AI Startup Founders: Is Your Use Case Durable?

In the rapidly evolving landscape of Artificial Intelligence, numerous AI application startups have emerged, each striving to carve out a niche by leveraging AI's capabilities to solve existing problems. However, the critical question that many of these startups need to address is the durability of their use case.

The Use-Case Durability Test

Many AI startups focus on solving past problems with the enhanced capabilities that AI offers, often providing solutions that are 2x to 10x better. While these solutions may offer immediate improvements, the long-term viability of the use case is often overlooked. To assess this, founders should ask themselves:

• Is the use case growing or shrinking?
• Is this use case relevant over the next 2 years?
• **What would happen to this use case over the next 5+ years? **

Real-World Example: SEO Headline Generation

Consider a startup that excels in generating headlines for SEO, significantly increasing click-through rates. A crucial question to ask is whether SEO, as we know it today, will remain relevant in the next three years. If the answer is no, the startup must consider how to pivot from headline generation to other related products or services.

Headline generation could serve as a landing product, opening doors to selling other products to the same customer base. The key is to have a unique view of the future and to position the startup to capitalize on emerging trends rather than relying solely on current needs.

Why Use-Case Durability Matters

Startups are inherently about the future, not the present. To succeed, founders must anticipate future trends and position their companies to capitalize on them. This forward-thinking approach is especially critical in the fast-paced world of AI.

The Challenge of Solving Yesterday's Problems

Many AI startups fall into the trap of solving yesterday's problems with today's technology. While this can lead to operational efficiency and immediate gains, it often fails the use-case durability test. Disruptive AI technologies can change the problem landscape, rendering existing solutions obsolete.

The Importance of Betting on the Future

Founders must bet on their unique opinions and beliefs about the future. This involves understanding how AI will evolve and how it will impact various industries. By anticipating these changes, startups can create solutions that are not only relevant today but also sustainable in the long run.

Expert Insights and Perspectives

Pruthvi Vikas: Focusing on Enterprise and Mid-Market Solutions

According to Pruthvi Vikas, startups targeting enterprise and mid-market clients often don't have the luxury to be overly selective. While the initial use case may evolve, the customer remains a constant. The strategy should involve:

• Service-oriented approach: Grabbing the current use case.
• Tactical diversification: Expanding into other use cases.
• Finding repeatability: Identifying patterns and scalable solutions.
• Productization: Turning repeatable solutions into tangible products.

Murtuza Kutub: Integrating AI into Existing Products

Murtuza Kutub emphasizes the importance of integrating AI in a way that wows customers, rather than merely wrapping existing products with an OpenAI interface. Companies like Zapier are setting the standard for seamless AI integration. Startups that simply offer an OpenAI wrapper are likely to face challenges.

Puneet Kataria: Spotting Opportunities in Disruptive AI

Puneet Kataria highlights that solving yesterday's problems with AI can provide operational efficiency but fails the durability test. AI is so disruptive that it is going to change the problem landscape altogether. Founders must bet on their opinions and beliefs about the future.

Yogesh Tomar: The Next Generation of AI Winners

Yogesh Tomar shares his take on what the next generation of winners in the AI age might look like. He emphasizes the importance of understanding the brief history of computing and human progress to anticipate future trends.

Sandeep K: Reshaping the Problem Itself

Sandeep K points out that many AI startups focus on solving existing problems with a 10x boost but fail to consider whether the problem will even exist in a few years. He believes that the real winners are not just improving things but reshaping the problem itself.

Conclusion: The Key to Long-Term Success

For AI application startups, the key to long-term success lies in conducting a thorough use-case durability test. By asking critical questions about the future relevance of their solutions, founders can position their companies to thrive in the ever-changing AI landscape. Remember, it's not just about solving today's problems, but anticipating and shaping the future.

Are you ready to give your use case a durability test?