CSR and AI: where corporate teams really stand in 2025

AI attracts interest but remains underutilized

80% of CSR professionals already use ChatGPT or other LLMs in their daily work. A third consult them multiple times per day. Interest is real, usage is frequent. But here's the catch: only 5% use specialized AI tools beyond generic LLMs.

Even more striking, 55% still don't automate their repetitive tasks. And 54% consider themselves beginners despite daily use. AI remains an occasional writing assistant, not yet a strategic automation engine.

The real game-changer? Moving from text generation to automating CSR data collection. That's where transformation happens.

Ground reality: weeks swallowed by admin work

The numbers don't lie. Here are the three most time-consuming tasks for CSR teams:

1. CSR data collection (72%)
2. Follow-ups with colleagues and suppliers (65%)
3. CSR report writing (40%)

Between 6 and 20 hours per week vanish into these administrative activities. Time invested and frustration felt compound, creating a daily grind saturated with low-value tasks.

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Clear expectations: automate first, write second

If you gave them a magic wand, here's what they'd wish for:

The message is crystal clear: urgency centers on data. Collection, reliability, structure. That's where AI must first create value.

Expected benefits? Faster report creation (67%), automated compliance monitoring (45%), and improved data accuracy (37%). With CSRD coming into force, pressure on data quality has never been higher.

Three conditions to unlock budgets

Despite massive conviction (92% anticipate major impact by 2028), budget translation lags. 62% have no dedicated budget for AI processes, and 72% lack budget for AI/automation tools.

To trigger investment, three levers are decisive:

1. Prove ROI (45%)
No more promises. Teams want measurable gains: hours saved, errors reduced, ESG ratings improved. Concrete results.

2. Adapt to sector specifics (35%)
Generic tools won't cut it. Solutions must understand each sector's particularities—retail, manufacturing, tech, services.

3. Guarantee regulatory compliance (33%)
Zero risk tolerance. Data reliability and accuracy are the #1 concern (43%), closely followed by security (40%). Makes sense: in CSR, a data error can cost dearly in reputation.

Early adopters already save time

Intermediate and advanced AI users spend 10% less time on collection and 16% less on writing.

These gains, though modest, tell an important story: we're at the beginning of the curve. Only 29% of professionals have reached this mastery level. Impact will multiply when this competency scales. Check out our AI prompts guide for CSR managers to accelerate your learning curve.

Automate to focus on what matters

The goal isn't to replace people. It's to free up time for what truly counts: analysis, strategy, impact. Learn how to set up effective ESG reporting and structure your approach for measurable results.

AI's carbon footprint: a critical issue

78% of CSR professionals agree on one point: companies should disclose the carbon footprint of their AI systems when claiming AI-driven sustainability improvements.

This exceptional consensus sends a clear signal: if AI improves sustainability performance, its own environmental cost must be accounted for and made public. Transparency is non-negotiable.

Moreover, 54% acknowledge that using AI in sustainability reporting increases greenwashing risk. Hence their heightened vigilance on data traceability and transparency. Consistency matters.

CSR and AI in 2025 - Key Takeaways

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👉 Download the full report

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Turn compliance into competitive advantage

AI won't replace CSR teams. It will free them from time-consuming administrative tasks so they can focus on what matters: measurable impact.

At Ditto, that's exactly what we're building. Over 500 companies already trust us to transform compliance constraints into performance drivers. Automated collection, reliable data, accelerated reporting—without sacrificing quality or compliance.

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