Objectives and assumptions of VESTA project
Strategic objectives of the project
The strategic objectives of the VESTA project focus on modernising vocational education in the field of sales through the use of AI. The main assumptions are:
☑ Innowacja in VET: equipping SMEs and VET training providers with a shared techno-methodological toolkit for analysing and diagnosing training needs. This means creating an AI-based platform that enables the identification of competence gaps and training needs within companies.
☑ Synergy between SMEs and education: aligning the resources of SME sales departments and VET analysts/designers by developing common methods of using AI in sales management. In this way, practical business knowledge will merge with educational experience, creating more effective competency-development programmes.
☑ Reduction of the skills gap: disseminating the VESTA application and related tools to reduce skills mismatches in sales management. The project aims to reach a wide range of stakeholders so that the new solutions are widely implemented in business practice.
☑ Support for lifelong learning: promoting continuous e-learning for sales professionals by providing access to open educational resources (OER) that support effective use of the VESTA application. This is intended to encourage professionals to keep developing their skills even after the project ends.
Justification for the project
The VESTA initiative addresses a specific, identified market problem. In the era of digital transformation, many SMEs face a lack of appropriate competences in sales and data analysis. Current vocational training systems do not always precisely indicate which sales skills SMEs need, making it difficult to match training offers to the market. Moreover, companies themselves often lack the tools or methodology to assess their training needs and plan them strategically in a dynamic business environment. According to Gartner research, as many as 59 % of SME managers identify a skills mismatch in the sales department as an urgent challenge hindering company growth. Without intervention, this gap will deepen, limiting SME competitiveness on the market.
The VESTA project is a response to these challenges. A proactive model for analysing SME needs using AI will be developed, allowing prediction and evaluation of what employees already know and what skills they will need in the future to achieve professional excellence and maintain company competitiveness. This model will be applied in the practical VESTA application, integrating AI analyses with recommendations for training actions. In addition, the partners will create a rich set of educational materials (micro-learning, video tutorials, interactive scenarios) to support the application’s content-recommendation system. The project also envisages implementing personalised training paths for SME employees – moving away from universal catalogue training towards precisely tailored solutions, which is critical especially for small firms where there is no room for errors or delays in developing staff competences.
Operational objectives and project activities
To achieve the above assumptions, the VESTA consortium will undertake a series of coordinated actions:
- First and foremost, the design and implementation of the VESTA application – an innovative AI-based tool for analysing training needs and diagnosing competences in SMEs – is planned.
- In parallel, the partners will review existing e-learning platforms and open resources (OER) to select and adapt the best training content for the project’s needs.
- Next, micro-lessons, video tutorials and scenario-based narratives (so-called narrative branching) will be created to serve as open educational resources integrated with the application.
- After developing the tools, their deployment and testing are planned in four EU countries – the VESTA application and training materials will undergo pilot trials with target users, allowing feedback to be collected and solutions improved.
- An essential element is also the creation of an open cooperation network – the partners will establish an international group of stakeholders (by signing a multilateral Memorandum of Understanding) to ensure the project’s results are sustainable and to continue cooperation after its completion.