AI accelerating Finland’s bioeconomy

AI is accelerating the bioeconomy: How Finland is pioneering smarter materials, circular design, and industry collaboration

AI is rapidly reshaping the way we design materials, optimize bioprocesses, and build circular products from renewable sources. At the CLIC Bioeconomy Thematic Group Meeting, experts from VTT and the ELLIS Institute Finland showcased how AI and data-driven methods are unlocking new opportunities for sustainable innovation.

Background

During the first CLIC Bioeconomy Thematic Group Meeting of 2026 held on the 11^th March, three guest expert presentations showcased how artificial intelligence is rapidly transforming materials research, bioprocessing, and circular product design. Together these talks painted a clear picture: AI is becoming a foundational technology for accelerating sustainable innovation in the bioeconomy.

AI enables materials and bioprocess design

In his keynote, VTT Research Professor Anssi Laukkanen introduced VTT’s approach to AI-driven materials and bioprocess development. He described how traditional materials and bioprocess innovation is slow, costly, and fragmented, often involving long empirical cycles and siloed datasets. To tackle these challenges, VTT is developing Materials Acceleration Platforms (MAPs) that integrate high throughput experimentation, computational modeling, and automated data generation with machine learning and AI into seamlessly orchestrated workflows.

At the heart of this shift is the concept of the self-driving laboratory: a hybrid physical–digital research system where AI coordinates experiments, updates models, and makes iterative design decisions. This approach drastically expands the scale and speed at which new materials and bioprocesses can be explored.

Laukkanen illustrated how AI is already helping researchers to e.g. design novel protein-based materials using graph neural networks, navigate vast design spaces for polymer systems like PHAs, and generate thousands to millions of candidate molecules. He also highlighted emerging agentic AI systems: AI agents that can autonomously plan workflows, integrate simulation and lab tasks, and react to natural language instructions. These systems are already being tested in advanced applications at VTT, such as battery materials.

Bridging cutting edge AI research with industry

Mari Avikainen, Corporate Relations Manager at ELLIS Institute Finland shifted the focus to the national landscape by positioning Finland as a European leader in machine learning excellence. ELLIS (European Laboratory for Learning and Intelligent Systems) is a research network created to ensure Europe keeps pace with fast-moving AI developments in the US and China. Finland now hosts one of only two elite ELLIS Institutes in Europe.

Key ambitions of the Finnish institute include attracting world-class AI talent to Finland, coordinating hundreds of researchers across all Finnish universities and VTT, developing new machine learning methods directly relevant to real-world R&D, strengthening European sovereignty in AI tools and platforms and accelerating innovation through industry collaboration. Ten professors were recruited in the first international call, who’s work spans across materials science, biotechnology, machine learning methods, and computational modelling, creating strong synergies with Finnish industry needs.

Applying AI in circular biocomposite development

To offer a real-world collaboration example, VTT Research Scientist Petteri Kokkonen showcased the Business Finland Funded co-innovation project ABiCo, which develops high-performance biobased biocomposites to replace fossil-based primary raw materials. Biocomposites introduce complex engineering challenges such as natural fibre variability, changing recycled streams, and varying component geometry. The result is a highly interdependent system where small changes ripple across materials, processing, performance, costs, and sustainability of the product. Within ABiCo, AI addresses these issues by mapping nonlinear relationships between materials, processes, and properties, and predicts performance based on minimal input data.

Petteri also highlighted the toughest barrier: data. Current workflows are scattered, partly manual, and inconsistent across organizations. Without integrated data systems and traceability, even powerful AI models struggle. The ABiCo project addressed this by identifying six crucial interaction points between materials, engineering, and circularity requirements. The team is now preparing a white paper proposing an integrated modelling approach-essentially a platform ecosystem where AI models, simulations, and sustainability assessments can interact seamlessly.

A new phase for R&D in the Finnish bioeconomy

As seen during the Thematic Event, R&D in Finland is entering a new phase where AI, advanced materials research, and circular economy innovation converge. As AI and data-driven methods mature, they will increasingly act as the connective tissue between data, experiments, industry needs, and system-level sustainability goals – shaping the future of bio-based materials and processes in Finland and Europe.

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