Why ESG Reporting is the Next Big Data Challenge for Businesses

Eden Smith • October 16, 2025

Businesses today don’t just face financial data, they now also collect huge volumes of ESG data: emissions, social responsibility metrics, governance structures, supply chain practices, human rights compliance, and more. What was once a compliance checkbox is rapidly evolving into a strategic necessity. But that evolution brings a new set of data challenges that many companies are only just beginning to confront.


Regulatory Pressure and Reporting Scope Expansion


Regulation is increasingly pushing ESG from voluntary disclosure to mandatory reporting. For example, the EU’s Corporate Sustainability Reporting Directive (CSRD) expands reporting requirements to more companies and more detailed ESG areas. Businesses are seeing not just more data to collect, but more kinds of data, higher granularity, and tighter demands for auditability and assurance.


But many organisations are not ready. A Workiva survey found that 83% of companies believe collecting accurate data for CSRD will be a challenge. ESG Today Meanwhile, only around 29% of companies feel prepared for ESG data assurance, per recent KPMG research. KPMG As regulations deepen, the cost of lagging behind increases, not only through financial penalties, but reputational risk.


Data Quality, Standardisation, and Scope 3 Complexity


Collecting raw data is one thing; ensuring that data is accurate, consistent and comparable is another. Many senior executives report that data quality is one of the biggest hurdles in their ESG reporting journey. Sustainability News+2CIO+2


Scope 3 emissions (those from supply chain and indirect impacts) remain particularly difficult. It involves pulling data from many suppliers, often with very different data maturity levels or inconsistent systems. Deloitte’s 2024 Sustainability Action Report found that while many companies are making progress, Scope 3 reporting is still “rare” in practice, and many organisations cite data from suppliers as both incomplete and inconsistent. Sustainability News+2Ace Cloud Hosting+2


Standardisation is also a problem. Multiple frameworks—such as GRI, SASB, TCFD, and ESRS (under CSRD), all have overlapping but distinct requirements. This patchwork makes it difficult to align and compare data across organisations or geographies. Manifest Climate+2PwC+2


Technology, Resource & Governance Gaps


Many ESG data tasks still rely heavily on manual work—gathering, cleaning, and consolidating information from different sources, often via spreadsheets. Even in large organisations this leads to inefficiencies, delays, errors, and limited auditability.


Another big challenge is skills and resources: many companies don’t have enough in-house ESG or data experts. According to KPMG, skills and resources are viewed as the single biggest challenge in ESG assurance readiness. Proper technology platforms, data pipelines, and infrastructure, such as having a data warehouse or single source of truth for ESG metrics, are increasingly essential.


Governance structures are often under-built. Without clearly defined roles, data ownership, responsibility, audit trails, and metadata standards, it becomes difficult to ensure consistency, reliability, and confidence in ESG reporting.


Seizing the Opportunity


The businesses that succeed will be those that go beyond compliance and treat ESG reporting as strategic intelligence. This means using ESG data not just to report, but to inform leadership decisions, risk management, investment strategy, supply chain decisions, and operations.

Several organisations are increasingly using AI and automation to streamline data collection and improve accuracy. Platforms that integrate with utilities, supplier systems and supply chain data are helping reduce manual workload and human error.


Also, early movers are investing in analytics dashboards, scenario modelling, and predictive ESG indicators, looking ahead rather than just reporting what's already happened. This gives them competitive advantage.


What You Can Do Now


  • Map your data sources: Understand where ESG data lives in your organisation, including internal systems, supplier data, third-party datasets.
  • Prioritise metrics: Focus first on what matters most, those ESG areas that pose the biggest risk or opportunity for your business.
  • Invest in technology & automation: Tools to capture, process, validate ESG data can dramatically improve accuracy and reduce manual burden.
  • Build governance and ownership: Clear roles, responsibilities, data ownership, and quality controls across the organisation are essential.
  • Upskill your teams: ESG reporting demands both technical/data skills and subject-matter knowledge in sustainability, regulation, and materiality.


Final Thoughts


ESG reporting is fast becoming one of the most complex, but also most strategically valuable, data challenges businesses must master. The companies that fail to plan risk falling behind, not just in compliance, but in stakeholder trust, investor confidence, and competitive positioning.

Data isn’t just for finance or operations anymore, it’s central to how companies demonstrate responsibility, resilience, and long-term value.


If your organisation is looking to navigate ESG data complexity, build stronger reporting, or turn ESG into strategic value, it may be time to consider external analytics or data consulting support.

By Christa Swain December 3, 2025
Executive Summary: AI, Ethics, and Human-Centred Design Our recent Leaders Advisory Board event - designed in partnership with Corndel - featured three engaging sessions that explored how AI impacts human cognition, customer experience, and fairness. Here's what we learnt: 1. Think or Sink – Are We Using AI to Enhance or Reduce Cognitive Ability? Speaker: Rosanne Werner , CEO at XcelerateIQ & ex Transformation Lead at Coca-Cola Roseanne opened the day with an interactive and thought-provoking session, firmly positioning AI: “AI should be your sparring partner, not your substitute for thinking.” Her research revealed a striking insight: 83% of people using LLMs couldn’t recall what they wrote, compared to just 11% using traditional search . The message? It’s not about avoiding AI, but using it in ways that strengthen thinking , not outsource it. Roseanne explained how our brains form engrams - memory footprints that enable creativity and critical thinking. Over-reliance on AI risks weakening these pathways, reducing retention and problem-solving ability. She introduced the Mind Over Machine Toolkit , six strategies to use AI as a thinking partner: Provide Context First – Frame the problem before asking AI. Use AI as a Challenger – Stress-test ideas and uncover blind spots. Iterative Co-Creation – Collaborate, refine, and evaluate. Document Your Thinking – Keep reasoning visible. Reflective Prompts – Support reflection, not replace judgment. Sparring Partner – Test assumptions and explore risks. Roseanne summed it up with a simple rule: use Sink for low-value, repetitive tasks, and Think for strategic, creative decisions. 2. Designing Chatbots with Human-Centred AI Speaker: Sarah Schlobohm , Fractional Chief AI Officer Sarah brought a practical perspective, drawing on experience implementing AI across sectors - from banking and cybersecurity to rail innovation. She began with a relatable question: “Who’s been frustrated by a chatbot recently?” Almost every hand went up. Through a real-world example (redacted out of politeness), Sarah illustrated how chatbots can fail when designed with the wrong priorities. The chatbot optimised for deflection and containment , but lacked escape routes , sentiment detection, and escalation paths - turning a simple purchase into a multi-day ordeal. “Don’t measure success by how well the chatbot performs for the bot—measure it by how well it performs for the human.” Sarah introduced principles for better chatbot design: Human-Centred Design – Focus on user needs and emotional impact. Systems Thinking – Consider the entire process, not just chatbot metrics. Escalation Triggers – Negative sentiment, repeated failures, high-value intents. Context Awareness – Detect when a task moves from routine to complex and route accordingly. The takeaway? Automation should remove friction from the whole system - not push it onto the customer. 3. Responsible AI and Bias in Large Language Models Speaker: Sarah Wyer , Professional Development Expert in AI Ethics at Corndel “When we create AI, we embed our values within it.” She shared her journey tackling gender bias in large language models , from GPT-2 through to GPT-5, and highlighted why responsible AI matters. AI systems reflect human choices - what data we use, how we define success, and who decides what is fair. Real-world examples brought this to life: facial recognition systems failing to recognise darker skin tones, credit decisions disadvantaging women, and risk assessment tools perpetuating racial bias. Even today, LinkedIn engagement patterns show gender bias! Sarah made the point that simple actions - like testing prompts such as “Women can…” or “Men can…” - can reveal hidden disparities and spark vital conversations. To address these issues, Sarah introduced the D.R.I.F.T framework , a practical guide for organisations: D – Diversity : Build diverse teams to challenge bias. R – Representative Data : Ensure datasets reflect all user groups. I – Independent/Internal Audit : Test outputs regularly. F – Freedom : Create a culture where employees can challenge AI decisions. T – Transparency : Share processes without exposing proprietary code. Wrapping up the final session - before we opened the floor to panel questions and debate - Sarah created the opportunity to discuss how we address AI bias within our organisations by stepping through the DRIFT framework. Shared Themes Across All Sessions AI is powerful, but context matters . Human oversight and ethical design are critical . Use AI to augment thinking , not replace it. Measure success by human outcomes , not just automation metrics. We've had such great feedback from this event series - especially around the quality of speakers and the opportunity to have meaningful conversation and debate outside of functions. Definitely more in the events plan for 2026! If you'd like to be part of the conversation please navigate to our LAB events page to register your interest .
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