5 AI trends for 2025: The next wave is coming

Source: Quantum

While writing this post, I was thinking that instead of writing “what to expect”, it would be easier to write “what not to expect from AI in 2025”! For a technology that is making progress in almost every field at the same time, how can you pick 5 areas? To narrow it down and hopefully make it more interesting, I decided to choose trends that are not directly related to the development of ChatGPT or its competitors. It is safe to say that these trends will grow, and these applications and the companies behind them will do their best to make these applications a solution to all possible problems.

Here are 5 AI trends for 2025 (in no particular order):

Trend 1: Agents are everywhere

You may have heard the term Agentic AI. While AI has always been about learning patterns, AI has evolved to the point where it can (a) learn patterns from data (b) generate new content based on those patterns, and (c) act on those patterns. When these three come together, you have an AI agent—a piece of software that can learn, create actions, and execute them. Expect to see more developments in this area in 2025.

Trend 2: Transformation of the Education System

There has been a lot of discussion about whether AI will encourage cheating, replace teachers, or otherwise fundamentally affect how students learn. While all of these are critical, another force is emerging that is just as important, if not more important. This year, there has been growing evidence that recent graduates are having trouble finding jobs because of AI-driven skills and the economy. This raises questions not only about how students learn, but also about what they learn. The economic pressures of a declining job market will force graduates, and ultimately the institutions that train them, to confront new demands on their employees. Students will need to adapt first, upskilling in a variety of ways, and institutions will need to follow. I expect we will start to see these changes in 2025.

Trend 3: AI in Science

Two of the 2024 Nobel Prizes in Science will be for AI. This should be a wake-up call: AI in science is here to stay. It’s also worth noting that while the world’s attention and imagination are focused on generative AI, billions of dollars are pouring into AI’s scientific applications, with new announcements coming every day, from space exploration to medical advances. It’s also worth noting that despite all this investment and progress, data suggests that AI-discovered drugs have about the same success rate in Phase II clinical trials as other drugs, with the caveat that some of these drugs are already “known” in some form. As of this writing, I have not seen any news of AI-generated drugs being approved by the FDA. What does this combination tell us? It tells us that the potential is huge, but it has yet to be fully realized.

Trend Four: Data Mining

Sceptics have long predicted that AI will run out of data, while others have refuted this. What seems to be consistent in these predictions is not the existence of data, but the increasing difficulty of obtaining high-quality and ethically produced data. I expect this to be a trend in 2025. The untapped data, especially about our physical environment, is still enormous. However, large language models have already mined much of the easily accessible data. Expect to see an increasing amount of effort in 2025, whether it’s through commercial contracts to acquire data, labeling systems to curate untapped data, or deploying more sensors. Add to that the aforementioned AI trends in science, and we can imagine that efforts to mine scientific data will accelerate.

Trend 5: Robotics

AI has made inroads in all areas where problems can be solved with software (e.g., email, content creation, MRI analysis, etc.). In all of these areas, AI has driven cost savings and job disruption. Robotics brings AI into the physical realm—whether it’s manufacturing, surgery, agriculture, or space exploration. The applications of combining AI with physical automation are almost endless. In 2025, we can expect to see existing trends in this area expand and gain wider public attention.

In summary

Over the past year, large language models and generative AI have advanced rapidly, seemingly capable of solving any basic task. In 2015, we can expect to see the next wave as deeper impacts on specific sectors and institutions, as well as convergence with other technology waves, come into focus.