2023 marked an exciting year for artificial intelligence (AI), not only with the rise of consumer-facing generative AI (GenAI) models but also with enterprise AI that can help businesses scale. Glen Echo Group has been closely following these developments as our clients and partners explore how AI can help them leverage data for growth.

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‍Databricks, a global data and AI company, released its 2024 State of Data + AI report last month, which analyzed usage data from over 10,000 customers on how they improved, implemented and utilized machine learning (ML) strategies for their data management needs. What Databricks found echoes what we have been saying since last summer ― AI is here, and is already an integral part of our world and business practices.

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Key takeaways: 

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This year’s GenAI strategy centers on customizing large language models (LLMs) with enterprise data. 

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Widely accessible LLMs like ChatGPT have continuously showcased that AI is only as good as the data it’s trained on. Businesses have responded to the need for narrow, accurate models by optimizing off-the-shelf LLMs with their own private data rather than using standard models.  

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Companies are exploring how to work with and build proprietary LLMs that fit specific use cases using tools like vector databases. Seventy percent of Databricks customers leveraging GenAI are using tools like retrieval and vector databases to customize models.

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Companies want to know how to use AI.

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The growing popularity of data intelligence platforms shows that companies are seeking to better understand how they use AI internally. Rather than traditional siloed data and AI platforms, data intelligence platforms offer a new way to organize data that companies are gravitating toward. This new category of data platforms uses GenAI to more easily secure and leverage data, and lower the technical bar to create value from it. 

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Highly regulated industries are early adopters.

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Some of the most highly regulated business sectors ― including financial services and healthcare and life sciences ― led the way in embracing AI innovations, keeping pace with and often surpassing their less-regulated counterparts. While highly regulated industries have a reputation for being risk-averse, unified governance solutions, like Databricks Unity Catalog, span all data and AI assets and make it easier for organizations to train and deploy GenAI models on their private data. 

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In human terms? Enterprise AI models are helping the biggest businesses manage massive amounts of data and streamline internal processes while keeping that data secure. 

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Overwhelmingly, businesses spent the last year focused on adapting open algorithms, tailored to specific use cases and proprietary data. Going forward, we can expect that enterprise AI will continue to champion open source models that empower companies to build their own LLMs and protect their data. 

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Policy Implications:

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Industry isn’t new to using GenAI for its internal data practices, and understanding how companies approach implementing AI while protecting data offers valuable insights into where this technology is headed. 

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Meanwhile, lawmakers at the state and federal levels are rushing to regulate AI, even as the technology expands and changes at a rapid pace. What does this mean for the companies currently trying to take advantage of new tools, but may soon be focused on compliance? 

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• Without a federal privacy law, companies will need to be vigilant of the patchwork of state laws that continue to crop up. As some states place more stringent provisions on data, companies will need to be able to respond accordingly.  
• The U.S. Supreme Court has overturned the 1984 Chevron v. Natural Resources Defense Council case and Chevron doctrine. Under the new ruling, courts will be expected to exercise independent legal judgment, without deferring to a federal agency’s interpretation. The result? Companies tracking compliance will need to look to the courts – and Congress – not federal agencies which have traditionally taken up the mantle for regulations. 

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Reports like the Databricks State of Data + AI report can help stakeholders identify major trends for AI development ― and potentially AI regulation. Stay tuned for more resources and expert commentary as the #SummerofAI continues!

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