Introduction: Generative AI is widely considered the fastest moving technology innovation in history. It has captured the imagination of consumers and enterprises across the globe, spawning incredible innovation and along with it a mutating market ecosystem. Generative AI has also caused a copious amount of FOMO, missteps, and false starts. These are the classic signals of technology disruption—lots of innovation, but also lots of mistakes.
In this time of AI disruption, who has shined? In my view, it was those that are building and delivering pragmatic, enterprise-grade solutions. Those who have been invested in and have understood AI for some time. Those who have clear visions and goals for end results. They are AI innovators. With that in mind, I developed a list of companies and products that I felt were the AI innovation leaders of 2023. Two criteria factored heavily into the thinking: (1) Enterprise focused (not consumer), and (2) general availability in 2023. Here are the categories for AI Innovation Leaders of 2023:
- AI Product of the Year
- AI Company of the Year
- AI Stack of the Year
AI Company of the Year
Five nominees floated to the top:
- Databricks
- LangChain
- Microsoft
- Hugging Face
My winner is: Microsoft
Here is why: No company has taken a bigger risk on a promising but untested AI technology partner than Microsoft has done with OpenAI. Many times, such a gamble can go sideways, but Microsoft has masterfully managed its OpenAI relationship since 2022, including the Altman debacle in November. The crowning achievement of that partnership is the successful channeling of OpenAI intellectual property (IP) to produce the Copilot suite of initiatives across a wide range of Microsoft products.
If Copilot continues to roll out smoothly, Microsoft will be nearly single-handedly responsible for making AI into a mass market technology within the next 18 months. Work and personal productivity will rise simply based on Microsoft users alone and fundamentally change the way we interact with software. Its success or even the promise of its success will spur even greater investment by enterprises to leverage the power of AI. For more details, see Microsoft Copilot Will Be the AI Inflection Point.
Microsoft was able to move quickly and sure-handedly forward with generative AI because the company has been heavily invested in AI for more than 10 years. It has built the expertise to not only understand what the technology can do but also how to build the proper guardrails around AI to leverage it responsibly at enterprise scale. For more details, see Under The Hood: How Microsoft Copilot Tames LLM Issues.
A long history and deep experience in enterprise software security factored into those guardrails as well. Another element of Microsoft’s AI investment that has not only helped the company but also the entire market move more quickly is the company’s AI research, particularly around evolving, smaller language models (Orca 2, Phi-2, etc.). For more details, see Microsoft Orca 2: The Biggest Generative AI Breakthrough Since ChatGPT.
Finally, Microsoft’s AI work this year expands beyond the cloud to on-device or edge AI. Millions of personal computers including tablets, laptops, and desktops, run Microsoft operating systems (Oss) and software. Microsoft will be working with its OEM partners to enable on-device AI. One of the more intriguing initiatives in that regard is the launch of Windows AI Studio, a new AI experience to help enterprises and developers jumpstart local AI development and deployment on Windows. For details, see Windows AI Studio: Jumpstart for On-Device AI?
Runner up: Databricks
Here is why: Databricks’ mantra is to bring AI to your data and to unify your data and AI through governance, warehousing, ETL, data sharing, and orchestration. The company was ahead of its time in that regard. The company is, in essence, a data management company purpose-built for AI. Databricks were recently valued at more than $43 billion.
At the company’s Data + AI Summit in June, it was refreshing to hear a company talk plainly and knowledgeably about how enterprises should be thinking about AI. Databricks offers pragmatic guidance at a time when there are a lot of unknowns around generative AI.
Just two examples:
- In his keynote, Databricks CTO Matei Zaharia put up the following graphic: “Problem: Naively adding an LLM assistant doesn’t work.”
- During one keynote presentation, the speaker showed a graphic with the following text: “Modeling techniques will quickly commoditize …. Your data is your competitive edge.” This is contrary to a lot of the conventional messaging around large language models (LLMs), which is, the more data the better.
These examples give you an idea of the approach that was taken during the event. Databricks has the knowledge, culture, and vision to become a leader in helping enterprises navigate generative AI. For more details, see Databricks’ MosaicML Acquisition, LakehouseIQ Launch, Data + AI Summit Show Gen AI Savvy.
Runner up: Hugging Face
Here is why: Since open sourcing the model behind their original teen-focused chatbot, Hugging Face has been a well-regarded but little-known champion of open source development. That all changed in 2023 as the company became a powerhouse player in the generative AI market ecosystem. Throughout 2023, Hugging Face has tirelessly pursued a range of strategic partnerships to grow the AI open source community, including bilateral joint initiatives with AMD, Intel, NVIDIA, Amazon Web Services (AWS), and Dell. There is no question that a significant amount of the rapid innovation in the development AI models in 2023 came from the Hugging Face community.
Runner up: LangChain
Here is why: This indispensable framework enables developers to easily link LLMs to external data sources, which gives the models knowledge of recent data without limitations. One of the challenges of using many LLMs is that their knowledge is limited, the models are trained and retrained periodically, but not in real time. LangChain’s framework addresses this challenge and enables models to produce more accurate results. Launched as an open source project in 2022, LangChain incorporated in April 2023.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Top AI Trends for 2024 | The AI Moment, Episode 7
Google Named Top Adult in the Generative AI Rumpus Room 2023
The Top AI Influencers of 2023
Author Information
Mark comes to The Futurum Group from Omdia’s Artificial Intelligence practice, where his focus was on natural language and AI use cases.
Previously, Mark worked as a consultant and analyst providing custom and syndicated qualitative market analysis with an emphasis on mobile technology and identifying trends and opportunities for companies like Syniverse and ABI Research. He has been cited by international media outlets including CNBC, The Wall Street Journal, Bloomberg Businessweek, and CNET. Based in Tampa, Florida, Mark is a veteran market research analyst with 25 years of experience interpreting technology business and holds a Bachelor of Science from the University of Florida.
