The AI First Dilemma: Navigating the Hype for Founders and Investors

The pressure to be “AI-first” has never been greater. In industries ranging from healthcare to finance, companies are scrambling to infuse their operations with artificial intelligence (AI) to stay competitive. But what exactly does being “AI-first” mean? Is it about building AI-native products from the ground up, or is it about integrating AI into existing software solutions? The answer isn't clear, and this ambiguity is causing a lot of confusion among founders, buyers, and investors.

The market is telling everyone they need to be AI-first. According to Rock Health, AI-enabled companies secured 54% of digital health funding in 2025, reflecting a significant shift in investment priorities. KLAS Research also noted that the adoption of AI in healthcare organizations increased from under half of respondents to more than two-thirds over the course of 2025. Menlo Ventures and other leading investors have observed similar trends.

Despite this surge in interest and funding, there’s a growing debate about whether being “AI-first” is a sustainable strategy or just a fleeting trend. The stakes are high, and the consequences could be significant for both startups and established companies.

Navigating the AI-First Landscape

There are two distinct categories of companies trying to navigate this new landscape: AI-native companies and software companies looking to integrate AI. Each faces unique challenges and opportunities.

AI-native companies are built from the ground up with AI at their core. They have a head start in terms of technology and innovation, but they must quickly build defensible moats to survive. These moats can include proprietary data, deep workflow integration, and robust integrations that make them difficult to replace. The bar for success is high, as investors are eager to back the next big AI-driven disruptor.

Software companies, on the other hand, have a different set of challenges. Many already own established workflows and have built strong relationships with their clients. They sit squarely within daily processes, have proprietary data, and key integrations that serve as natural barriers to entry. However, they need to figure out how to integrate AI into their existing products without disrupting their core operations.

For software companies, the pressure to become “AI-first” can be overwhelming. But it’s important to recognize that they have a head start. They already own valuable workflows and data, which are essential for building effective AI solutions. The key is to leverage these assets to create meaningful enhancements that provide real value to their users.

The challenge for both types of companies is to build something durable rather than just timely. This means focusing on long-term sustainability and defensibility, not just short-term gains. For AI-native companies, this could mean developing proprietary algorithms and datasets that give them a competitive edge. For software companies, it might involve integrating AI in ways that enhance their existing workflows without alienating their user base.

Points to Watch

As the AI landscape continues to evolve, several key points will be crucial for founders and investors to watch:

1. Market Trends: The market is currently flush with capital, but this could change as more companies enter the space. Founders need to stay agile and adapt to shifting investor priorities.
2. Technology Evolution: AI technology is advancing rapidly, which means that today’s cutting-edge solutions could become obsolete tomorrow. Companies must invest in ongoing research and development to stay ahead of the curve.
3. User Adoption: The success of any AI solution ultimately depends on user adoption. Companies need to focus on creating intuitive, user-friendly products that address real pain points for their customers.
4. Regulatory Environment: As AI becomes more prevalent, regulatory scrutiny is likely to increase. Companies must be proactive in addressing ethical and legal concerns to avoid potential pitfalls.

The rush to become “AI-first” is a double-edged sword. While it offers significant opportunities for innovation and growth, it also comes with risks. Founders and investors need to approach this trend with a balanced perspective, focusing on long-term value creation rather than short-term hype.

Ultimately, the companies that succeed in this new landscape will be those that can effectively integrate AI into their operations while maintaining a strong focus on user needs and sustainable growth.