AI continues to be a hot topic as we enter 2024, with company’s reevaluating the technology’s impact and preparing to adapt to the fast-changing landscape.
According to PwC, in 2024, artificial intelligence (AI) will start to fundamentally change how business gets done. It will impact how companies grow revenue, conduct everyday operations, engage customers and employees, build new business models, and more.
Here, experts share their thoughts on the future of AI for 2024:
AI will continue to boom, and we will see adaptations in almost every area of our lives: While it will undoubtedly make our lives easier in many ways, we will see an uptick in error rates because this technology is only as smart as the language it’s been trained on. AI will inevitably replace more people and jobs, but the good news is that it will also create more jobs. In a few years, we will see many IoT devices generating huge volumes of high-cardinality data. With AI, the possibilities are virtually endless, and we are only now starting to explore them. —Jason Haworth, CPO, Apica
AI will force organizations to rethink how they train and develop their junior engineers / prepare their career paths: AI will force engineering leaders to redefine the role of junior engineers as AI automates the basic tasks they perform. A few months ago, proficient developers wrote perfect code, and now AI does. Therefore, developers must become experts in areas like prompt engineering, testing and training large language models, and knowing how to deal with non-deterministic outcomes - a skill even more experienced engineers wouldn’t have had to touch just last year. The industry must prepare for this upcoming crunch by investing in educational initiatives, upskilling programs, and fostering an environment that nurtures talent and promotes continuous learning. —Jim Rose, CircleCI CEO
Expect a paradigm shift from model-centric to data-centric AI: Data is key in modern-day machine learning, but it needs to be addressed and handled properly in AI projects. Because today’s AI takes a model-centric approach, hundreds of hours are wasted on tuning a model built on low-quality data. As AI models mature, evolve and increase, the focus will shift to bringing models closer to the data rather than the other way around. Data-centric AI will enable organizations to deliver both generative and predictive experiences that are grounded in the freshest data. This will significantly improve the output of the models while reducing hallucinations. —Rahul Pradhan, VP, product and strategy, Couchbase
Practice patience through the Trough of Disillusionment: Generative AI is the future, but we are still searching for the optimal application to harness its full potential. Over the next year, we will uncover generative AI’s many flaws and weaknesses. But we can’t give up on the technology—we must be patient while we work through the kinks. The Trough of Disillusionment quickly turns into the Slope of Enlightenment. —Gary Sangha, founder and CEO of LexCheck
Generative AI will unlock the value and risks hidden in unstructured enterprise data: Unstructured data—primarily internal document repositories—will become an urgent focus for enterprise IT and data governance teams. These repositories of content have barely been used in operational systems and traditional predictive models to date, so they’ve been off the radar of data and governance teams. GenAI-based chat bots and fine-tuned foundation models will unlock a host of new applications of this data, but will also make governance critical. Companies who have rushed to develop GenAI use cases without having implemented the necessary processes and platforms for governing the data and GenAI models will find their projects trapped in PoC purgatory, or worse. These new requirements will give rise to specialized tools and technology for governing unstructured data sources. —Nick Elprin, co-founder and CEO, Domino Data Lab
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 have an AI roadmap and to 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. —Jacqueline Woods, chief marketing officer, Teradata
Generative AI’s negative impacts will be hard to manage early on—including job loss, deep fakes, and a deepening digital divide: Although generative AI is reimagining how we interact with machines, there are some immediate concerns that will be particularly challenging in the early years of widespread AI and language model adoption. For a lot of people involved in what we loosely call “knowledge work,” quite a few of their jobs are going to vaporize. Rapid change makes it hard to quickly absorb displaced workers elsewhere in the workforce, and as a result both the private sector and governments will need to step up. Deep fakes are also another hurdle, and we can expect increased attacks on what we humans collectively think of as our reality—resulting in a world where no one can, or should, trust a video of you because it may be AI-generated. Finally, advances in AI will exacerbate the digital divide that has been happening over the past 20-30 years between the “haves and have nots,” and will further increase inequality across the globe. I can only hope that by making information more accessible, this emerging technology leads to a new generation of young adults who better understand the issues and potential, and can counter that risk. —Sridhar Ramaswamy, SVP of AI at Snowflake
AI will advance abstraction in programming: We will see a significant leap in how AI advances abstraction for developers. As developers have looked to increase efficiencies, they have abstracted out the common and mundane tasks. Each new language, framework, and SDK that comes along abstracts another level of tasks that developers don't need to worry about. AI will take abstraction to the next level. AI-powered reference architectures will give developers a jump on starting new projects or lend a hand when solving complex problems. Developers will no longer begin with a blank slate. Instead, AI will help remove the intimidation of an empty page to jumpstart projects and streamline workflows. —Scott McAllister, principal developer advocate, ngrok
AI and ML specialists: demystifying unstructured data: AI and ML will play a pivotal role in deciphering the unstructured data puzzle in 2024. Experts who can harness the power of AI and ML to extract insights from unstructured data, such as social media posts, videos, and customer reviews, will be highly sought after. —Rohit Choudhary, CEO of Acceldata
AI meets the three S’s: Before widespread adoption, AI and LLMs need to be smart, safe and at scale. AI offerings will incorporate computer vision for real-time automated decision-making from video content. With that, companies can use AI for threat detection at public events, video-enabled flight boarding and grab-and-go stores. —Younes Amar, VP of product at Wallaroo.ai