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Today: Jun 12, 2024
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AI startups racing in the dark

1 min read

TLDR:

  • The AI startup landscape is highly competitive, with many companies likely to fail.
  • Corporations are becoming major players in the AI space, posing a significant risk to startups.
  • Growth is essential for startups to defend against competition and attract investment.
  • Create a good product that addresses market needs, is compatible with existing systems, and captures market share.
  • Move quickly in the enterprise sales space and focus on converting experimental projects into products for implementation.

Every AI startup is currently engaged in a fiercely competitive race. While some companies may fail, particularly those that merely build “wrappers” for big players’ algorithms or create AI features rather than everyday use products, the rapid advancements in the AI space pose a threat to even those building proprietary algorithms. The entrance of big tech companies into the race means that a single update from a company like OpenAI can potentially eliminate a startup’s competitive advantage.

Furthermore, corporations are now moving quickly in the AI space too, adding AI capabilities into their existing stacks and becoming ecosystems in themselves. Microsoft, for example, is known for its ability to rapidly develop and deploy B2B solutions, and their Office + Azure offering has even taken market share away from other products, including Atlassian.

Addressing the risk posed by big players and corporations requires a focus on growth. While VCs may prefer startups with unique algorithms, from a sales perspective, the product’s quality and compatibility with a client’s existing ecosystem are more important. By capturing market share with a product that has great usability and addresses pain points, startups can buy themselves time and defenses to develop their own algorithms, expand their product offering, or become an attractive acquisition target.

In the enterprise sales space, moving quickly to the paid demo stage and discussing rollout options with experimental arms within corporations can be beneficial. While these experimental projects can provide impressive brand name references, converting them into implemented products is challenging.

Despite the intense competition and risks, there are opportunities for AI startups. Even in a slow market, there is interest from both clients and VCs. The key is to focus on creating a good product and enjoying the journey.