Industry executives and experts share their predictions for 2024.  Read them in this 16th annual VMblog.com series exclusive.

Year of the Data Cloud and True AI Deployment

By Molham Aref, co-founder and CEO of RelationalAI

As we head into the new year, I believe we'll continue to see data clouds take off to fuel AI and analytics. And, we'll finally start to see some true and interesting AI deployments in the enterprise following all the hype around generative AI of the past few years. As more data continues to get moved into the cloud, we can expect to see knowledge graphs leveraged more to eliminate barriers in navigating language modes needed for the rise in AI technology.

2024: the Rise of the Data Cloud to Advance AI and Analytics 

While data clouds are not new, I believe there will be a continued emergence and a clear distinction made between data clouds and compute clouds in 2024. With compute clouds like AWS or Azure, we have had to assemble and stitch together all the components needed to work with AI. So with data clouds, like Snowflake or Microsoft Fabric, users have it all pre-packaged together in a single platform, making it much easier to run analytics on data needed to build AI systems. The rise of the data clouds will offer a better starting point for data analytics and Artificial Intelligence (AI) and Machine Learning (ML).

Extreme Hype Around Generative AI will Diminish, True Generative AI Deployments Will Emerge 

In the new year, we will also begin to see the extreme overhype around generative AI start to diminish. I've been working in, and around, AI since the early nineties, AI has always been prone to be overhyped. Having said that, I think we are going to see enterprises actually deploying generative AI in more measured and meaningful ways. As with most new technology adoption in the enterprise, it's going to take longer for these kinds of AI systems to become part of enterprise software in the ERP or HCM sense, but real value will start to be created next year.  We will be able to calibrate our expectations appropriately once we begin to see its true impact. 

Survival of the Fittest Among AI Players

The venture capital climate has been tough as of late and will be even more so in 2024. I believe we will begin to see a shift in the industry when it comes to the survival of AI startups, as AI startups start to get acqui-hired by the big tech companies for their talent. This has already started to happen and in the last few months we've seen higher than normal venture-funded companies big and small either shut down or quietly get acquired by bigger players.

I think there will be an evolutionary cycle for the companies that can survive the next 18 months or so. It has been said before that some of the best and most valuable companies are usually created in difficult times, like during the 2008 recession and in 2000 when the dot-com bubble burst, as they usually tend to have better products and more disciplined companies. Companies that can run efficiently, be agile, and can adapt quickly to tough situations will be better positioned. At the end of the day, companies that have a strong product, and a demonstrated value proposition, will be in a better position to outrun the competition.

Knowledge Graphs will Help Users Eliminate Data Silos 

As enterprises continue to move more data into a data cloud, they are collecting hundreds, thousands, and sometimes even tens of thousands, of data silos in their clouds. Knowledge graphs can easily drive language models to navigate all of the data silos present by leveraging the relationships between various data sources. In the new year, we will see a variety of established and novel AI techniques that support the development of intelligent applications emerge.  

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