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

Creativity, Exploration, Discovery, and Trust will be AI's Next Steps in 2024

By Steve McMillan, CEO at Teradata

With an understanding of Generative AI and its benefits growing significantly over the past year, enterprises that spent 2023 either racing to build novel AI solutions or contemplating ways to do so, will now be taking a deeper look. That means instead of worrying about "the next best thing," companies will be looking at creating solutions designed to deliver better outcomes for their customers.

I also expect to see companies getting more creative in how they build AI solutions, particularly around finding ways to ensure they have the flexibility to use data at scale without disrupting their day-to-day IT requirements and processes. Also, as regulations around AI continue to climb around the globe, I anticipate a much greater emphasis around trusted, responsible, and ethical AI, along with more clarity on how to achieve each.  

AI projects will be judged on their ability to be transformative 

In 2023, enterprises latched onto the ChatGPT and large language model (LLM) AI craze. In 2024, expect to see AI truly enabling the era of creativity in which the technology will be fundamental in transforming industries. There will be a strong shift to investments in generative AI programs that will be revolutionary (rather than simply novel) and deliver better outcomes. The focus will be on generating solutions that improve the efficiency and effectiveness of internal operations by imbedding AI into the organizations' products and services wherever it makes sense. Doing this well means ensuring the data for AI projects is clean, accurate and trustworthy. As more organizations leverage AI-driven automation and integrate AI and machine learning (ML) into nearly every aspect of their business decision-making, getting the data right will not be a "nice to have," but rather an "absolutely must have."  

I also expect there will be a reckoning around LLMs. Since all types of AI are wholly reliant upon data, companies that don't get the data part right will fail. The same is true for those who invest in generative AI projects without AI expertise, and without deep data expertise. Expect to see more companies investing in upskilling and reskilling their current staff, and bringing in outside talent where they need to. AI talent is at a premium, but it is also needed to ensure AI can be effectively implemented across the organization.  

AI exploration and discovery

As more and more organizations need to unleash data, and open data in particular, the demand for solutions that enable AI exploration and discovery at enterprise scale will grow dramatically in 2024. Emerging options that include serverless query engines that spin up in the cloud with powerful analytics, integrate data with advanced LLMs, and access multiple open table formats in high performance will best address the experimentation needs of enterprises. That's because they will make it easier for data scientists, data engineers, and developers to explore and discover innovative new use cases - on-demand and using data at scale. Expect to see much more enterprise value and breakthrough business results being operationalized with AI thanks to solutions like Teradata's AI Unlimited.

Trust, ethics, and sustainability 

In 2024 it will become increasingly apparent that AI must be trusted, ethical and sustainable. Everyone will be talking about trusted information and trust in information. This is important because without knowing and trusting the data sets used for AI projects, can you really be comfortable with the outputs? The quality of predictions or insights is only as good as the data that informs it. In the coming months, the inception point for AI projects should always start with this: "Can you trust the data? Is it clean and reliable?"  

We'll also see more scrutiny around data ethics. Governments worldwide are calling for greater accountability and transparency with AI, particularly around the data used in training AI systems. Similarly, consumers can and will demand greater visibility into how data is used by AI in decision-making that may impact them for transactions like mortgage loans or insurance policies. To address these issues, more companies will develop AI/ML approval processes that include review by an ethics committee. We'll see more implementations of ethics measures, including monitoring for bias and fairness in AI/ML models and data over time.

Finally, we'll also see more companies thoroughly scrutinizing and addressing the impact of the immense energy usage of AI. Much of this will revolve around having efficient AI models. That will bring about a rise in small and medium language models that can be customized for certain AI applications, while also being accurate, secure, and potentially more efficient.

Final thoughts

As the AI boom cycle continues, the regulatory environment for AI will evolve considerably in 2024 and beyond. Governments at every level, from local to national to transnational, are seeking to regulate the deployment of AI - and I expect we'll see businesses and government come together to create and enforce AI regulation.

Everything I've discussed here is an opportunity. From better defining trusted AI and homing in on customer-centric solutions, to better tools to develop AI solutions, and even regulation, 2024 is already shaping up to be an exciting year.  

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ABOUT THE AUTHOR

Steve McMillan is President and Chief Executive Officer of Teradata and joined the company's board in June of 2020. He has more than two decades of technology experience, and has a track record of transforming enterprise services and product businesses into industry-leading cloud portfolio offerings.