As we step into 2025, R&D organizations are bracing for another year of rapid-pace, transformative shifts. We see several pivotal trends that will shape the research landscape that all R&D leaders should consider. The coming year promises both challenges and remarkable opportunities at the intersection of science and technology:

Rise of Agentic AI

Artificial intelligence continues to evolve at a staggering pace, and we see 2025 marking the rise of AI agents / agentic AI. These autonomous systems are designed to execute tasks—ranging from data analysis to decision-making and operational execution—without human intervention. 

"...AI agents tend to have three different characteristics. AI systems are considered “agentic” if they can pursue difficult goals without being instructed in complex environments. They also qualify if they can be instructed in natural language and act autonomously without supervision. And finally, the term “agent” can also apply to systems that are able to use tools, such as web search or programming, or are capable of planning." (MIT Technology Review "What are AI agents?", July 2024)

While this particular form of AI is still in its early stages, 2025 will still see increased applications of AI agents in R&D but around predictable, repeatable tasks. Their true potential, however, lies in addressing complex, high-stakes problems that require contextual understanding and nuanced judgment, like in drug discovery and development. To ensure these agents perform reliably and ethically, R&D organizations must begin developing new oversight frameworks tailored to the unique challenges of agentic AI. Once validation and supervisory hurdles are overcome over the next several years, AI agents will revolutionize complex R&D processes and accelerate innovation at an unprecedented pace.

For more, read R&D World’s interview with Enthought COO Dr. Michael Connell > AI agents: The next big thing in science — eventually?

Next Generation Surrogate Models

Prediction lies at the heart of R&D. Whether developing new materials or discovering life-saving drugs, researchers depend on predictive models to guide their efforts. An emerging trend in R&D is what Enthought has coined “AI Supermodels”—the next-generation surrogate models designed to enhance the accuracy and efficiency of predictions in research environments. These advanced tools offer a transformative leap in how complex systems are understood and optimized.

Unlike traditional models that often require extensive computational resources and vast datasets, AI Supermodels provide high-precision predictions even with limited empirical data. This capability enables researchers to overcome the constraints of high-dimensional, complex problems that were previously out of reach. By reducing the time and complexity involved in training models, AI Supermodels will expand the scope of what’s possible in R&D—in 2025.

Example schematic. Source: Efficient learning of accurate surrogates for simulations of complex systems (Nature Machine Intelligence, May 2024)

For industries like materials science, chemistry, and pharmaceuticals, the implications are profound. Researchers can simulate and optimize experiments faster, reducing the time to market for innovative products. Moreover, these models enable more efficient resource allocation, allowing teams to focus on high-value tasks rather than repetitive computational processes. AI Supermodels are poised to redefine the boundaries of scientific discovery and product development.

Increased Investments in Digital Transformation

Companies of all industries will continue increasing investments in digital transformation (DX), but many have now learned the expensive lesson that achieving meaningful results requires more than just technological upgrades or adding AI. Many have experienced the common pitfall of confusing incremental improvements with real transformation; therefore, outcomes have failed to meet expectations. As science-driven companies plan their 2025-2026 R&D DX budgets and technology initiatives, many are / will be taking a different approach by focusing on aligning their DX investments with the larger business strategic goals.

Spending on digital transformation technologies and services worldwide (in trillion USD). Source: Statista 2024

Though modernizing tools and processes can and should yield short-term benefits, real transformation involves a fundamental shift in how the organization operates. It’s a continuous journey, where the value grows cumulatively through learning and experimentation. To support this growth, leaders are structuring their 2025 DX budgets more thoughtfully, ensuring that initiatives are adequately funded, balancing short-term needs with long-term objectives. This approach fosters innovation while maintaining organizational focus, ultimately driving sustainable transformation.

For more on the differences between digital transformation and digital enhancement, see blog  > A Starting Decision Framework for Technology Initiatives in R&D