"<< Background >>We believe that universities in general and MBA programs, in particular, are in a unique position to significantly raise the awareness of leaders in the public and private sector of the prospects offered by careful but at the same time bold applicative possibilities of AI. MBA students represent a concentrated group of likely future leaders who, given a sound understanding of AI and its almost unpredictable opportunities, can react in their local surroundings cater for a significant change in attitudes and trust towards AI. Europe’s current and future sustainable economic growth and societal wellbeing increasingly draw on value created by data: the keyword being SUSTAINABLE. AI is one of the most important applications of the data economy and thus the probably crucial tool for business development that cares for people, planet and profit at the same time. Drawing on it, the objective of AI4PPP is to provide to our target groups not only a basic understanding of AI, the language surrounding the technological and social aspects of AI, but also to show how it works and to show the potential of its future implementations in all professions and industries. As part of our research conducted in 2020 by Algebra MBA and EY, it was shown that C-level executives are looking for support in technology in order to maintain the market positions of their companies. Among students, especially executives point out that they are willing to accept the digital transformation and emerging technologies as part of their organizations but have a lack of understanding on how to evaluate benefits, how to make first step and how to guide technology implementation and organization’s human capacity management in order to keep up with digital age. Being present in education for 20+ years focused on digital technologies from an applied perspective, last several years Algebra University recognized trend in applicants – who are now taking C-level positions in organizations, with a clear need to gain relevant skills in order to be able to implement AI in their organizations. With past experiences with technology, which often leads up to overpricing and/or overpromise as major setbacks, C-level executives are now more careful than ever, with money ready to invest, but with the gap in understanding on how to start their AI journey. They are more than ever open to EDU institutions instead of big tech vendors, understanding that they need to improve knowledge and be able to adapt their mindsets rather than looking for short-term answers often provided through advertisements of big tech. We believe to be able to contribute in this way to the eradication of misconceptions around AI and to the creation of an all-inclusive ecosystem, where different members of the community will be armed with the basic skills needed to adapt to a changing world, in which AI will be prevalent. Our project will help alleviate the current misconceptions surrounding AI through education and skill acquisition. Currently, the demand in the fields of AI R&D outweighs the supply of a skilled workforce. This demand is expected to grow exponentially within the next ten years. Also, AI development demands diversity in all avenues of its creation and implementation.<< Objectives >>The main objective of the project Artificial Intelligence for People, Planet, and Profit (AI4PPP) is to deliver an innovative, well-rounded, high value transferable educational and training programme in AI through:- comprehensive DACUM analysis- development of educational content based on DACUM analysis,- adaptation and creation of teaching contents and materials according to established needs of the target groups,- piloting the newly innovative developed modules and materials and its improvement based on piloting process,- implementation of AI-empowered scenarios in selected industries- preparation for certification validation based on micro-credentials conceptAI4PPP is an interdisciplinary project designed to meet challenges of the modern education system and challenging market needs, by providing an awareness-raising, holistic and flexible education in business aspects of AI. We expect improved educational and training modules in AI together with guidelines, to be implemented and used by partner organizations and other relevant HEIs. Importantly, they will broader international connections and links with other sectors necessary for any future actions and further development of project activities even after the project ends. In the long term, this project will increase their visibility and reputation on regional and European level and hence will gain major influence on policy processes in these sectors. Upon completion of the project, the results will finally reach partner’s personnel and students, both on the strategic decision-making level and practical level of everyday work of teaching and learning.<< Implementation >>The project activities are divided in a) horizontal tasks – PM (AG1), Transnational Meetings (AG2), Multiplier Events (AG4); b) theme-related tasks which will result in specific PR (AG3) and accordingly to the achievement of the project objectives and delivery of the planned results.All activities are organized within groups of activities:AG1, Project Management and Implementation (led by AUC), includes ensuring project activities and outputs are in line with timetable and budget, coordinating and organizing PMT meetings, budget spending, producing reports, collecting and storing all relevant documents, and communicating with NA. AG1 will produce the following deliverables: 3 Partnership Agreements, 2 interim and 1 final reports; meetings minutes. AG2, Transnational Meetings (led by partners accordingly, coordinated by AUC), which is related to AG1 and support following tasks: preparing a Project Quality Plan (PQP), evaluation of PQ and financial management and monitoring the realization of activities and quality of outputs based on PQP (deliverables: 1 PQP, 1 mid-term evaluation report, 1 final evaluation report).During the AG3/PR1 Gap Analysis understanding of AI potential (led by AUC) partners summarize report and evaluation based on their experience lead by AUC/EY survey which will be refined into the report (deliverables: research analysis report, 1 st multiplier event). As part of AG3/PR2 DACUM analysis (led by AUC), we will deep dive into AI expert job role, responsibilities, and everyday life to acquire data needed to assure usability and foundations for syllabus in the emerging field of AI (deliverables: DACUM results). As part of AG3/PR3 Syllabi will be Developed and Tested (led by FUDS) using several focus points: usability via modular approach, relevance following gap analysis conclusions and adaptability making them usable for various target groups as preparation for AG3/PR4 Educational material development (led by UAH). The process of modules structuring includes: focus on industry and cross-domain topics relevant and suitable to adopt through AI approach; developing educational modules according to these selected topics (scenario selection, module development and simulation cases). All modules will be driven by industry examples and will be based on the demand analysis carried out in AG3/PR1 and AG3/PR2. Modules will be prepared in a way that they could be used by students in order to make synergy with study programs (deliverables: Education material containing: business problem, task decomposition; approach analysis; AI technique selection; operationalization of results; 2nd multiplier event). The developed educational modules will be integrated into the learning environments through AG3/PR5 Module piloting (led by AUC). Main objectives: support partners in their effort in planning, implementing and evaluating innovative and efficient approaches in AI learning; contribute to the popularisation of the AI piloting real cases. This includes aselection of participants, selection of suitable courses' study programs to use the repository, piloting the modules and evaluating the process (deliverables: report on pilot execution, 3rd multiplier event). AG3/PR6 (led by FUDS) include industry and use cases selection in order to challenge skills and lessons learned on real-life scenario. Development of AG3/PR7 (lead by UAH) Guidelines and preparations from micro-credentials covers 2 main functions: training mechanism contributing to the development of participants' new skills and experiences; and speed up of AI boarding process including business value creation by recognizing program through micro-credentials. Micro-credentials certification handbook which will be produced during AG3/PR7, will respond to 2 necessities: how to efficiently educate and train individuals in AI and how to respond to current challenges and trends represented by AI in business environments (deliverables: 1 guidelines, 4th multiplier event).<< Results >>Partners will carry out a wide range of activities in order to implement a well-rounded, high value transferable educational and training programme in AI through (i) comprehensive DACUM analysis in order to proof trends and skills used and needed among relevant AI professionals; (ii) development of educational modules, (iii) adaptation and creation of teaching contents and materials according to established needs of the target groups,(iv) piloting the newly developed modules and materials, (v) implementing scenarios of AI application in selected industries, and (vi) finally make all preparations for AI educational program to be certified using micro-credentials approach/concept (all described in detail in the section ""Project results"").AI4PPP is an interdisciplinary project designed to meet challenges of the modern educations system and challenging market needs, by providing an awareness-raising, holistic and flexible education in business aspects of AI. We expect that improved educational and training modules in AI together with guidelines, to be implemented and used by partner organizations and other relevant HEIs. This will help in adopting an AI-based mentality powered by piloting and simulating AI processes. By implementing scenarios of AI into selected industries, the project will elaborate guidelines for improvements in usage of AI methodologies and tools in business having backpropagation elements to be used in education and by doing so will popularize AI within a various and especially non-technical sector (i.e. social sciences and humanities).Namely project outputs are (i) report including a repository of existing AI training courses/study programs and market needs in respect to relevant occupations, with special attention to the MBA students and non-technical sectors; (ii) DACUM analysis with identification of relevant skills/needs and “must have” for AI professionals; (iii) transferable educational/training materials/modules, including topics covering wide range of different industries and cross-domain topics that will illustrate the main benefits of AI and at the same time will attract different populations (HEIs, policy makers, entrepreneurs, employees etc.); (iv) piloted and simulated use cases for EDU, the developed piloting model will be tested during the project implementation at the partners' institutions thus providing partners with immediate outcomes and feedback; (v) implementation scenarios for selected industries proofing applicability and business value of acquired skills; (vi) proactive focus point on the end-to-end learning materials, a tool for piloting and simulating use-cases in AI and as a foundation for collaboration between stakeholders and students – bringing micro credentials recognition for current and future participants.Improvements will be developed for AI-related course studies (AI topics already vertically implemented in curricula) and for non-AI courses (courses that have implemented AI as a horizontal element in curricula and studies that haven't implemented AI topics in curricula at all) including tailoring recommendations in relation to institutions specificities. In addition to these concrete results, the following outcomes are also foreseen: (vii) increased knowledge about AI implementation at HEIs in its MBA courses especially; (viii) arisen awareness and capability of users to process and analyze data as a foundation for AI-skills understanding and development also in absence of previous sectorial (digital) knowledge; (ix) enhanced business sector (especially non-technical one) ability and speed to achieve goals by proper use and exploitation of AI; (vii) fostered partners' capacities in developing innovative learning materials/tools and encouraged development and adoption of AI in higher education; (x) strengthened links between HEIs and enterprises to promote excellence and regional development."