Levi, Ray & Shoup, Inc.

Top AI and Analytics Trends We’re Watching In 2024

2/8/2024 by Steve Cavolick

What will you remember about 2023? For me, 2023 was THE year of AI. ChatGPT stole the headlines early and GenAI took off from there, at first augmenting our artistic creativity, then showing how it could quickly perform tasks such as writing social media content, enhancing online searches, writing code, and improving the user experience. With the number of jobs requiring data science skills expected to rise 36% in the next seven years, it’s not surprising that the various aspects of AI lead most daily news cycles.

It's also clear that crisis is the new norm and that world events affect all of us. Already this year, there have been massive earthquakes and floods, as well as attacks on freighters in key shipping lanes. AI cannot solve those issues by itself, but it can help us by analyzing actionable data and allowing you to pivot when you need to react to local or global conditions.

These are the data and AI trends we think you should be watching in 2024 and which you should consider incorporating into your business transformation strategies. Which other ones are on your list?

Investments In AI Governance Will Spike

The more that organizations invest in AI, the more they will need to spend on governance. Using dirty and biased data to train models can have traumatic effects on individuals and invite legal and regulatory punishments for companies that are not careful. Just ask Rite Aid about the ramifications of this. Governance will need to cover training data, the model, the output of the algorithms, and ideally tie back into overall enterprise risk programs.

Multimodal AI Grows

Multimodal AI is AI that uses multiple types, or modes, of data to make a recommendation on how to solve a problem or predict the next best action. This is different from single modal AI, which is engineered to work with one kind of data, such as traditional row and column data. Multimodal AI can process information in different formats, such as text, video, sound, and speech. One example of a use case for multimodal AI would be in automobile safety, where AI uses images and sounds of drivers and lane position of the car to determine if a driver is asleep and decide what corrective action is required.

More AI Regulation Is Coming

We’ve previously highlighted how individual cities and states are enacting legislation for ethical use and transparency of AI. The U.S. recently introduced a set of national guidelines akin to “Know Your Customer” for financial institutions, mandating cloud providers to verify the identity of non-U.S. account holders. This measure aims to prevent unfriendly foreign states are using cloud services in America to train their AI models. Regulation is one way to protect citizens from inappropriate use of their data or likeness and reduce lawsuits stemming from improper use of IP.

Semantic Layers and Metadata Are Cool Again

Semantic layers are tools that provide a simplified view of complex data, making it easier for non-technical users to access and analyze big data. For example, a manufacturer may have customer information in multiple ERP and inventory systems. Without a semantic layer, a user would need to understand how information is structured and where relationships exist in their repositories in order to answer questions. Semantic layers are part of a meta trend towards self-service AI and BI. With a semantic layer, non-technical workers can easily find and navigate data to create reports and build AI models.

If you are interested in learning more about how LRS can help you find value in your data using modern data architectures and AI, please contact us to request a meeting.

About the Author

Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.