The Moat Paradox: Rediscovering the Competitive Advantage for Success with AI

Building a purely technological moat has been a challenge since its inception big language model (LLM). Due to lower entry barriers to introducing new products to the market and constant fear of becoming obsolete overnight, existing businesses, startups and investors are all trying to find path to a sustainable competitive advantage.

However, this new landscape also offers the opportunity to establish a different kind of moat, building on a much broader product, solving many of the sore points for customers and automating massive workflows from the ground up. to the end.

AI explosion with blast radius constantly increasing since GPT3.5/ went publicChatGPT, was mind-blown. In addition to the discussions around efficiency and risk, businesses in the space find themselves constantly dealing with the question of whether building a tech moat is still possible.

Companies are grappling with the reality of creating a defendable product with significant barriers to entry for new competitors or incumbents. Just like in the past, this will continue to be a necessary ingredient for a new business to grow and become a centaur or unicorn.

Real revolution open source model

The real revolution is not just ChatGPT. The real revolution consists of open source model becomes commercially available — free of charge. Also, solutions like LoRA is allowing anyone to quickly and economically retrain open source models on specific datasets.

The fact is that while OpenAI kicked off the era of “democratization of AI”, the open source community kicked off the era of “democratization of Software”.

What this means for businesses is that now, instead of defining narrow “one-featured” products that solve tough problems that competitors have yet to meet, they can can listen to its customers on a much broader scale and offer diverse products that solve many problems. which seemed unrelated just a year ago. When combined with integrations that fully automate customer workflows, businesses can truly achieve a sustainable competitive advantage.

Put yourself in the customer’s shoes

Simply put, to stand out, a business will need to connect the dots between problems, find solutions that no one has considered, and then find additional dots to connect.

Put yourself in the customer’s shoes. When you are presented with dozens of solutions simultaneously, how do you understand and appreciate the difference? How can you make long-term decisions if you feel there might be more solutions next month?

Customers would rather have a “AI partner” updates its services with the latest technology instead of many small providers.

Executing this strategy requires establishing a broad vision and much shorter goal cycles across the organization during product development and company-wide synchronization. For instance, ML/AI teams should participate in weekly sprints. This will allow them to add new AI features more efficiently and make decisions regarding adding new LLMs or open source models within the same timeframe to improve or enrich services.

Build broader AI products

By building a diverse product rather than focusing on a single feature, startups can achieve this legendary moat as it simplifies product adoption, creates additional barriers entry barriers (for both new entrants and market leaders) and protection against new products. open source model that can be released and destroy a business overnight.

Take an example of the AI ​​replication (ASR) market: Several vendors have entered this market with similar prices and relatively nuanced product differences. Suddenly, this seemingly sleepy market was shaken when OpenAI released Whisper, an open source ASR that showed the potential to disrupt the market instantly but with some significant vulnerabilities. The “incumbents” in the market, who were faced with the above dilemma, decided to launch a new monopoly model and focus some of their messages on the issues of Whisper.

At the same time, others have found ways to bridge these gaps and market a superior product with limited R&D efforts that are receiving incredible feedback from corporate customers and a starting point. with satisfied customers.

Going back to the original question, can one build a moat in the AI ​​space? I believe that with product vision, flexibility and the right execution, businesses can build rich and timely offerings that compete head-to-head with market leaders. Many of the core principles needed to identify great startups are already in the minds of VCs who understand what it takes to recognize opportunities and grow them accordingly. It is important to realize that today’s castles look different than in years past. What you protect is no longer jewels, but entire kingdoms.

Ofer Familier is Co-Founder and CEO at GlossAI.