INcreasing the uptake of AI technology in Retail

Risultati finali

A toolkit addressed to continuing vocational education and training providers to enhance the integration of the project AI skills development solutions into VET provision. The toolkit includes the following resources: (1) a user manual, (2) a collection of use cases for the integration of the platform into online or hybrid courses, (3) a content library (providing pre-existing customizable AI educational resources), and (4) at least three AI videos to share the project’s key results (i.e., AI Skills Needs & Gaps Analysis Report, the AI Core Curriculum and the Open Educational Resources)

AI Skills Assessment Tool

The AI Skills Assessment Tool will be a comprehensive and objective evaluation instrument designed to assess retail workers' proficiency in the knowledge and skills linked to the domains defined in the AI skills needs and gaps analysis (WP3). Developed collaboratively by T4E and UNIWARSAW, this tool will serve as a pivotal component of the INAIR project's curriculum implementation since it will provide learners with recommendations for learning blocks and differentiated pathways that match their proficiency levels.The deliverable includes documentation (i.e., methodological guidelines, worksheets, assessment survey, assessment scale and score grid) and a digital assessment tool.

INAIR E-Learning Environment

E-learning platform - in ENG and all the beneficiaries' languages - delivering the project Open Educational Resources and tailored learning experiences on AI for owners and employees of MSMEs in Retail.

Project Website

Digital platform aimed to showcase and disseminate the key information, progress, and deliverables of the INAIR project. The website will serve as an online hub, providing accessible and up-to-date information about the project's objectives, activities, results, and impact to the project stakeholders.

Open Educational Resources

Collection of min. 16 Open Educational Resources (OERs) on AI for retailers, including the following: learning modules (interactive lessons and assessments that learners can complete at their own pace) interactive tools (i.e., allowing retailers to experiment with AI and see how it works in real-world situations), or animations and simulations, to provide interactive visual representations of complex concepts and processes; webinars (e.g., recorded online presentations providing retailers with a deeper understanding of AI and its applications) or interactive videos; learning games; assessment tools (tests and quizzes that allow retailers to assess their knowledge and understanding of AI and identify areas where they need additional support). In line with the principles of OERs, the consortium aims to design and create resources that will support Open Education, Open Research, Open Access and Open Data. The OERs produced will provide open AI-Education course material and information, striving for unlimited participation and open access to retailers via the E-learning platform. Moreover, the OERs will allow for new ways of assessment and evaluation. Hence, it is important for the interactive resources to not only facilitate an engaging learning process but also to further impact and motivate the interest of retailers to raise their level of attention and engagement with AI. All project results will be freely available for access.Languages: English and each beneficiary's language.

Open Educational Resources (OERs) Validation Report

Report on the results of the validation of the project Open Educational Resources (OERs), T5.3. The document will collect the results of the peer review process, including the following content: (a) a description of the methodology applied to validate the OERs; (b) a summary of the feedback received from industry experts on the content, structure, and effectiveness of the OERs; (c) a summary of the key findings from the validation process and recommendations for improvement; (d) appendices (any additional data, charts, or tables that support the findings in the report). Based on a mixed-methods approach, qualitative and quantitative data will be collected from both internal and external experts across the partner countries. Participants will consequently have the opportunity to share their perceptions on the OERs created, based on defined evaluation criteria. The report provides an overview of the evaluation process, results and expert recommendations.

Analysis of the AI Skill Needs and Gaps In Retail

"Report of the findings and conclusions of the transnational research work within WP3 - ""Analysis of AI Skills Needs and Gaps in Retail"", including recommendations and guidelines for designing the AI Core curriculum for MSMEs in Retail (WP4). D3.1 aims to provide a comprehensive insight into AI skills and technologies in the retail sector in the 5 countries covered in the project. The report will be based on thorough desk research utilizing scientific and grey literature, relevant EU projects, web scraping, open datasets, and official statistics. The goal is to identify crucial AI skills required in the retail industry, assess the demand for these skills through job offers, analyze real-world implementations of AI in retail using use cases and best practices, and incorporate Eurostat statistics to support the findings. Based on the comprehensive knowledge gained in WP 3, the research team will formulate essential recommendations and guidelines for designing an AI Core curriculum tailored specifically to MSMEs in the retail sector. •Literature Review: The research report will begin with an extensive systematic literature review, delving into the current state of AI adoption in the retail sector. It will cover peer-reviewed scientific papers, industry reports, and other grey literature to gain a comprehensive understanding of the AI landscape in retail.•Identifying Crucial AI Skills for Retail: The next section of the report will identify the essential AI skills required in the retail industry. This analysis will be based on expert insights gathered from specialized retail consultants and technology experts, retail business owners and academics, trade unions, chambers of commerce, and representatives of other relevant national and EU-funded projects and initiatives, incl. the Bridges 5.0 and AI4Europe consortia and the members of the Pact for skills' Large-scale Partnerships in Digital and Retail.•Analyzing Demand for AI Skills in Retail Job Offers: To assess the demand for AI skills in the retail job market, the report will conduct an exploratory analysis of relevant job offers from various retail companies across the EU. Web scraping techniques will be employed to gather a significant sample of job postings, which will then be analyzed to identify the most sought-after AI skills and qualifications. The primary platforms chosen for each market are as follows: pracuj.pl (PL); xing.com (DE); adzuna.it (IT); ejobs.ro (RO); cypruswork.com (CY)•Text Mining Analysis: UNIWARSAW will use text mining techniques (topic modelling, co-occurrence analysis) to extract meaningful information from the collected job ads. The analysis will primarily focus on identifying keywords and phrases related to AI skills and technologies employers seek in the retail industry across the five markets of interest.Expected Outcomes: This comprehensive job ads analysis aims to provide valuable insights into the AI talent requirements in the retail sector of the selected markets. The results will help stakeholders understand current market demands and emerging AI-related skills and technologies trends.•Real-world Implementations of AI in Retail: In this section, the report will showcase real-world use cases of AI applications in the retail sector. The use cases will be collected from prominent retail companies. Emphasis will be placed on highlighting the impact of AI technologies on operational efficiency, customer experience, and business growth.•Best Practices in AI Adoption for Retailers: Drawing from the use cases, success stories and gathered insights, the report will outline best practices for retailers looking to adopt AI technologies. These practices will encompass implementation strategies, data governance, ethical considerations, and methods to overcome common challenges.•Incorporating Eurostat Statistics: The research report will incorporate statistical analysis of Eurostat data related to the retail industry and its A"

AI Core Curriculum for MSMEs in Retail

The AI core curriculum, built around the findings and conclusions of the multi-level AI skills needs and gaps for retailers (WP3), will cover the fundamentals of AI and its applications for greening retailers and supporting them in optimizing resources and processes. It will address transversal, green information, and digital and technical skills needed to adopt AI to make their companies, processes and products more sustainable, following ESCO’s classification. It will embed modular learning approaches and articulated in 16 Learning Blocks distributed across three different proficiency levels (i.e., Foundation, Intermediate, Advanced). The curriculum will be based on the fractal educational model, and therefore on concept-based curriculum design, student-centered teaching, heutagogy, and openness. It aims to foster active engagement, personalized learning paths, self-determined learning practices, and flexible access to resources.The deliverable will include:• outline of the methodological approach;• documentation of the curriculum design and development process;• the outline of the learning blocks and differentiated learning pathways for retail workers. Each learning block will cover generalizations (or conceptual understandings), guiding questions, critical content, key skills, assessment methods, and suggested learning experiences;• a map of relevant web-based AI tools meeting the requirements defined in The Ethics Guidelines for Trustworthy Artificial Intelligence developed by the EC’s High-Level Expert Group on AI.Format: Electronic publication. Language: ENG.

Dissemination, Exploitation, Communication and Outreach (DECO) Plan

The Dissemination, Exploitation, Communication, and Outreach (DECO) Plan will outline the consortium's integrated approach to the DECO activities. The Plan will detail the objectives, strategy, actions, channels, tools, timeline, roles and responsibilities to inform, promote and communicate the project activities and its results, disseminate the project outcomes and outputs and enhance the uptake of the project results.

Pilot Training Results Report

"The ""Pilot Training Results Report"" will document the outcomes and findings of the piloting cycles conducted as part of Task 6.3. This report aims to provide a detailed overview of the pilot testing of the e-learning environment and curriculum designed for micro, small, and medium-sized retailers (MSMEs) in the retail sector. The primary objective of the report is to present a comprehensive analysis of the pilot training results, including insights from early adopters, stakeholders, and industry experts, to guide the refinement and enhancement of the e-learning platform.The report will cover the following content:•Methodology•Composition of the Group•Piloting Process•Evaluation Survey•Results and Findings (Presentation of qualitative and quantitative data collected from early adopters, stakeholders, and industry experts; Feedback on platform usability, curriculum effectiveness, and the overall learning experience)•Impact and Recommendations (recommendations for further enhancements based on the pilot training results);•Conclusions•Annexes (e.g., Evaluation survey questionnaire, Data analysis methods, Additional relevant documents)"

Pubblicazioni

INAIR Policy Paper: Recommendations for Equitable and Sustainable AI Adoption in European Retail SMEs

Autori: Harms, C., Lanzetta, M., Włoch, R., Śledziewska, K., Acomi, N., Acomi, O., Abbruzzese, G.& Fotiadis, T.
Pubblicato in: 2026
Editore: Zenodo
DOI: 10.5281/ZENODO.20714389

AI skills needs and gaps for MSMEs in the retail sector in Cyprus, Germany, Italy, Poland, and Romania

Autori: Włoch, Renata; Ślosarski, Bartosz; Paliński, Michał; Śledziewska, Katarzyna; Teodorowicz, Karol; Łebkowska, Weronika
Pubblicato in: 2024
Editore: Zenodo
DOI: 10.5281/ZENODO.12793437

Assessing AI Competences in Retail MSMEs: A Methodological Approach

Autori: Acomi, Nicoleta; Chervinskyi, Mykyta; Acomi, Ovidiu; Lanzetta, Miriam; Abbruzzese, Gianluca
Pubblicato in: 2025
DOI: 10.5281/ZENODO.15310155

AI Core Curriculum for MSMEs in Retail

Autori: Acomi, Nicoleta; Lanzetta, Miriam; ACOMI, OVIDIU; Chervinskyi, Mykyta; Włoch, Renata; Śledziewska, Katarzyna; Abbruzzese, Gianluca; Fotiadis, Thomas; Andreotti, Cecilia; Manchi, Giordano
Pubblicato in: 2025
Editore: Zenodo
DOI: 10.5281/ZENODO.14358284

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Risultati finali

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