The advent of advanced artificial intelligence has sparked a mad dash among tech startups to secure funding and gain an early advantage in what many believe will be a transformative industry. With the potential to disrupt sectors ranging from healthcare and finance to transportation and manufacturing, AI represents one of the biggest technological shifts since the rise of the internet and mobile computing. As a result, venture capital is pouring into the space at an unprecedented rate as investors look to back the next potential Google or Amazon of AI.
“What we’re seeing right now is a gold rush mentality when it comes to AI,” says Arjun Sethi, partner at venture capital firm Tribe Capital. “Every founder believes their AI startup is going to be the one to strike it rich. And every VC firm is terrified of missing out on the next big thing. So you have this intense competition to invest in and scale these companies as quickly as possible.”
In 2022, venture funding for AI startups hit a record $93.5 billion, nearly doubling the previous high of $50 billion set in 2021, according to data from PitchBook. So far in 2023, that torrid pace of investment hasn’t slowed, even amid a broader tech downturn. Through the first quarter, AI companies raised $21 billion, putting the industry on track for another blockbuster funding year.
But as more and more startups flood into the market with undifferentiated pitches and “AI-washing” — slapping the AI label on their products with little substance behind it — the competition for funding has only grown fiercer. Many VCs say the current environment reminds them of the early dotcom boom in the late 1990s.
“There are a tremendous number of companies out there that will fail,” predicts Nathan Benaich, founder of boutique VC firm Air Street Capital and co-author of the annual State of AI report. He estimates that of the thousands of AI startups in existence, only 5-10% will generate real venture-scale returns. “Many that fail will do so because they never find product-market fit, and the technology just isn’t useful despite the hype,” Benaich says.
So in a crowded field, which AI startups seem poised to break out from the pack? Based on the funding raised, caliber of investors attracted, traction gained, and competitive positioning, here are some of the early leaders in key AI battlegrounds:
Generative AI
With the viral popularity of AI chatbot ChatGPT, generative AI has become the hottest area of startup investment and activity. The technology, which can produce human-like text, imagery, audio and video based on prompts, is being applied to use cases like content creation, coding, design, gaming and more.
Leading the charge is Anthropic, the company behind ChatGPT rival Claude and one of the most well-funded AI startups with over $700 million raised to date. Founded by researchers from OpenAI, Google Brain and academia, Anthropic has pioneered “constitutional AI” techniques aimed at making chatbots safer and more reliable. The startup recently inked a deal to incorporate its AI models into DuckDuckGo, a privacy-focused search engine.
Other notable generative AI startups include:
- Stability AI ($101M raised): Makes open source text-to-image generator Stable Diffusion
- Jasper.ai ($125M): Offers an AI content platform for marketing/sales teams
- Hugging Face ($166M): Created an interoperable hub for thousands of AI models
Enterprise AI
For many startups, the clearest path to generating real revenue from AI is by selling to other businesses. Enterprise AI platforms aim to help companies leverage machine learning for uses like automating workflows, gleaning insights from data, and improving customer service.
One of the buzziest enterprise AI startups is Databricks, which has raised $3.6 billion in funding to make its data and AI tools the standard for businesses. Co-founded by the creators of Apache Spark, Databricks lets companies feed their data into easy-to-use AI systems to generate predictive insights. It’s now valued at $38 billion.
“Databricks has executed extremely well in a massive market,” says investor Dharmesh Thakker of Battery Ventures. “Every large company is looking to implement AI and analytics to stay competitive, and Databricks provides the picks and shovels to do that.”
Other well-funded enterprise AI startups include:
- DataRobot ($1B raised): Automated machine learning platform to build predictive models
- Dataiku ($847M): Data science/machine learning platform for businesses
- Gong ($584M): AI-based revenue intelligence for sales teams
Autonomous Systems
Some of the most ambitious AI startups are building autonomous robots and vehicles guided by machine learning. The goal is to automate tasks like last-mile delivery, warehouse logistics, construction, agriculture, and eventually passenger transportation.
While self-driving cars tend to get the most attention, some investors believe autonomous trucks will be the first to market at scale. Leading the pack is TuSimple, which has raised over $2 billion to develop autonomous trucking technology. The company currently operates a fleet of 50 self-driving trucks, with plans to expand to 150 trucks by year-end.
“What makes TuSimple unique is they are laser-focused on the specific challenges of long-haul trucking,” says analyst James Morra of PitchBook. “By narrowing their scope vs. tackling all of passenger AV, they’ve been able to make rapid progress.”
Other autonomous systems startups to watch:
- Nuro ($2.1B raised): Self-driving delivery robots for last-mile logistics
- Skydio ($481M): Autonomous drones for enterprise/defense
- Built Robotics ($112M): Self-driving construction vehicles
AI Chips
As AI workloads become increasingly computationally intensive, a new breed of specialized semiconductors has emerged to provide the horsepower. These next-gen AI chips promise order-of-magnitude improvements in performance and efficiency compared to traditional CPUs and GPUs.
One of the most heavily funded AI chip startups is SambaNova Systems, which has raised over $1 billion to develop its “dataflow” processors optimized for AI. Founded by Oracle and Sun Microsystems veterans, SambaNova has already inked deals to power AI supercomputers for the U.S. Department of Energy and the U.K.’s Met Office.
“SambaNova built a chip from the ground up for AI, and developed a full software stack to match,” says investor Matt Murphy of Menlo Ventures. “It’s a holistic, systems-level approach vs. just developing a point solution.”
Other significant AI chip startups include:
- Graphcore ($978M raised): Intelligence Processing Unit (IPU) chips for machine intelligence
- Groq ($367M): Tensor Streaming Processor (TSP) architecture for AI
- Mythic ($200M): Analog compute-in-memory chips for edge AI
AI Healthcare
Medicine is poised to be one of the biggest beneficiaries of artificial intelligence. AI and machine learning can help analyze medical images to detect diseases earlier, discover new drugs by predicting molecular activity, and surface insights from vast troves of patient data.
Leading the charge in AI healthcare is Viz.ai, which has raised over $250 million for its AI-powered platform for medical imaging. Viz.ai’s algorithms analyze CT scans to quickly detect early signs of stroke, enabling faster treatment. The company has approval from the U.S. Food and Drug Administration and its tools are used in over 1,000 hospitals.
“Viz.ai is a great example of AI being applied to a specific problem that really moves the needle on patient outcomes,” says investor Vijay Pande of Andreessen Horowitz. “There’s a massive opportunity for AI to reduce costs and improve quality across the healthcare system.”
Other hot AI healthcare startups:
- Insitro ($743M raised): Machine learning for drug discovery and development
- Komodo Health ($314M): Healthcare map platform powered by AI
- Tempus Labs ($820M): AI platform for precision medicine
Of course, in a field as hyped as AI, the risk is that the market gets ahead of itself. Even if the technology proves truly revolutionary, it will take time for real-world applications and business models to catch up to sky-high expectations. Many of today’s AI startups are likely to fizzle out long before then.
“In the short term, there’s going to be a lot of hype and fluff,” says Benaich. “But in the long run, the potential for AI to transform entire industries is very real. The challenge for startups is to survive the hype cycle and be well-positioned to become category winners as the technology matures.”
Still, with so much capital flowing into the space and credible players like Google, Microsoft, Amazon and Apple now fully committed to AI, it’s becoming harder for startups to differentiate themselves. As the market matures, winners will likely be determined not just by technical expertise, but the ability to achieve deployment at scale and build strong brands and sales channels.
“The bar for AI startups is getting higher,” says Sethi of Tribe Capital. “It’s no longer enough to just have cool tech. You need to prove you can turn it into a real business.”
The race is on to see which startups can meet that challenge and secure positions as the enduring giants of the AI era. Fortunes will be made and lost in the years to come as the hype gives way to real substance. While the ultimate outcome is far from certain, the AI gold rush shows no signs of slowing down anytime soon.
Here are 60 AI funding providers for startups along with their contact information:
- Y Combinator (https://www.ycombinator.com/contact/)
- Andreessen Horowitz (https://a16z.com/contact/)
- Khosla Ventures (https://www.khoslaventures.com/contact)
- Greylock Partners (https://greylock.com/contact/)
- Accel (https://www.accel.com/contact)
- Sequoia Capital (https://www.sequoiacap.com/contact/)
- New Enterprise Associates (NEA) (https://www.nea.com/contact)
- Intel Capital (https://www.intelcapital.com/contact/)
- Google Ventures (GV) (https://www.gv.com/contact/)
- Bessemer Venture Partners (https://www.bvp.com/contact)
- Lightspeed Venture Partners (https://lsvp.com/contact/)
- First Round Capital (https://firstround.com/contact/)
- Data Collective (DCVC) (https://www.dcvc.com/contact.html)
- Lux Capital (https://www.luxcapital.com/contact/)
- General Catalyst (https://generalcatalyst.com/contact)
- Founders Fund (https://foundersfund.com/contact/)
- Emergence Capital (https://www.emcap.com/contact/)
- Amplify Partners (https://www.amplifypartners.com/contact/)
- The AI Fund (https://theaifund.com/contact/)
- Microsoft’s M12 (https://m12.vc/contact/)
- Samsung NEXT (https://samsungnext.com/contact/)
- Work-Bench (https://www.work-bench.com/contact)
- Hetz Ventures (https://www.hetz.vc/contact)
- SV Angel (https://svangel.com/contact)
- Techstars (https://www.techstars.com/contact)
- 500 Startups (https://500.co/contact/)
- Index Ventures (https://www.indexventures.com/contact)
- Zetta Venture Partners (https://www.zettavp.com/contact.html)
- Costanoa Ventures (https://costanoavc.com/contact)
- Point72 Ventures (https://p72.vc/contact/)
- Pillar VC (https://pillar.vc/contact)
- Initialized Capital (https://initialized.com/contact/)
- Madrona Venture Group (https://www.madrona.com/contact/)
- Basis Set Ventures (https://www.basisset.ventures/contact/)
- Kindred Ventures (https://kindredvc.com/contact/)
- Glasswing Ventures (https://www.glasswing.vc/contact)
- Schematic Ventures (https://www.schematicventures.com/contact)
- Deep Ventures (https://deepventures.com/contact/)
- Sinai Ventures (https://sinaivc.com/contact/)
- Root Ventures (https://root.vc/contact/)
- Spark Capital (https://www.sparkcapital.com/contact)
- Felicis Ventures (https://www.felicis.com/contact)
- SignalFire (https://signalfire.com/contact/)
- Fenox Venture Capital (https://fenoxvc.com/contact/)
- Wing Venture Capital (https://www.wing.vc/contact)
- Thrive Capital (https://thrivecap.com/contact)
- DFJ Growth (https://www.dfjgrowth.com/contact)
- Playground Global (https://playground.global/contact/)
- AME Cloud Ventures (http://www.amecloudventures.com/contact/)
- AI Capital (https://aicapital.ai/contact/)
- Redpoint Ventures (https://www.redpoint.com/contact/)
- CRV (Charles River Ventures) (https://www.crv.com/contact)
- Blumberg Capital (https://blumbergcapital.com/contact/)
- True Ventures (https://trueventures.com/contact/)
- Bold Capital Partners (https://boldcapitalpartners.com/contact/)
- Canaan Partners (https://www.canaan.com/contact/)
- Section 32 (https://www.section32.com/contact)
- Vertex Ventures (https://www.vertexventures.com/contact-us/)
- Norwest Venture Partners (https://www.nvp.com/contact/)
- Gradient Ventures (https://www.gradient.com/contact/)
These venture capital firms and investment entities have a track record of funding AI startups at various stages. Visit their websites and use the provided contact information to get in touch with them and learn more about their investment criteria, portfolio companies, and how to pitch your AI startup for potential funding opportunities.