AI can help you make the most of your ESG data - When Excel is not Enough

There’s nothing wrong with emails and Excel spreadsheets. They’re good tools. But when it comes to managing masses of data, they do tend to be rather labour-intensive. 

AI is a great support for ESG work: less manual effort, more impact

Senior Data Advisor Tiina Nokkala notes that there’s a rich harvest of low-hanging fruit around ESG data, all ripe for the picking.

“AI isn’t a cure-all for everything, but it is a huge help in ESG data management. AI can reduce manual work in data collection and processing, harmonize information across varying sources and formats, and make that data usable across different parts of the business,” Tiina Nokkala explains.

Even just reducing manual work would be a major relief. Companies receive hundreds, even thousands, of ESG-related inquiries from their stakeholders, often via email or online forms. The same questions keep coming up: requests for emissions data, SBTi commitments, certifications, standards, internal and supplier responsibility, and so on.

“These requests are typically read and then manually forwarded to someone in sales, finance, production, procurement or HR – with the hope that they’ll respond. There’s no follow-up, previous answers are not reused, and there’s certainly no AI or automation involved,” says Kati Kaitua, Senior Data Advisor, ESG Data Management.

Kati Kaitua emphasises that manual work is not limited to just handling inquiries.

“Take the EcoVadis certification, for example. It’s critical and important, and securing it can mean several days spent just chasing down the required data,” Kati Kaitua says.

Start with simple AI solutions that deliver real value

At Tietoevry Tech Services, AI projects start by identifying potential use cases together with the customer and evaluating them based on business value, feasibility and the complexity of the solution.

“It’s often best to start with an AI solution that will deliver reasonable business value with not too much effort,” explains Senior Data Management Consultant Touho Siitonen.

“There are plenty of these opportunities around ESG data right now – practically in every company, especially in manufacturing,” Tiina Nokkala says.

AI solutions can start delivering business value quite quickly. SmartGen Suite is Tietoevry Tech Services’ framework that significantly speeds up AI projects by leveraging reusable components.

Practical examples: how AI enhances ESG processes

Touho Siitonen shares examples of AI solutions that could be adapted to ESG data management with Tietoevry Tech Services’ SmartGen Suite.

“One of our Nordic clients owns thousands of properties. Whenever someone needed to know who’s responsible for electricity, water, or waste management at property X, it created a bottleneck. The information had to be requested from contract managers, who’d sift through thousands of agreements to find the right one and extract the needed details,” he describes.

Now, a GenAI-powered contract management system handles this instantaneously. It can interpret both text and checkbox fields.

You can ask the system in plain Finnish who’s responsible for waste management at a specific property. The answer comes immediately, with a hyperlink to the correct contract. The solution is a huge time-saver, and it supports scope 1 and 2 emissions tracking and data verification. Data security is naturally accounted for: users can only access information from contracts they’re authorized to view.

“Another great example is a large Nordic client of ours. For them, updating product information was an enormous task. With the GenAI system we built, they now pull data from multiple sources and generate correctly formatted product descriptions automatically, in all required languages. Their experts just need to review them, make any final tweaks, and approve them for publication,” Touho Siitonen says.

Kati Kaitua points out that a similar AI solution could ease many repetitive routines in ESG reporting and communications.

“A dedicated ‘responsibility mailbox’ could collect all ESG-related inquiries, update an FAQ list based on these inquiries, route questions to the right people with suggested responses, and save final replies for future reuse,” she envisions.

“AI could also help update materiality analyses: It could track stakeholder expectations, collect and compare survey responses, and identify themes in large data sets. It could also be used to benchmark an organization’s sustainability against competitors or suppliers,” Tiina Nokkala adds.

Gaining competitive edge from AI: ESG data as a strategic asset

Tiina Nokkala, Kati Kaitua, and Touho Siitonen emphasize that AI isn’t just an efficiency tool. It can help create competitive advantage from sustainability data.

“With AI, ESG information can be incorporated into continuous development and strategic decision-making,” says Tiina Nokkala.

“At its best, AI is supportive intelligence that helps experts create new growth. For CSRD reporting alone, companies have collected enormous amounts of data, much of which currently goes unused internally. That’s a missed opportunity,” Kati Kaitua underlines.

“It’s wise to start with easy solutions that take manual data gathering off experts’ plates, freeing them to focus on thinking and genuine development work. This will give them a sense of how AI can support their day-to-day tasks – and the breathing room to conceptualize what kinds of more sophisticated AI solutions would bring them unique competitive edge,” Touho Siitonen concludes.