ESG reporting is no longer a “nice to have.” For many small and medium-sized enterprises (SMEs), it is becoming a requirement driven by regulation, investor expectations, and supply-chain pressure. Yet for many organizations, ESG still feels complex, expensive, and out of reach. How can SMEs engage with ESG meaningfully if they lack the time, expertise, and internal resources to do so?
Why ESG reporting Is especially challenging for SMEs
Most SMEs recognize the importance of sustainability and responsible business practices. The difficulty lies in turning that awareness into structured, credible ESG reporting.
SMEs often face a combination of limited ESG knowledge, fragmented data, and tight budgets in practice. ESG information is scattered across internal documents, spreadsheets, emails, and operational systems, making reporting both time-consuming and error-prone. As a result, ESG is frequently perceived as something designed for large corporations rather than smaller, resource-constrained organizations.
AI as ESG support, not replacement
Sparky* team approached to this challenge with a different mindset. Rather than asking SMEs to adapt to complex ESG frameworks, we explored how AI could adapt to the reality of SMEs.
The goal was to support companies throughout the ESG reporting process, guiding them step by step while helping them understand what ESG requires and how their existing data can be used. In this model, AI acts as a co-pilot, supporting decision-making and learning, rather than replacing human responsibility.
How the AI agent supports ESG reporting in practice
The AI solution we developed supports SMEs through a structured but flexible workflow:
Understanding the context
The AI engages users in a guided dialogue, asking targeted questions about their organization, operations, and sustainability practices.
Collecting and connecting data
Relevant information is retrieved from both structured sources, such as databases and KPIs, and unstructured sources, such as internal documents and policies stored in a vector database.
- Structuring the ESG report
Based on collected inputs, the AI helps draft ESG narratives aligned with reporting expectations and highlights missing or incomplete information.
Providing guidance and recommendations
The system points out potential improvement areas and supports users in strengthening governance, data quality, and ESG consistency.
This process allows SMEs to move from scattered data to a coherent ESG report without starting from scratch.
Why AI matters for SME ESG reporting
A few observations from real-world usage highlight why AI can make a difference:
- Many SMEs already possess most of the data needed for ESG reporting but struggle to locate and structure it.
- Guided, question-based workflows significantly reduce reporting time compared to manual approaches.
- AI-supported reporting helps internal teams better understand ESG concepts, not just document them.
Case Study: Testing the Approach in Italy
This AI-supported ESG reporting approach was tested and validated in the Italian market, where ESG expectations for SMEs are rapidly increasing. The solution was presented at AI WEEK 2025 in Milan and later implemented by several SME customers in Lombardia region.
In practice, companies reported that ESG reporting became more approachable and less intimidating. Teams were able to reuse existing data, improve internal alignment on ESG topics, and produce structured reports with greater confidence. Importantly, the process also helped organizations identify gaps they had not previously considered.
FAQ: Common questions about AI-supported ESG reporting
Does AI replace ESG experts or consultants?
No. The AI acts as a support tool that helps organizations prepare, structure, and understand ESG information. Human oversight and expertise remain essential.
Can SMEs trust AI-generated ESG content?
Yes, provided the system is transparent, auditable, and designed to work with verified company data. AI supports consistency, but responsibility stays with the organization.
Is this only about compliance?
No. While reporting is a starting point, the real value lies in helping SMEs understand their ESG performance and identify areas for continuous improvement.
What this means for project managers and changemakers
For project managers, this approach reinforces the idea that ESG should be managed throughout the project lifecycle. AI agents can support data-driven decision-making, improve transparency, and help translate ESG goals into operational actions.
Rather than treating ESG as an end-of-project obligation, AI enables it to become an integrated and manageable process.
Looking ahead
If ESG is meant to drive meaningful change, it must be accessible to organizations of all sizes. AI offers a powerful opportunity to lower barriers, support learning, and transform ESG from a compliance burden into a practical management tool.
What would change in your organization if ESG reporting felt less complex and more collaborative? How could AI support your next ESG-driven project?
Marina Krstić
Project Manager at Sparky* and co-founder with extensive experience in European projects and the management of complex, AI-driven initiatives. Her work focuses on bridging technology, sustainability, and business value, with a particular emphasis on delivering large-scale AI solutions in the finance and media industries.