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Due to the current state of the art in technology, the world is trending towards a knowledge-driven economy. According to the Knowledge4All Global Knowledge Index (GKI) (1), Portugal ranks 27th (61.8 GKI) among countries with the highest GK indices, and only 10 points below 1st place – Switzerland (71.5 GKI). However, when considering the population variable, there is a dilution of innovation potential, and Portugal falls to 34th place (1).
Europe remains the second most innovative region in the world and, according to the European Innovation Scoreboard (EIS), from 2020 to 2021 Portugal went from a strong innovator to a moderate innovator (2). These reports positively detail Portugal’s innovative entities, the favorable environment for innovation, the attractive research system, SMEs that innovate internally, broadband penetration, and SMEs with product and/or process innovations (2). On the other hand, Portugal presented gaps in terms of innovation in internal business processes, innovators who do not develop innovation in-house, scarce exports of knowledge-intensive technical services, low investment in R&D in the business sector, low levels of co-financing in public R&D, and low frequency of public-private partnerships. However, Portugal is above the European Union average in business creation (10+ employees), total business activity, and net inflows of foreign direct investment, indicators of high potential.
In this article, we will not focus on the reasons why Portugal is lagging behind in building a knowledge-driven society aimed at boosting innovation and economic growth, since, as demonstrated above, this is a complex multifactorial problem. Instead, we will focus on open innovation as an engine of economic growth and present the main reasons for its application to the Blue Bioeconomy sector.
Innovation, as defined in ISO 56000:2020 (3), is the practical implementation of ideas that result in the introduction of new products or services or the improvement of existing products or services. Traditionally, innovation takes place within a closed vertical structure within a company. Research and development of new products and services are done internally, kept secret, and later, in due course, some are introduced to the market. This process suffers from an intrinsic and natural bias, ignoring competitors, and sometimes the market, having additional disadvantages that will be discussed below.
Henry Chesbrough was the first to break the innovation paradigm with the introduction of the concept of open innovation (OI) in 2003 (4), and since then, it has naturally evolved into a model where companies use ideas, processes and market entry routes, both external and internal, resorting to pecuniary and non-pecuniary mechanisms aligned with their business model in order to guarantee technological advances in their products, processes or services, acquiring a collaborative competitive advantage. This openness to innovation ultimately impacts the consumer, company, industry, and societal levels (Figure 1).
Implementing AI requires a shift in business mindset based on sharing experiences, knowledge, and technologies, both within and outside the company. The key to successful implementation is focusing on diversity and knowledge of the available innovation ecosystem. Some possible actions on the AI implementation journey include investing in the diversity of the internal team, collaborating and co-creating with external R&D institutions and companies, connecting with innovative startups, organizing hackathons, brainstorming groups, and crowdsourcing, and engaging with local, regional, and international innovation hubs.
Until now, AI is still considered by some to be a paradigm shift in terms of Intellectual Property (IP) management, and a legal nuisance unworthy of effort. However, some of the world’s largest patent applicants, Philips NV, IBM, and Intel, have embraced AI as a strategic shift, and after analyzing their patent submission activities, no deleterious effects are observed (5, 6), and in some cases, the number of applications has increased. These companies have raised the level of their innovation to accommodate extensive information exchange with their collaboration partners (competitors and R&D institutions) and to manage collaborative relationships accordingly, so as not to compromise their IP or that of their partners.
Open and collaborative innovation requires companies to engage more actively and strategically in IP governance, not only in terms of acquisition and defense, but also in defending IP rights and generating royalties. The transmission of inventive ideas, whether in a formal or informal format, destroys the novelty in a patent application, so care must be taken with the sharing and disclosure of information in an AI project, and collaboration agreements should clearly regulate this aspect.
Although managing the results of knowledge generated collaboratively in a new open research ecosystem is a challenge, IP is a fundamental tool to overcome imprecision in defining and categorizing the knowledge or technology to be developed collaboratively, thus assisting in drafting a collaboration agreement. A patent or other intellectual property right, being a legal document, presents language suitable for drafting licensing agreements and can be used as a negotiation tool and to mitigate disputes with third parties who hold complementary technology. Furthermore, licensing agreements with third parties promote the development of a technology that would otherwise be slow to enter the market or fail to achieve distinct application in other markets.
The benefits of AI via collaborative projects could be summarized as increased networking and reduced investment/costs, risk, and time to market; however, there is much more. Co-creation and dissemination of results and technology generate new product ideas, create markets for disruptive technologies, and promote the creation of new business models and companies.
The European Commission has stated that “to cope with a growing global population, the rapid depletion of many resources, increasing environmental pressures and climate change, Europe needs to radically change its approach to the production, consumption, processing, storage, recycling and disposal of biological resources” (7). Due to pressing global challenges, AI projects are the most suitable instruments to achieve innovative solutions, and aquaculture and blue biotechnology, the pillars of the Blue Bioeconomy, are considered strategic (7).
The versatile products for human consumption derived from the Blue Bioeconomy contribute to mitigating the growing demand for protein, improve food security and human health without depleting natural resources, while in some cases sequestering CO2 from the atmosphere. High-potential non-food products of the Blue Bioeconomy, wholly or partially derived from materials of biological origin, include pharmaceuticals, cosmetics, chemical feedstocks, lubricants, detergents, paints, fertilizers, textiles, furniture, bioplastics, biofuels and bioenergy. Collaborative projects in the Blue Bioeconomy sector can yield various innovative value chains and market entry for innovative sustainable products, while aiming to monetize technologies applicable to different areas (8) The Kg of biomass produced has enormous monetization potential (Figure 2), and its total utilization is essential (9).
To materialize truly circular, zero-waste, economically viable processes, an AI approach must be used for all by-products of the Blue Bioeconomy (Figure 3). Recently, in Portugal, a multidisciplinary Consortium, based on AI principles, was created and funded with the aim of reindustrializing national companies through the incorporation of blue biotechnology products into their value chains (10). This is a turning point in the Portuguese business mindset, and the results and impact of this AI effort will be finalized by the end of 2025. Exciting times await us!
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