Our friends over at Teradata have prepared a special set of compelling technology predictions for the year ahead. From the company’s point of view 2024 should be quite a year! Straight from the executive suite, you’ll learn about what’s predicted to happen with AI, GenAI, LLMs and much more. Enjoy these special perspectives from one of our industry’s best known movers and shakers.
Hillary Ashton, Chief Product Officer, Teradata
2023 was defined by the rapid rise of ChatGPT. Next year, the focus on AI will shift from eagerness and excitement around large language model AI to what’s next. First, I foresee a massive productivity leap forward through GenAI, especially in technology and software. It’s getting more cost effective to get into GenAI, and there are lots more solutions available that can help improve GenAI solutions. It will be the year when conversations gravitate to GenAI, ethics, and what it means to be human. In some cases, we’ll start to see the workforce shift and be reshaped, with the technology helping to usher in a 4-day work week for some full-time employees. Talk around customer experiences will be dominated by AI’s impact, and we’ll see less focus on business intelligence. We can also expect to see a resurgence around IoT discussions due to AI kicking this into a higher gear with near-sentient robots doing things better and faster. In businesses, cybersecurity will be the “best worst” job next year.
I also expect to see more and better uses of LLMs beyond our work lives. For instance, personal small language models will emerge that will help us with chores such as automating forms for schools and doctors and other time-consuming activities that AI can do faster and more easily. Sadly, GenAI will still be lagging in the “tell me a great joke” and other departments that require a real, functioning brain, so human creativity will remain at a premium. And one other thought … luddites will become their own market segment.
Jacqueline Woods, Chief Marketing Officer, Teradata
2024 will be known as the year of the great data reckoning. For decades, companies have been drowning in data – that unto itself is not a new problem. The critical need to be ready for today’s new information frontier is upon us. It’s known as AI/Gen AI and it promises to deliver incomparable value to those able to leverage its power – to improve productivity, deliver faster innovation, and deliver greater enterprise value across a company. The severe lack of harmonized and trusted data will continue to drive negative bias and poor customer experiences, resulting in underperforming business outcomes. To take full advantage of what AI has to offer, companies must undergo a radical data transformation to ensure their data is clean and pristine. Only then will companies be able to get to trusted data that leads to usable information and valuable insights to accelerate better business performance.
In 2024, the duality of AI will come to life. Everyone is tremendously excited! Boards ask CEOs, “What is your AI strategy?” In turn, those officers are asking their teams to AI roadmap and get started. Like a shiny new toy, and like the folklore of “there’s gold in them hills,” it has the lure and misconception of being able to solve nearly any problem that you can think of. For now, Generative AI and large language models have given us a glimpse of how businesses, industries, and society can be transformed for the better. But with all the excitement comes FOMO – fear of missing out – and the companies that rush to implement AI initiatives without patience and careful planning can risk damaging their corporate reputation. Rather than jumping on the bandwagon, you need to be the driver’s seat of your AI journey. Companies that do so carefully and authentically will be the ones that come out ahead.
Anuradha Mohan, Senior Director, Product, Teradata
2023 has been an exciting year in technology. ChatGPT literally made AI a household name. While large language models (LLMs) have been around for years, they have been esoteric. ChatGPT democratized LLMs overnight. So, there’s been a rapidly growing and broadening understanding of LLMs and excitement around its possibilities. But there’s also a dose of reality in the mix, with increasing discussions around hallucinations and misinformation. In the year ahead, I anticipate the data-centric AI approach will expose that AI has reached a point where data is more important than the models it feeds. We’ll see more enterprises pivoting investments to focus on ensuring quality data to fine-tune their LLM models, rather than continuing to push for marginal improvements in models. 2024 will also be a year of reckoning in which companies that lead with technology rather than taking a data-first approach may find themselves with overengineered and high-cost solutions that may not hit the mark.
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