For several years, AI sent the venture capital market into a frenzy. Everyone, especially venture capitalists (VCs), bought into the hype, seemingly sending checks every time someone mentioned AI in a pitch. Valuations have soared, and even the most basic chatbots and AI applications secured funding.
But today, the attitude of venture capitalists has changed dramatically. They are no longer impressed that you have a GPT wrapper. Where is the single vision? Where is the defensibility? Venture capitalists are learning hard lessons from ambitious AI investments that overpromised and underdelivered. This new attitude has rapidly evolved the standard criteria and expectations for securing funding for AI startups.
If you are the tech founder of an AI startup and looking for venture funding in 2026, here are four things to consider before launching your company.
What do venture capitalists want to see from AI startups?
- Evidence of customer buy-in and defense capability, i.e. a moat.
- Superior execution.
- Hire and retain top AI talent.
- Ensure the business is ethical, transparent and ready to be regulated.
More evidence of substance
The barriers to bringing a product to market are the lowest they have ever been. In most cases, you must prove the customer’s interest; this is even more true if you are a new founder. A year ago, businesses were still trying to understand whether AI would be useful. Today, they realize that they cannot afford to sit idly by.
But many questions remain regarding retention, renewal and defensibility. Unlike in the past, a startup landing pilots and generating $1 million in early revenue is no longer a strong indicator of product-market fit or a sustainable business. Investors now want to know what’s going on After you have tested your product. Have you learned anything from customers who have churned? For customers who have unsubscribed, which alternative did they choose and why? Do you have a unique distribution that gives you an unfair advantage in getting your hands on more customers?
Expect VCs to push out $20-$30 million valuations with only a few hundred thousand in revenue and no clear moat. Of course, graduates from top-tier accelerators will have exceptions, as many VCs are still looking for the same pipelines for quality deal flow, but this won’t be common for founders in general.
The bar is higher: Startups must demonstrate not only traction, but also repeatability and defensibility. Venture capitalists no longer care who is first to market with a flashy AI demo. They want to know who is building something that can last, earn trust, and truly reshape the way work gets done.
Explain why someone else can’t do this
Founders who evolved quickly Generative AI have created several new generational businesses. These founders raised a lot of capital from venture capital firms in a frothy market and got results. They can defend their niches because they capitalized and delivered on their promises before the rest of the world.
I speak to hundreds, if not thousands, of tech founders each year who are pitching my fund as they raise their seed round. The one thing that VCs are most interested in, myself included, is founders who effectively explain their competitive advantage by focusing on a few key areas.
1. Unique value proposition
Venture capitalists want to see proof of the specific benefits your AI product offers that your competitors don’t. This needs to go beyond features, as these can be easily imitated, but focus more on tangible results for customers.
2. Differentiation
Highlight the specific differences that make your AI offering superior to others. Is your data proprietary? Is it deeply differentiated from large general purpose LLMs, etc.? ? Do you have exclusive partnerships that others can’t get? Double down on this.
3. Moat
Is your business sustainable? It is crucial to explain what will prevent other competitors from taking over your territory. This again goes back to intellectual properties or deep domain expertise within the team.
Venture capital firms want to back businesses that cannot be easily replicated by a competitor. Many tech founders think their product is one of a kind, but in reality, there are a lot of other companies doing the exact same thing, only better. Whoever does best will get money from venture capital.
Hire top AI talent
You need to hire and retain top AI talent if you want venture capital money. Hiring top AI talent is crucial to business success because it fosters innovation, drives efficiency and provides a competitive advantage in an increasingly AI-driven market. Venture capitalists want to know what you are doing to attract and retain the best AI candidates. Especially as the demand for top AI talent grows faster than ever, this needs to be founders’ number one priority.
As a VC, I can tell you that the field is paying more attention to team members. AI has changed the way we analyze talent. Demonstrate your team’s strengths. What unique backgrounds and expertise set them apart from the sea of talent? Founders need to know that it’s not enough to offer AI talent a high salary and great benefits. The best AI talent is only interested in opportunities where they can truly innovate and make a real impact.
Whether you’re looking for ML engineers or data scientists, make sure you find talent willing to follow responsible AI practices. Of course, it is important to find candidates who can design and deploy scalable ML models on diverse datasets or those who understand model integration. But it’s becoming sadly clear that top AI talent is looking for forward-thinking organizations that operate ethically. AI bias is real. Workplaces and their teams that honor the importance of AI guardrails will organically attract top AI talent.
Be ethical, willing to comply with regulations and transparent
Build thoughtful guardrails that leave room for future regulation has never been more important for AI. Venture capital firms are actively seeking founders who understand the regulatory landscape, proactively engage with emerging standards, and build with ethical foresight. In many ways, being “regulatory ready” becomes as important as product-market fit, as companies that anticipate compliance the challenges will be those that evolve with stability and confidence. We want to know whether or not you are violating any IPs or trademarks and whether your solution will be accepted by your set of customers based on current and future policies.
For example, California (where a large portion of AI companies are based) recently adopted THE Artificial Intelligence at the Border Transparency Actthe first state law to require large AI developers to publicly disclose a safety framework that incorporates widely accepted safety standards and explains a model’s ability to pose and mitigate “catastrophic risks.” More rules and regulations like this will be coming and venture capitalists want to know if your company is ready.
Ethical AI practices are a necessity. Investors now frequently ask tougher questions: How is the model trained? Can your results be audited? What is the mental framework of your model? Companies that can confidently answer these questions are not only better positioned to raise venture capital funds, but also to gain the trust of large corporate clients. In today’s market, founders must create AI that is both ethical and regulatory compliant, providing them with potential new advantages as the landscape evolves.
As AI startups launch venture projects, it is important to demonstrate product-market fit and traction. This is rule number one. We also want to know that you have the best talent working on the product, that your regulatory preparation and ethics are intact, and that you are building a technology company that cannot be easily replicated by your competitors. If you have all of this, there’s a good chance you’ll close your next funding round.