Last year generative AI moved from the background to the foreground of the AI 50 list. This year it is front and center as we see the beginnings of major AI productivity gains for both enterprise customers and consumers. Although the majority of 2023’s AI venture funding in the U.S. went to infrastructure—60% to the biggest large language model (LLM) providers—application companies continue to dominate the AI 50 list.

Meanwhile, we are beginning to see what AI-infused companies will look like. Today, many are integrating AI into their processes as a way to accelerate KPIs. We’re seeing large companies benefit from integrating AI into their products. Workflow automation platform ServiceNow is achieving case avoidance rates of nearly 20% with their AI-powered Now Assist. Palo Alto Networks has reduced the cost of processing expenses with AI. Hubspot has scaled customer support with AI. And Swedish fintech Klarna recently announced over $40 million in run-rate savings by building AI into their customer support. Thousands of companies are now integrating AI into their workflows to see increased growth and decrease costs. AI 50 companies are enabling these rapid improvements.

Tomorrow, we expect to see UX and UI reimagined around the capabilities of AI. Replicating existing functions better and cheaper, will be followed by evolving entirely new user interfaces to deliver valuable new experiences.

What’s new this year?

The big movements in this year’s AI 50 list highlight how generative AI is increasing enterprise and industry productivity. The category of enterprise general productivity doubled this year, going from four companies to eight as they broadened  their offerings to meet customers’ growing demands. Writer, previously in our enterprise marketing category, fleshed out their product lines to apply across all corporate departments. Notion, new to the list, integrated an AI assistant across their productivity platform, and added new capabilities like calendering.

Five productivity apps, OpenAI’s ChatGPT, Anthropic’s Claude, DeepL, Notion and Tome are now catering to customers at the consumer, prosumer and enterprise levels. Image editor Photoroom, video generation app Pika and game-builder Rosebud show that the lines are blurring between consumer and prosumer for creative software. Overall, companies in that category also doubled, going from three to six.

There are fewer industry vertical categories this year, but a new industrial sector emerged. Figure in robotics, Tractian in industrial maintenance and Waabi in self-driving are beginning to show how the integration of AI software with hardware will transform work in the physical world. 

2023 was a strong year for infrastructure overall, and includes some formidable new entrants like Mistral, a major contender in foundation models. In the cloud data platform category, Pinecone and Weaviate demonstrated the importance of vector databases. Meanwhile, Databricks, through its acquisition of MosaicML last year, has also moved to join Anyscale, Baseten, Replicate and Together in the inference provider category. And LangChain has established itself in a category of its own as an all-purpose application development framework for working with LLMs.

Companies of the future

Previous waves of tech innovation—networking, the internet and mobile—have largely been communication revolutions. AI promises to be something different—a productivity revolution, more akin to the personal computer, which shaped the future of business and industry.

As more AIs are developed, they will begin to work together as networks of AIs. In the past year, we have seen generative AI extend beyond simple text or code generation to agentic interaction. Just as the rise of the PC and then the smartphone drove demand for internet bandwidth to transmit data, the evolution of AI agents will drive demand for new infrastructure to support ever more powerful computation and crosstalk.

We are entering a world where, as Nvidia CEO Jensen Huang says, “every pixel will be generated.” In this generative future, company building itself could become the work of AI agents; And someday entire companies might work like neural networks.

What we are seeing in the application landscape now 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 company generation means there will be far more of them. Company formation will become faster and more fluid, with new ownership and management structures. Someday, there may be large companies operated by a single AI engineer.

Most companies of the near future will not be one-person companies, but they will have different needs and different pain points than the companies of today. They’ll require enterprise products that can solve challenges in knowledge management and content generation, in trust, safety and authentication. The amount of software these companies will run will expand and change, with code generation and software agents enabling more customization and fast-cycle iteration.

To win the hearts and minds of the businesses of the future, founders will need to answer some critical questions. What kinds of products will these companies make? What kinds of infrastructure and applications will they need? How will the workforce change? How will patterns of distribution and value capture change? What share of their total addressable market will be composed of people vs autonomous AI agents?

What’s Next

Productivity revolutions like the AI revolution drive costs down. Technological progress this century has radically driven down the cost of hardware, but the costs of services delivered by humans, from healthcare to education, have skyrocketed. AI has the potential to reduce costs in such crucial areas making them more accessible and affordable. These changes need to be made responsibly to mitigate job loss and drive job creation. AI will enable us to do much more with less, but we will need both government and private efforts to retrain and empower everyone.

AI is positioned to change the cost structure and increase productivity in some of the most crucial areas in our society. It has the potential to lead to better education, healthier populations and more productive people by abstracting away mundane work and allowing us to focus our attention on more important issues and better tools for the future. It can free up more people to tackle more problems to create a better society. 

The 2024 AI 50 captures this broadening scope of AI. The list has applications that are more general than ever, and we expect it to expand in both depth and breadth in the coming years. 2024 is really just the beginning.