How AI is transforming sustainability consulting for SMEs

Sustainability reporting is more critical than ever, and artificial intelligence is here to help. Discover how AI is transforming environmental data into clear, actionable insights for businesses.

The demand for clear and accurate sustainability reporting is growing, driven by new regulations like the corporate sustainability reporting directive (csrd) and pressure from customers. Businesses need to measure their environmental impact, but traditional methods for things like life cycle assessments (lcas) and greenhouse gas (ghg) reports are often complex and time-consuming. This is where artificial intelligence (AI) steps in, transforming how environmental data is collected, analysed, and turned into valuable insights.

How AI automates life cycle assessments (LCAs)

A life cycle assessment (LCA) helps understand a product’s full environmental impact, from raw materials to disposal. Traditionally, lcas are very manual, involving hundreds of hours of data gathering and processing. This makes them expensive and often difficult for smaller businesses to access.

AI-powered sustainability tools streamline this process by:

• Automating data collection: AI can connect to your business's systems to automatically gather necessary data, reducing manual effort.
• Identifying environmental hotspots: AI quickly analyses thousands of data points to pinpoint where the biggest environmental impacts occur. For more on the fundamentals of lcas, learn more about life cycle assessments.
• Enabling rapid scenario analysis: Instantly model the impact of changes, like switching packaging or suppliers, getting answers in minutes.

This automation helps consultants deliver faster, more robust lcas. For a deeper dive, see our lca consulting service. The european commission is also pushing for standardised approaches like the product environmental footprint (pef), where AI will be critical for widespread adoption.

AI-driven carbon reporting and scope 3 emissions

Calculating a company's full carbon footprint is another big task. While scope 1 (direct emissions) and scope 2 (electricity use) are simpler, scope 3 (indirect emissions across the value chain) is much harder. It often accounts for most emissions and requires data from many suppliers.

AI-powered tools, like the Hedgehog carbon platform, simplify this complex process by:

• Integrating with financial systems: AI can analyse spending data to provide reliable initial estimates for scope 3 emissions, a process known as spend-based carbon accounting.
• Processing diverse data formats: AI interprets various documents, from energy bills to expense reports, to convert activity data into carbon emissions, following standards set by the GHG protocol.
• Refining accuracy over time: Machine learning improves as more specific data is provided, leading to more accurate calculations.

This automation makes comprehensive ghg reporting manageable, freeing consultants to focus on developing crucial carbon reduction strategies. For specific support, explore our scope 3 consulting services.

Benefits for sustainability consultants

AI doesn't replace sustainability consultants; it makes them more valuable. By automating complex data tasks, AI elevates their role from data processing to strategic advising. The key benefits include:

• Focus on strategy, not spreadsheets: Consultants can dedicate their expertise to interpreting results, advising on reduction strategies, and helping clients with regulations.
• Increased scalability and accessibility: AI efficiency means consultancies can serve more clients, including small and medium-sized enterprises (SMEs) who previously couldn't afford detailed analysis.
• Deeper, data-driven insights: AI reveals patterns in large datasets that human analysis might miss, leading to more effective sustainability solutions. If you’re unsure which analysis is right for you, our article lca vs. carbon footprint: which is right for your business goal? can help.

Navigating the challenges of AI in sustainability

Despite its many benefits, adopting AI in sustainability consulting comes with challenges. It's important to approach these tools with a critical eye.

• "Garbage in, garbage out": AI models are only as good as the data they receive. Consultant expertise is vital for validating data quality.
• The "black box" problem: Some AI systems can be opaque, making it hard to understand their results. Use tools that offer transparency and allow for calculation auditing.
• Greenwashing risk: AI can generate convincing reports that hide or misrepresent data. Ethical consultants must use AI to reveal truth, not obscure it.
• The environmental impact of AI: The data centres and computers needed for AI consume significant energy, as discussed in sources like the mit technology review. The industry must prioritise developing "sustainable AI" that is both powerful and energy-efficient.

The future of AI and sustainability

The integration of AI into sustainability is just beginning. The next wave of innovation will likely bring:

• Predictive analytics: AI models can forecast future emissions based on growth plans, enabling proactive sustainability management.
• Prescriptive optimisation: AI will not only identify issues but also recommend the most cost-effective solutions to reduce environmental footprint.
• Automated regulatory compliance: AI tools will adapt to evolving reporting standards like the csrd, ensuring compliance without constant manual updates. For more on this regulation, see csrd: everything you need to know.

Ultimately, AI is a powerful tool for change. It doesn't replace human expertise but amplifies it. When used by skilled and ethical sustainability consultants, AI can simplify complexity, speed up action, and empower businesses to make a real, measurable difference.

Ready to leverage technology for your sustainability goals? Contact Hedgehog to learn how our expert consulting and carbon platform can help.