Early-Stage AI Companies to Watch in 2026

Artificial intelligence is entering its fourth year as the most talked-about force in business. Since ChatGPT’s launch in 2022, AI has upended and reshaped workflows in countless industries, and continues to dominate boardroom conversations and investor strategies. This year, a new wave of early-stage startups is emerging with bold ideas and transformative technologies. They aren’t looking to replicate the world-altering success of OpenAI, but rather to leverage technological advancements in AI to solve niche issues. For example, Tim Tully, an investor at venture capital giant Menlo Ventures, predicts that AI-powered sales and go-to-market tools will break out in 2026. Still, the difference between startups that succeed and those that fail will be a strong intuition for product management—and for founder tenacity. And speaking of founder tenacity, Kulveer Taggar’s venture fund, Phosphor Capital, invests exclusively in “top founders in each Y Combinator batch.” (His cousin, Harj Taggar, is a managing partner at YC.) A two-time alum of YC, Kulveer Taggar is looking for “customer-obsessed” founders and businesses that remind him of the startup accelerator’s most successful alumni, like Airbnb and Stripe, when they were just starting. Based on their suggestions and Inc.’s research, here are some early-stage AI companies poised for game-changing success. 1. OpenEvidence Founder: Daniel Nadler Location: Miami Founded in 2022 by Canadian entrepreneur Daniel Nadler, OpenEvidence produces a medical AI assistant often dubbed “ChatGPT for doctors.” The company’s platform uses large language models specifically trained on massive amounts of clinical data, medical research, and electronic health records to provide real-time recommendations, diagnostic support, and administrative assistance to health care professionals. Since its founding, OpenEvidence has secured major partnerships with several large hospital systems across the United States and Europe, allowing it to rapidly test and refine its models in clinical settings. The company says that its medical search engine is used on a daily basis by more than 40 percent of physicians in the U.S. today. In January 2026, OpenEvidence announced that it had raised a $250 million Series D round, at a valuation of $12 billion. OpenEvidence wrote in a statement that the new funding will be used “to invest heavily in the R&D and compute costs associated with the multi-AI agentic architecture of OpenEvidence, which provides the highest quality and most accurate medical answers of any system in the world.” Over the past 12 months, OpenEvidence has raised a grand total of $700 million. 2. AMI Labs Founder: Yann LeCun Location: Paris Yann LeCun, the acclaimed NYU professor, 2018 Turing Award winner, and former chief AI scientist at Meta, has launched his first startup, making him one of the most-watched figures in AI. Announcing his December 31 departure from Meta via LinkedIn, LeCun revealed plans for a new company dedicated to his research into advanced machine intelligence (AMI). The company’s goal, he wrote, is to drive the “next big revolution in AI: systems that understand the physical world, have persistent memory, can reason, and can plan complex action sequences.” These systems are also called “world models,” and they will be where LeCun focuses his attention. FIVE AI TRENDS WILL SHAPE IT IN 2026: Our report unpacks the macro trends shaping AI and ties each one back to IT strategy, governance, and transformation. 1. Foundational AI principles will rewrite organizational DNA Enterprises will develop their own guiding AI principles to address rising AI risk and align their AI strategy around core organizational values. 2. From copilots to vibe coding: AI will continue to reinvent IT New categories of enterprise AI tools will emerge, propelling many organizations toward a crucial decision: AI platform or best-of-breed AI tools? 3. Agentic AI will come of age and power the exponential enterprise Although current adoption of agentic AI is low, it will grow faster than generative AI, powering exponential growth and change across organizations while bringing new opportunities and risks. 4. Risk management will be the price of admission for AI The potential risks of new AI applications will drive organizations to adopt AI risk management programs, even in jurisdictions with no regulatory requirement. 5. AI will hang in the balance between freedom and control AI sovereignty will become top of mind for regulators, but legislative policies will develop in a disjointed fashion around the world.