The Salford Business School at the University of Salford, England, hosts the symposium “Sustainability in Executive Business Education Programmes” from December 4 to 6, 2025. As part of the event, Dr. Tetiana Gorokhova, guest researcher at CAIS, holds a presentation on December 4 titled “AI Mindset in Entrepreneurial Spaces: Helping SMEs Use AI for Real Sustainability Gains.” The paper was co-authored by Prof. Dr. Žaneta Simanavičienė, Kateryna Polupanova, and Tetiana Polupanova.
The presentation introduces an ongoing international executive training program built on the short course “Entrepreneurship and Innovation Based on Artificial Intelligence” and complemented by hands-on assignments. Participants develop low-cost prototypes of sustainability-relevant use cases and take initial practical steps toward their implementation. Early results show positive effects: increased confidence in selecting appropriate AI tools, stronger links between use cases and sustainability goals, and a clearer understanding of ethical guidelines such as transparency, human-in-the-loop, and data minimization.
Abstract
Small and medium-sized enterprises are central to the green transition, but many owners and managers still struggle to turn the promise of AI into visible results. This practice paper presents an ongoing international executive training built around a short course, “Entrepreneurship and Innovation Based on Artificial Intelligence”, paired with field assignments where participants prototype low-cost use cases – such as demand forecasting to cut waste, energy-aware scheduling, and repair/refurbish decision support.
The intervention is simple by design. First, a compact literacy module covers the essentials: data governance, bias, environmental footprint, and basic risk controls for AI. Second, a hands-on design sprint helps each participant choose one sustainability-linked process problem and map it to an AI-supported workflow. Third, participants draft a cautious implementation plan with clear metrics, rough costs, and compliance checks.
We track learning and early adoption using a pre/post survey and short reflective reports. Early signals are encouraging: participants report higher confidence in choosing fit-for-purpose AI tools, tighter links between use cases and SDG-relevant KPIs (such as materials and energy efficiency, error/waste reduction), and a clearer understanding of ethical guardrails (including transparency, human-in-the-loop, and data minimisation). Our contribution is threefold: (i) a ready-to-use micro-curriculum for executive and EBE settings; (ii) a straightforward rubric that ties SME AI use cases to sustainability metrics that matter; and (iii) a practical checklist of common pitfalls – tool-first thinking, metric myopia, and data-quality blind spots – paired with teaching responses. We conclude with a pragmatic pathway for resource-constrained SMEs and concrete advice on embedding responsible AI skills across executive programmes.
The complete program of the symposium can be found here:
https://surli.cc/mogqpj