AI: Startup Vs Incumbent Value

AI: Startup Vs Incumbent Value

In the realm of AI, the distribution of value between startups and incumbents has been quite uneven. Surprisingly, the majority of the value generated from AI has gone to incumbents, despite the significant activity and innovation happening in the startup space. This stands in stark contrast to previous waves of technological advancements, such as the internet and mobile, where startups reaped a large portion of the value.

During the internet wave, companies like Google, Amazon, Paypal, and Facebook emerged as successful startups, capturing a substantial share of the value. However, incumbent players like Microsoft, Apple, IBM, and Oracle also managed to extend their dominance onto the internet and secure a portion of the value. The split between startups and incumbents in this case was roughly 60:40 or 70:30.

Similarly, the mobile wave saw incumbents like Apple and Google taking the lion's share of the value, with every mobile version of an incumbent's app gaining significant traction. Nonetheless, startups like Whatsapp, Uber, and Instagram managed to carve out their niches and capture a considerable portion of the value. The split between startups and incumbents in the mobile space was around 20:80.

In contrast, the crypto industry has been almost entirely dominated by startups. Bitcoin, Ethereum, Coinbase, Binance, and FTX, among others, have largely driven value creation in this space, with minimal involvement from existing financial services or infrastructure companies.

When it comes to AI, the story has been similar to the internet and mobile waves, with incumbents like Google, Facebook, Tiktok, Netflix, and Amazon making significant strides in AI applications. Startups in the AI space have often faced the challenge of overcoming the distribution, capital, and product moats of incumbents. To succeed, startups need to build products that are significantly better than what incumbents offer or target untapped customer segments and distribution channels.

One possible reason for incumbents' success in the AI space is their data advantage. However, as companies increasingly leverage the broader internet as a training set and adopt models that work well with smaller data sets, this advantage may diminish over time.

While many AI startups in the past focused on challenging incumbents or operating in hard markets like education and healthcare, this current wave of AI feels different. The speed of innovation in various AI areas has been remarkable, and the technology itself has become significantly stronger. This means that startups now have a better chance of creating products that are 10 times better than what incumbents offer.

GPT-3, although useful, hasn't yet sparked the creation of large-scale businesses by startups. However, a model that is 5 to 10 times better than GPT-3 could pave the way for a new ecosystem of startups while enhancing existing incumbent products.

Unique to this wave of AI startups is the emergence of infrastructure-centric companies with widespread adoption and rapidly growing usage. OpenAI, Stability.AI, Hugging Face, and Weights and Biases are among the notable players in this space. Their presence provides startups with greater access to AI technologies and fosters a more robust ecosystem.

Furthermore, there are several areas where AI can bring significant value. Highly repetitive, highly paid tasks like coding, marketing copywriting, and image generation for websites can greatly benefit from AI-powered workflow tools. The ability to summarize or generate text and images in a high fidelity manner opens up new possibilities for product applications.

However, it's crucial to avoid the trap of using AI as a solution in search of a problem. Startups must identify real end-user needs and untapped markets that can truly benefit from the advancements in AI technology.

In conclusion, the future looks promising for startups in the AI space. After years of working directly on AI products or investing in them, it feels like startups are finally poised to reap substantial value from AI. The rapid pace of innovation, the emergence of infrastructure-centric companies, and the ability to create products that are significantly better than incumbents' offerings all contribute to a bright future for AI startups.

Actionable Advice:

1. Focus on building products that are at least 10 times better than what incumbents offer. This will help you overcome their distribution, capital, and product moats.

2. Identify actual end-user needs and untapped markets that can benefit from AI technology. Don't fall into the trap of using AI as a solution in search of a problem.

3. Leverage AI-powered workflow tools to automate highly repetitive and highly paid tasks. Look for areas where AI can enhance existing workflows and provide substantial value.

Exciting times lie ahead for startups in the AI space, and with the right approach and a deep understanding of customer needs, success is within reach. So, let's embrace the opportunities that AI brings and usher in a new era of innovation and value creation.