How Lithuania is trying to unleash the full potential of science-business cooperation with the help of AI
The responsible organisation
Lithuanian Innovation Centre‘s (LIC) mission is to provide innovation support services by implementing Lithuanian innovation policy. The main strategic goal of LIC is the increasing of Lithuanian international competitiveness by stimulating innovation in business through knowledge-transfer activities. This goal is divided into the following objectives:
- foster capabilities of companies to develop and implement innovation;
- accelerate commercialisation of innovative solutions;
- decrease the risk of innovation implementation.
The problem
The lack of collaboration between science and business has been identified as a significant obstacle to Lithuania’s development in the domains of science, technology, and innovation. Both the Lithuanian government and international institutions, such as the European Commission and the OECD, have underlined this issue, recognising that it hampers country’s economic growth (EC, 2019; OECD, 2016). The lack of comprehensive statistical data to assess the magnitude and extent of this problem is however critical. The need to have reliable figures on the level of science and business integration and possible inefficiencies has become stronger.
The solution and its implementation
The Lithuanian Innovation Centre, in collaboration with Vilantis (a private provider of digital solutions), is developing an AI tool that will allow to visualise through interactive diagrams the extent to which scientific knowledge is integrated in Lithuania’s business ecosystem. The AI tool is built upon a trained neural network and a vector space representation. Its primary function is to gather, process and systemise data related to the scientific knowledge generated by research institutions within the country – namely, scientific publications, joint science-business research projects etc. Then, this technology is able to triangulate data and correlate research outputs with their use in Lithuanian economic activities, offering insights on how that scientific knowledge is indeed exploited within the business ecosystem. In particular, the AI tool will help qualify the following elements:
- Who are the users of scientific knowledge;
- Who finds the scientific knowledge relevant and to what extent;
- How and which sectors are using it;
- To what extent scientific knowledge adds value to business processes.
Expected benefits
This solution is expected to provide evidence-based information to policy makers and Lithuanian businesses on the level of scientific knowledge integration in the economy. Clearer figures will facilitate the possibility to identify solutions to boost and enhance scientific knowledge utilisation. A relevant outcome expected in the medium-term from the application of this AI-based solution is its capability to help the Lithuania Innovation Agency in monitoring and measuring more transparently how knowledge transfer activities (e.g., of scientific publications, data on university graduates and joint science-business projects) are effective. In the long-term, this could potentially provide policy makers with remarkable insights to take informed decisions in the field of economic development and innovation policies.
Current challenges
This project is nonetheless facing multiple challenges of operational and legal natura:
- Operational issues
- Low interoperability of data formats. The LIC manages three types of information in different formats: scientific publications, data on university graduates and joint science-business projects. This complicates the process of analysing and triangulating the data to extrapolate meaningful findings;
- Low accuracy of data. The data are often poorly reliable, and it requires complex and time-consuming data validation processes;
- Lack of in-house AI skills. This leads to the need to involve private sector actors which is however limited by limited budget capacity;
- Difficulties in engaging other institutions to take part into the project and provide the necessary data to train the AI tool.
- Legal issues:
- Presence of sensitive data requires to conduct scrutiny of privacy related legislation. This lengthens the full implementation and uptake of the tool

Detailed Information
Year: 2022
Status: Pilot
Country: Lithuania
Technology: Artificial Intelligence
AI domain(s): Machine learning - interpretation and classification of data
Geographical extent: National
Responsible Organisation: Lithuanian Innovation Centre
Interaction: Goverment 2 Goverment and Government 2 Business
Function of government: Economic Affairs