Sequoia Capital
Over the past year, generative AI has moved from the background to the foreground on the AI 50 list. This year it takes center stage as we see the beginnings of major AI productivity gains for both enterprise customers and consumers. Although the majority of AI venture funding in the US in 2023 went to infrastructure – 60% to the largest Large Language Model (LLM) providers – application companies continue to dominate the AI 50 list.
In the meantime, we are starting to see what AI-powered businesses will look like. Today, many are integrating AI into their processes to accelerate KPIs. We see large companies benefiting from integrating AI into their products. The workflow automation platform ServiceNowNOW achieves case avoidance rates of almost 20% with its AI-powered Now Assist. Palo Alto NetworksPANW has reduced processing costs with AI. Hubspot has scaled customer support with AI. And Swedish fintech company Klarna recently announced over $40 million in savings by integrating AI into its customer support. Thousands of companies are now integrating AI into their workflows to increase growth and reduce costs. AI 50 companies enable these rapid improvements.
Tomorrow we expect a redesign of UX and UI around the capabilities of AI. By replicating existing features better and more cost-effectively, entirely new user interfaces are developed to deliver valuable new experiences.
What's new this year?
The big moves in this year's AI 50 list illustrate how generative AI is increasing the productivity of companies and industries. The general business productivity category doubled from four to eight companies this year as they expanded their offerings to meet growing customer needs. The author, who previously worked in our Corporate Marketing category, has developed his product lines to be applicable across all corporate departments. Notion, new to the list, has integrated an AI assistant into its productivity platform and added new features like calendar.
Five productivity apps, OpenAI's ChatGPT, Anthropic's Claude, DeepL, Notion and Tome, now target consumers at the consumer, prosumer and enterprise levels. Photo editor Photoroom, video generation app Pika and game developer Rosebud show that the lines between consumer and prosumer for creative software are blurring. Overall, the number of companies in this category also doubled, from three to six.
This year there are fewer industry categories, but a new industry sector has emerged. Figure in robotics, Tractian in industrial maintenance, and Waabi in autonomous driving are beginning to show how integrating AI software with hardware will transform work in the physical world.
2023 was a strong year for infrastructure overall and included some impressive new entrants such as Mistral, a key competitor in foundation models. In the cloud data platform category, Pinecone and Weaviate demonstrated the importance of vector databases. Meanwhile, Databricks has also moved to join Anyscale, Baseten, Replicate and Together in the inference provider category through its acquisition of MosaicML last year. And LangChain has established itself in a category of its own as a general-purpose application development framework for working with LLMs.
Companies of the future
Previous waves of technological innovation – networking, the Internet and mobile devices – were largely communications revolutions. AI promises to be something different – a productivity revolution more akin to the personal computer that has shaped the future of business and industry.
As more AIs are developed, they begin to work together as networks of AIs. Over the past year, we've seen generative AI extend beyond simple text or code generation to agent interaction. Just as the rise of the PC and then the smartphone increased demand for Internet bandwidth for data transfer, the development of AI agents will drive demand for new infrastructure to support increasingly powerful computation and crosstalk.
We are entering a world where, as Nvidia CEO Jensen Huang says, “every pixel is generated.” In this generative future, business building itself could become the work of AI agents; And one day, entire companies could function like neural networks.
Sequoia Capital
What we are currently seeing in the application landscape are the first iterations of the tools that will be used by the next generation of companies. We can probably expect these companies to be smaller, but the ease of starting a business means there will be far more of them. New ownership and management structures make starting companies faster and more fluid. One day there could be large companies run by a single AI engineer.
Most companies of the near future will not be one-person businesses, but they will have different needs and different vulnerabilities than today's companies. You need enterprise products that can solve challenges in knowledge management and content generation, as well as trust, security and authentication. The amount of software these companies will use will increase and change, with code generation and software agents enabling greater customization and rapid iteration.
To win the hearts and minds of the companies of the future, founders must answer some critical questions. What types of products will these companies produce? What types of infrastructure and applications will they need? How will the workforce change? How will distribution patterns and value capture change? What proportion of their total addressable market will be humans versus autonomous AI agents?
What's next
Productivity revolutions like the AI revolution are driving down costs. Technological advances this century have radically reduced the cost of hardware, but the cost of human-provided services, from healthcare to education, has skyrocketed. AI has the potential to reduce costs in these important areas and make them more accessible and affordable. These changes must be made responsibly to mitigate job losses and spur job creation. AI will allow us to do much more with less, but we will need both government and private efforts to retrain and empower everyone.
Sequoia Capital
AI has the ability to transform cost structures and increase productivity in some of the most important areas of our society. It has the potential to lead to better education, healthier populations, and more productive people by abstracting everyday work and allowing us to focus our attention on more important issues and better tools for the future. It can give more people the freedom to tackle more problems, creating a better society.
The AI 50 2024 captures this growing scope of AI. The list contains applications that are more general than ever, and we expect it to expand in both depth and breadth in the coming years. 2024 is actually just the beginning.
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