Redefining Sustainability while AI settles into your boardroom

Diversity, Equity, and Inclusion (DEI) and Environmental, Social, and Governance (ESG) programs are under pressure worldwide. Headlines suggest budget cuts and rolling back initiatives, but this may be less of a retreat and more of a realignment. According to Deloitte’s 2022 Corporate Sustainability Survey, 61% of executives said they were “re-evaluating” sustainability efforts under current financial constraints. That re-evaluation could be a crucial, if overdue, reset—one that invites a more intelligent, data-driven approach to corporate social responsibility.

Accountability has always been the Achilles’ heel of ESG and CSR. On paper, companies commit resources to social investments or environmental projects, often backed by tax benefits or marketing wins. In South Africa, businesses can write off up to R10,000 by donating to Public Benefit Organizations (PBOs), effectively investing in their own future market sustainability. It’s a noteworthy model, yet as Harvard Business Review bluntly stated in a 2021 analysis, “Companies fail to track the data that actually matters.” Many organizations don’t even measure their own operational metrics accurately, so how can they be expected to measure an initiative far removed from their daily workflow?

When companies do try to measure impact, errors—both accidental and intentional—often creep into the data. In one real-world instance, a client’s AI-assisted data review uncovered an NGO whose monthly income jumped from R600,000 to R66 million overnight. The culprit? Two extra zeros in a spreadsheet. A mistake this trivial can completely warp averages, job creation stats, and even broader strategies around grant allocation. As Bill Gates famously said, “How you gather, manage, and use information will determine whether you win or lose.” In sustainability terms, it can mean the difference between effective change and wasted resources.

Another case showed a grant-funded aquaponic fishing project where more funding bizarrely led to less output—production plummeted from 3 million tons to 1 million, then to 500,000 over three years. The official report, intended to impress sponsors and government agencies, read like a wall of jargon with no quantifiable performance indicators. No one challenged the numbers; no one had a reason to suspect a crash in actual yield. A McKinsey Global Survey on ESG found that 83% of executives struggle to measure long-term social and environmental outcomes, exposing a large blind spot for potential greenwashing and inadvertent failures.

So where does this leave us? Enter artificial intelligence—not just the buzzword, but the proper application of AI tools to sift through thousands of rows of data and pinpoint suspicious spikes, missing entries, or inconsistent reporting. Properly deployed, AI can even cross-check internal reports against external benchmarks and historical patterns. This turns spreadsheets from an unreadable morass into something that reveals meaningful insights. The World Economic Forum recently noted that “ESG data lies in plain sight—if you know where to look,” underscoring the need for better tools and methodologies.

Even the best AI, however, remains just that—a tool. Anomalies must still be interpreted by domain experts. If you run a fish-farming initiative, for example, you need aquaponics specialists who can confirm whether a 30% dip in fish tonnage is normal for the season or a red flag signaling imminent collapse. AI can highlight the issue, but the corrective action often hinges on human expertise. This synergy is essential for truly robust ESG programs: a feedback loop where technology surfaces hidden truths and people use their judgment to respond effectively.

Most organizations also face a vast universe of “unknown unknowns.” The Johari’s Window concept applies here: we don’t know what we don’t know, especially when it comes to unfamiliar metrics or rapidly evolving community needs. The 2020 KPMG Survey of Corporate Responsibility Reporting showed that over 70% of large companies had no standardized process for verifying social and environmental metrics across projects. AI-driven approaches can consolidate data, flag anomalies, and even suggest new indicators. That’s where real transformation begins: not only can you verify results, but you can also uncover novel solutions to problems you never knew you had.

Staying true to your organization’s core purpose is another critical part of this reset. If your mission is food security through aquaponics, focus first on fish production figures—everything else should be secondary. Community workshops, sustainability panels, and training sessions are worthwhile only if they don’t derail the core metric that matters: providing a stable food source. Yet, it’s all too easy to lose track of that main objective once a handful of secondary indicators pile up, each demanding attention and budget. AI can keep an eye on every data stream, but it can’t impose strategic discipline. Leaders must decide whether an activity directly boosts fish tonnage (or whatever your main driver is) or simply makes for a nice press release.

All signs point to ESG not disappearing but maturing. Organizations that adapt, combining rigorous data management with cutting-edge analytics and specialist knowledge, will find a clearer path to both impact and profitability. By catching errors early and refining core metrics, companies can genuinely align social investments with their financial health. As a CEO quipped in a Fortune roundtable last year, “Saving the planet should be profitable, or it’s just another donation. And if we measure it right, it will be.”

The hard truth is that sustainable initiatives often fail for lack of consistent, trustworthy metrics. Instead of allowing outdated spreadsheets and one-off PR stories to define your sustainability journey, it’s time for an overhaul. Realignment doesn’t mean retreat; it means refocusing with the right data, the right experts, and the right technology. AI, for all its controversies, offers a way to sift, verify, and compare oceans of information—uncovering the insights that make or break real progress. If this is indeed a great ESG reset, it’s one that, done properly, can amplify corporate accountability and lead to a more prosperous, sustainable future for everyone involved.