The Future of AI: Opportunities and Challenges

The Future of AI: Opportunities and Challenges

Artificial Intelligence (AI) is rapidly advancing, but with this progress comes unique challenges and opportunities. One overlooked idea is the potential for AI to generate new revenue streams. The growth of generative AI applications, such as image generation, copywriting, and code writing, has been staggering, and infrastructure vendors are likely to be the biggest winners in this market. However, app companies are growing quickly but often struggle with retention, product differentiation, and gross margins.

The promise of generative AI is so great that many model providers have organized as public benefit corporations, issued capped profit shares, or incorporated the public good explicitly into their mission. However, it is unclear whether most model providers want to capture value, and if they should. The demand for proprietary APIs is growing rapidly, and hosting services for open-source models are emerging as useful hubs to easily share and integrate models.

Behind the scenes, running the vast majority of AI workloads, is perhaps the biggest winner in generative AI so far: Nvidia. The company reported $3.8 billion of data center GPU revenue in the third quarter of its fiscal year 2023, including a meaningful portion for generative AI use cases. Infrastructure is, in other words, a lucrative, durable, and seemingly defensible layer in the stack. However, the standard moats tend not to be durable over the long term, and it is too early to tell if strong, direct network effects are taking hold.

One of the biggest challenges for AI is the difficulty in finding structural defensibility anywhere in the stack, outside of traditional moats for incumbents. While there is considerable slack in organizations to perform at much higher levels, the role of leadership is to convert that lingering potential into superlative results. Margins should improve as competition and efficiency in language models increases. Retention should increase as AI tourists leave the market, and there's a strong argument to be made that vertically integrated apps have an advantage in driving differentiation.

In conclusion, while AI presents many opportunities, it also presents challenges and uncertainties. The key to success is to find structural defensibility and develop strategies to keep going even when things are hard. It is not yet clear if there will be a long-term, winner-take-all dynamic in generative AI, but both horizontal and vertical companies are likely to succeed, with the best approach dictated by end-markets and end-users. As AI continues to evolve, we must be ready to adapt and innovate to stay ahead of the curve.