at sustainable unit economics. That's the transition from runway extension to real business. And it's happening in lockstep with OpenAI and Anthropic both signaling IPO exploration. The timing is deliberate, not coincidental.

The broader inflection is this: AI infrastructure just stopped being a venture game and became a capital markets story. Until now, the narrative around Cohere, OpenAI, and Anthropic was all about mega-rounds—$30 billion valuations, Saudi funding, strategic capital from big tech. That's the story when investors believe revenue is still years away. But when all three platforms simultaneously hit revenue milestones and start preparing for public debuts, the market is saying something different. Enterprise AI is real. The unit economics work. And the question shifts from "will this matter?" to "how do we allocate capital across competing platforms?"

Consider what's happening in enterprise purchasing decisions right now. Three months ago, companies were comparing Cohere versus OpenAI with a binary choice: the private startup or the mega-valued private company. There was no precedent for choosing between public AI infrastructure providers. That changes when even one of these companies files their S-1. The moment Cohere or OpenAI hits public markets, enterprise buyers get something they don't have today: audited financials, quarterly earnings calls, regulatory scrutiny, and forward guidance. That's risk reduction. That's the moment a CTO at a Fortune 500 company says "we can commit to this platform for the next five years." It's the moment competitive advantage shifts from funding size to sustainable margin.

The evidence is in the enterprise adoption numbers. Cohere reaching revenue targets doesn't happen by accident—it requires customers paying for API usage, fine-tuning, enterprise support. Anthropic's $30 billion valuation last month only makes sense if investors believe the company will prove unit economics at public company scale. OpenAI's IPO exploration suggests the company is confident enough in its revenue trajectory to prepare for public scrutiny. These aren't coordinated moves, but they're directionally aligned. The market is saying: enterprise AI is past proof-of-concept, into production deployment, heading toward public market validation.

This reshapes three decisions simultaneously for different audiences. For investors, the window for late-stage mega-rounds in AI infrastructure is closing. The next capital event for companies like Cohere or Anthropic is likely an IPO filing, not another private round. That means the venture mega-round era is giving way to public market crowding. Expect increased competition for allocation when S-1 filings arrive. For enterprise decision-makers, the choice between AI infrastructure vendors just got a lot more straightforward. Instead of evaluating private company risk, you'll soon evaluate competing public platforms on revenue growth, margin expansion, and competitive differentiation—the same metrics you use for enterprise software today. That legitimizes AI investment internally. It also reduces vendor lock-in risk, since multiple providers will exist with public financial backing.

For builders—the engineers, product leaders, and researchers at these companies—the trajectory just became visible. Cohere hitting revenue targets means the company isn't just surviving on funding; it's on a path to scale. OpenAI and Anthropic exploring IPOs means their early employees are looking at liquidity events within 18-24 months. That shifts how AI engineers evaluate where to invest their next 3-5 years. Public company scale appeals to different talent than well-funded startups—not better or worse, just different. You're choosing between maximum growth potential (private) versus stable scale and eventual exit (public-track). The inflection point is when those choices become mutually exclusive. We're there now.

The precedent here is worth noting. This mirrors the moment in 2010-2012 when cloud infrastructure startups like Rackspace and eventually Amazon Web Services transitioned from "interesting alternative" to "required vendor." Enterprise confidence shifted when the first cloud infrastructure company went public. Once Rackspace filed, every enterprise IT leader suddenly had permission to commit budget to cloud. The inflection happened not at founding or Series A, but at the moment public markets validated the business model. We're at the same moment in AI infrastructure. The first public AI infrastructure company to file won't just go public—it'll reshape how enterprises allocate spend across the entire AI vendor ecosystem.

What's different now is the compressed timeline. Unlike cloud infrastructure, which took 8-10 years from founding to IPO, AI infrastructure startups are compressing that cycle. Cohere was founded in 2021. OpenAI launched ChatGPT in November 2022. Anthropic launched in 2021. We're talking about companies moving from concept to public market readiness in 3-5 years. That acceleration matters for timing. Enterprises that delay AI vendor selection now are betting they'll have more options in 12-18 months. Investors that wait for IPO filings are betting they won't miss the initial public market window. Both calculations are tight.

The enterprise competition angle is critical too. When Anthropic secured its $30 billion valuation last month, the message to enterprises was clear: this company isn't shutting down, isn't getting acquired, isn't pivoting. It's building for scale. Now with Cohere hitting revenue targets and OpenAI signaling IPO interest, enterprises have genuine alternatives. That's the moment lock-in risk drops. Instead of choosing between one well-funded startup and betting your AI strategy on venture capital longevity, you can choose between three platforms with different pricing, different model capabilities, and different growth trajectories. That competitive pressure forces all three companies to accelerate their paths to profitability and public markets. It's self-reinforcing.

For professionals in the space, the implication is straightforward: your next AI career move should have a public company exit timeline. Companies still in mega-round mode are betting on 7-10 year outcomes. Companies preparing for IPOs are betting on 18-24 month outcomes. That's the difference between startups and scaling platforms. The talent markets will sort accordingly—top engineers will migrate toward companies with visible exit timelines, while experimental researchers will stay at well-funded private ventures. It's the natural bifurcation that happens when startups cross from private to public company territory.

The inflection point is clear: enterprise AI infrastructure is no longer speculative. Cohere hitting revenue targets plus simultaneous IPO momentum from OpenAI and Anthropic signals the sector has moved from mega-round funding to public market validation. For investors, the mega-round era is closing—expect S-1 filings within 12-18 months. For enterprise decision-makers, competitive public platforms arriving soon changes vendor selection calculus—from risk mitigation to capability comparison. For builders, the choice between private venture upside and public company scale becomes real. For professionals, the talent bifurcation is starting now. Watch for the first S-1 filing—that's the moment enterprise adoption acceleration begins and investor crowding into AI infrastructure intensifies. The 18-month window to position before public market crowding is opening right now.