AI Guides Europe’s Next Phase of Bio-Based Plastics

EU-backed research is testing AI tools to design bio-based plastics faster, with closer attention to performance, regulation and end-of-life impact

4 Feb 2026

Artificial intelligence is moving from theory to early use in Europe’s bio-based plastics sector, as EU-backed research projects explore how data-driven tools could reshape the way new materials are designed and assessed.

Researchers and industry partners are testing whether AI can reduce reliance on slow, trial-and-error development by analysing existing datasets and predicting how new polymer formulations might perform. The aim is to design bio-based plastics that meet functional requirements during use while degrading safely at the end of their life.

Collaborative initiatives such as MAGICBIOMAT illustrate this approach. These projects combine material science with data analytics in research and pilot settings, creating digital models that simulate how polymers might behave in soil, water or outdoor environments. By doing so, developers hope to identify design flaws earlier and shorten development cycles before moving towards commercial scale.

The work comes as regulatory scrutiny of plastics increases and customers demand clearer evidence to support sustainability claims. Designing materials with end-of-life behaviour in mind from the outset is becoming a strategic priority, even though many of the tools remain experimental.

Technology providers such as Digiotouch are supplying data platforms and analytics systems to support this research. Their involvement reflects a broader shift in materials innovation, where progress increasingly depends on how well digital infrastructure connects data, design and production processes.

Manufacturers including Organik Kimya are assessing how AI-generated insights might, over time, align with existing production methods. For now, the focus is on learning rather than deployment, with most applications still confined to pilot environments.

If successful, AI-supported design could help companies respond more quickly to regulatory changes, reduce material waste and improve confidence in emerging bio-based solutions for uses such as packaging and agriculture. However, challenges remain around data quality, model validation and the transfer of insights from laboratory conditions to real-world settings.

Despite these limits, the direction is becoming clearer. AI is emerging as a research enabler within Europe’s circular materials agenda, offering a more systematic way to link sustainability goals with material performance as the sector evolves.