Most Organizations Are Failing Their ESG Commitments. The Problem Isn't Ambition.

IDC's research on sustainability performance points to a consistent root cause and a clear path forward.

The ESG commitments are on the record. The targets are set. The board presentations have been made.

And then the numbers come in. According to IDC, 65% of organizations have not met their ESG compliance requirements. Only one in three has fully met its sustainability goals. This isn't a story about organizations that don't care. It's a story about organizations that care, committed publicly, and are now falling short in ways that create regulatory, reputational, and financial risk simultaneously.

IDC's Infobrief, Boost your Sustainability Performance with ERP-Centric, AI-Driven Solutions, diagnoses why this gap persists and what it takes to close it.

The Data Problem at the Root of It

The most consistent finding across IDC's research is that the sustainability gap is fundamentally a data quality problem. 37% of organizations lack accurate, trusted data for ESG reporting. 41% report insufficient internal sustainability expertise to manage what's being asked of them.

This isn't a capabilities problem or a commitment problem. It's an infrastructure problem. Most organizations are managing sustainability data the same way companies managed financial data before ERP existed: in disconnected tools, manual processes, estimates, and spreadsheets that were never designed to support audit-ready reporting.

The consequence is predictable. ESG data is often derived from industry averages rather than actual values. Reporting processes are labor-intensive and error-prone. And when regulators or investors ask for defensible, auditable numbers, organizations can't always provide them.

Why the Regulatory Stakes Are Rising

Over 1,000 new ESG regulatory developments are underway globally. The shift from voluntary to mandatory reporting is not a future state. It is in motion. Europe's CSRD is already in effect for large companies. The SEC's climate disclosure rules are advancing in the US. California has passed its own sustainability reporting standards.

The expectation these frameworks are converging on is essentially what financial reporting already demands: accuracy, auditability, traceability to source data, and leadership attestation. Organizations that have been managing sustainability data informally will not be able to meet that bar without changing the underlying infrastructure.

IDC is direct on this point: sustainability data must be managed with the same precision as financial data. The organizations best positioned to meet rising regulatory requirements are those that have moved sustainability management into ERP-centric, cloud-based environments where data quality, auditability, and compliance can be systematically managed rather than manually assembled.

What the Data Shows About Organizations That Get This Right

IDC found a meaningful performance gap between organizations using ERP-based sustainability solutions and those that aren't.

→ 74% of companies with an ERP-based sustainability solution have high confidence in their data quality

→ 83% have high confidence in their ability to meet reporting requirements

→ Organizations with an ERP-based sustainability solution are 76% more likely to have achieved the highest level of sustainability maturity

That last figure is striking. Sustainability maturity, where sustainability is integrated into business processes and continuously monitored, reviewed, and improved, is not primarily a function of how much organizations have invested in sustainability initiatives. It's a function of whether the data infrastructure supports it.

Where AI Fits In

IDC's research also points to a significant shift in how sustainability programs will operate.

76% of organizations believe AI will be very important or critical to their sustainability initiatives. 64% expect their sustainability software to incorporate AI or GenAI in the next one to three years.

The use cases are practical. At the beginner stage: understanding the regulatory environment, performing materiality assessments, tracking ESG priorities across stakeholder groups. At the intermediate stage: breaking up data silos, providing insights across business functions, automating collection from external stakeholders. At the advanced stage: anticipating climate risks on supply chain activities, continuously improving operational performance through real-time insights and recommendations.

The organizations that will make the most of AI in sustainability are those that have already built the data foundation. AI applied to poor data produces poor results faster. The infrastructure decision comes first.

The Path Forward

IDC's key takeaways are clear: manage sustainability data like financial data, in an ERP-centric, cloud-based, AI-enabled solution. Use AI to automate reporting and gain actionable insights. Leverage the specific AI capabilities that match your organization's current maturity level rather than trying to skip stages.

The window for getting ahead of regulatory requirements is narrowing. Organizations that build the right foundation now will find compliance manageable and performance improvement achievable. Those that don't will find themselves reacting to requirements they can't yet meet.

At Qubittron, building that foundation on SAP is part of the work we do with clients navigating exactly this challenge.