In recent years, we’ve witnessed the breakout growth stories of GitHub Copilot and ChatGPT expand into a movement that has sparked an investment frenzy in GenAI. Against a backdrop of a cooled VC market that is deploying funds at roughly 55% of 2021’s peak, GenAI is a VC hotspot unlike any other in recent memory, with 20,000+ new GenAI startups speaking for nearly a third of all venture funding in Q3 ’24.
The Velocity of GenAI is Undeniable
The gravitational pull of so much money going into so many startups in one focus area is accompanied by the stark evidence of winners breaking out faster than ever before. Leading GenAI startups as a group reach ARR milestones 2-5x faster than comparable SaaS companies, and reach exits in half the time of non-AI startups.
Investors can correlate this to unprecedented zero-to-$B AI revenue ramps at larger scale public and private companies like Microsoft and OpenAI. The result is not just significant VC money shifting from generalist into AI-focused strategies, but also a tactics shift. Firms are investing in multiple competing companies that all work in GenAI. Investors are betting across the board, with GenAI to win, place, and show.
Startups Themselves are Some of the Strongest AI Use Cases
Cash isn’t the only factor that’s driving this velocity. The mobility of AI and go-to-market (GTM) talent with lean, focused teams that maximize the power of agentic automation is crucial. For positions in services, sales, and technical job functions like customer service agent (CSA), sales development representatives (SDRs), site reliability engineering (SREs), and more, this innovation cannot be understated.
As startups working on agents proliferate (400+ companies already), we’ve seen a pattern in adoption that mirrors the rise of prior breakouts like Jasper and Stability AI. Many early adopters are AI startups themselves, whose founders are doubling down on the advantages of the technology by internalizing it into operations. This indicates that companies view AI as not only the product but an organizational principle of the company. That reality maximizes technological leverage to increase workforce alignment towards revenue goals.
These efficiencies are the “invisible product” of AI revenue, and part of the answer to the question some investors have posed about the slow emergence of AI as a business in its early innings. One AI sales development representative (SDR) agent startup we met with has $10M annual recurring revenue (ARR) and 35 full-time equivalents (FTEs). Yet, it has a team of zero SDRs itself and only a few account executives (AEs), whose customers comprise mostly SMBs with a few enterprises signed on. If promises of the savings from agentic services are borne out, this could offer a way out of the “SaaS crash” for companies who aren’t in the GenAI hotspot, by boosting their operating profits.
A Growth Opportunity Not to be Overlooked
Demonstrations of such robust ROI for their customers will drive further the demand for AI availability and the need for efficient infrastructure to build out faster. The industry’s pace of doubling tokens per dollar per Watt every six months creates new opportunities for startups to innovate in both the software and hardware level to avert energy and emissions impacts of what we believe will be widespread and persistent AI workloads.
How M12 is Fueling GenAI Startup Innovation
Along with increasing coverage of the emerging economy for agentic and GenAI startups, M12 is expanding its focus to include New Systems for operating data centers, and processing and distributing AI workloads. These companies bracket the AI software stack, but extends beyond cloud infrastructure to physical endpoints. M12 has already made some investments in this category and our team is excited to see where this path leads the world.
