# Technology Readiness Levels (TRLs) in the Era of Co-Creation
## 2 Related Work  
The current operational and technological context of many manufacturing companies often obliges them to develop innovative solutions, leading to a complex asset lifecycle composed of different phases, starting from conception and planning before progressing through design to engineering, construction, validation, verification, and commercialization. [PERSON] et al. [4] developed and proposed a TRL template that aimed to support the lifecycle management of manufacturers' assets, fostering the exploitation of related data and knowledge from the development phase of the technologies employed onwards. The proposed TRL model was structured at nine levels, classified into three main phases, and was considered an improvement on the EC and NASA TRL standards. Nonetheless, some weaknesses were identified during the verification phase. Improvements were recommended, intended to make the assessment and verification of the assets' TRL easier. In 2022, during the Sustainable Places 2022 conference, eleven European projects joined forces on a clustering workshop entitled 'Low-TRL Renewable Energy Technologies' [8]. These EU Horizon 2020 research and innovation programs addressed high-risk technology developments for breakthrough renewable energy and fuel technologies, and their activities focused on providing knowledge and scientific proof of the feasibility of the proposed concepts. They were presented and brought together, trying to co-address similar challenges to bring their technologies to TRL 9. In order to do so, a validation of their TRL was a prerequisite and their rank was TRL 3-4. The recommendations that followed proposed a roadmap to move the technologies further up the TRL ladder for market uptake and full integration into the energy system. The accelerating use of artificial intelligence (AI) and machine learning (ML) technologies led [PERSON] et al. [9], to research the definition of a principled TRL process to ensure robust, reliable, and responsible systems. Their proposed Machine Learning TRL framework highlights that the existence of data-related requirements along every step would ensure that the development process considers data readiness and availability, which will not only help define ML-specific testing considerations (levels 5 and 7) but also help highlight ML-specific failure modes early. Its synergy with the existing industry standard software engineering practices would allow it to handle unique challenges. Their research concludes with the assumption that the proposed framework's distinct advantage is the nomenclature: an agreed-upon grading scheme for the maturity of an AI technology and a framework for how/when that technology fits within a product or system, enabling everyone to communicate effectively and transparently [9]. Thus, for AI technology, TR models differ from other cases [10,11], as AI is a multidimensional construct, hitherto not widely explored in this context. It should be highlighted that, no matter the sector, successful innovation involves more than a great idea [12], as collaboration with others makes things happen [13]; even though new ideas may often be born into a reactionary environment, collaboration can overcome inertia [14] and unlock the chains of convergent thinking, resulting in something innovative. On the other hand, co-creation means including 'trans-disciplinary actors' [15] and other key stakeholders, especially people who would be affected by a specific decision in a decision-making process. In order to do so, co-creation is a technique that is based on iterations during a creation process [16], which takes collaboration to the next level. Whenco-creating, stakeholders dive in deep [17; 18] they bring each person's unique perspective, skill sets, and experiences to produce the best possible solution with the highest impact [19]. However, a collaborative partnership alone is not enough, especially when creating new products or strategies, as new technologies encounter many implementation challenges that can hinder or halt their introduction [20].