Thinking through AI as the next new platform opportunity - Version One: Why "Exit to Community"?

Thinking through AI as the next new platform opportunity - Version One: Why "Exit to Community"?

As artificial intelligence (AI) continues to evolve and shape various industries, it presents itself as the next new platform opportunity. However, several important questions arise when considering the potential of AI platforms and the value they bring to companies and developers. Additionally, the concept of "Exit to Community" offers an alternative perspective on the ownership and structure of startups. By exploring these two topics, we can gain valuable insights into the future of AI platforms and the role of communities in business ownership.

The first question that arises when thinking about AI platforms is how much value the underlying platform will keep for itself. History has shown that most platforms tend to extract the bulk of the value, leaving only crumbs for those building on top. This raises concerns about the potential monopolistic power and profit-maximizing strategies of the platform providers. However, the emergence of multiple companies offering similar AI platforms, akin to the competition between AWS, Azure, and GCP in cloud computing, may limit the dominance of a single company. OpenAI, Google, and Facebook, along with other potential contenders, are vying to play significant roles in the AI platform space. This competition could lead to a more balanced distribution of value, benefiting companies building on top of these platforms.

The second question revolves around who will capture most of the new value generated by AI platforms: incumbents or start-ups? Incumbents, with their unique data sets, large user bases, and strong balance sheets, are well-positioned to gain an edge, particularly in the consumer market. However, when it comes to enterprise software, there is an opening for start-ups to create more value for their customers with vertical-specific AI products. By designing interaction models that minimize friction and risk, such as making it easy to involve humans in the loop, start-ups can differentiate themselves. Additionally, leveraging proprietary data in language models and addressing regulatory and privacy constraints can help start-ups protect their brands and create a competitive advantage.

Moving on to the concept of "Exit to Community," it proposes a different approach to the ownership of startups. Rather than traditional exits to venture capitalists or other investors, "Exit to Community" envisions communities becoming the eventual owners of the startups that serve them. This idea emphasizes shared ownership as a destination, acknowledging that it may not always be the starting point. The dominant venture capital model in tech emerged in the late 1970s when pension funds were allowed to invest. However, the laws surrounding business ownership and financing are not equal for all. To make "Exit to Community" a fully available option, policies that support financing business ownership by communities, not just wealthy investors, are needed.

Creating mission-led businesses today can benefit from trusting in those who do the day-to-day work. Community-created and community-governed technology offers a powerful alternative to traditional models. However, it requires time and effort to go against the grain and make community-based technology the default option. By embracing shared ownership and involving communities in the decision-making process, businesses can create more inclusive and sustainable models that benefit both the community and the company.

In conclusion, the rise of AI platforms presents both opportunities and challenges. The distribution of value and the role of incumbents and start-ups in capturing that value are key considerations. Additionally, the concept of "Exit to Community" offers an alternative approach to business ownership, emphasizing shared ownership and community involvement. To navigate these trends successfully, here are three actionable pieces of advice:

1. Collaborate and compete: Companies operating in the AI platform space should seek collaboration opportunities with other players while maintaining a competitive edge. Collaboration can lead to a more balanced distribution of value and prevent monopolistic tendencies.

2. Focus on vertical-specific AI products: Start-ups looking to create value in the enterprise software market should develop AI solutions tailored to specific industries. By addressing industry-specific challenges and providing unique value, start-ups can compete with incumbents.

3. Embrace community-based technology: Businesses should consider involving communities in decision-making processes and exploring shared ownership models. By trusting in those who do the day-to-day work, companies can build more inclusive and sustainable businesses.

By combining these strategies, companies can navigate the evolving AI landscape and build platforms that empower both the platform providers and the companies and developers building on top. The future of AI platforms lies in finding the right balance of value distribution and creating opportunities for shared ownership and community involvement.