The Value of AI: Startups vs. Incumbents

The Value of AI: Startups vs. Incumbents

In the world of technology and innovation, there is often a constant struggle between startups and incumbents to capture the most value from emerging trends. This is particularly true in the field of artificial intelligence (AI), where the distribution of value has been somewhat unexpected.

Looking back at previous waves of technological advancements, such as the internet and mobile, we can see a pattern emerge. In the early days of the internet, the majority of the value went to startups like Google, Amazon, and Facebook. However, incumbents like Microsoft and IBM were also able to extend their franchises onto the internet and capture a significant portion of the value.

A similar trend was observed in the mobile space, where incumbents like Apple and Google dominated, but startups like WhatsApp and Uber were able to carve out their own share of the market. The split between startups and incumbents in these cases was roughly 70:30 in favor of startups.

However, when it comes to AI, the story is quite different. The vast majority of the value has gone to incumbents like Google, Facebook, and Amazon, with very little participation from existing financial services or infrastructure companies. This can be attributed to the fact that AI applications require a data advantage, which incumbents often have due to their vast user bases and access to large datasets.

So, what does it take for a startup to beat an incumbent in the AI space? Typically, they need to build a product that is 10 times better than what the incumbent offers. This can be achieved by either overcoming the distribution, capital, and pre-existing product moats of the incumbent or by targeting a brand new customer segment or distribution moat that the incumbent cannot serve.

One possible reason why incumbents have been successful in capturing the value from AI is their data advantage. However, this advantage may be diminishing as companies use the broader internet as an initial training set and switch to models that work more efficiently with smaller datasets.

The current wave of AI innovation feels different from previous ones for a few reasons. Firstly, the speed of innovation across many areas is remarkable, making it easier to create products that are 10 times better than what incumbents offer. Secondly, there are a clear set of infrastructure-centric companies with broad adoption and rapidly growing usage, providing startups with access to the technologies they need to compete.

Additionally, there are highly repetitive tasks that can be automated using AI, such as code generation and content creation, which opens up opportunities for startups to build workflow tools that integrate AI features. Moreover, the ability to summarize or generate text and images in a high-fidelity way using AI technology is enabling new product applications that were not possible before.

However, it is important for startups to avoid the trap of building solutions in search of problems. The key is to identify actual end-user needs and unserved markets that will benefit from the exciting technology that AI offers. By focusing on the needs of the end user and creating products that address these needs, startups can finally start to realize real value from AI.

In conclusion, the distribution of value in the AI space has largely favored incumbents over startups. However, with advancements in technology and a focus on addressing actual end-user needs, startups have the potential to capture a larger share of the value in this wave of AI innovation. To succeed, startups must build products that are 10 times better than what incumbents offer and target new customer segments or distribution moats. The exciting times lie ahead for startups in the AI space.

Actionable Advice:

1. Focus on the actual end users' needs: Instead of building solutions in search of problems, startups should identify and address the actual needs of their target audience. By understanding the pain points and challenges faced by users, startups can create products that provide real value.

2. Leverage infrastructure-centric companies: Take advantage of the infrastructure-centric companies that have emerged in the AI space. These companies offer access to technologies and resources that can help startups compete with incumbents. By leveraging these resources, startups can level the playing field and create innovative products.

3. Avoid the hammer-looking-for-a-nail problem: It is essential for startups to avoid building solutions without a clear problem to solve. Instead, startups should identify unserved markets and unmet needs that can benefit from AI technology. By focusing on these areas, startups can create products that have a real impact and capture value.

In the ever-evolving world of AI, startups have the opportunity to disrupt and capture value from incumbents. By leveraging technology advancements, focusing on user needs, and identifying untapped markets, startups can carve out their own share of the AI-generated value. The future holds exciting possibilities for startups in the AI space, and it's time to capitalize on the potential that AI offers.