Most organisations have now completed their first double materiality assessment. For many, it was a significant undertaking. Often turning out to be expensive, time-consuming, and heavily reliant on external consultants. And while the first assessment delivered something of real value, a consistent pattern has emerged in conversations with sustainability leaders across sectors: the model that got them through cycle one is not sustainable beyond it.
The cost is high, the output is static, and the methodology walks out the door with the consultant. And when auditors, board members, or regulators ask the organisation to defend its materiality positions, the spreadsheet offers no answers.
This is not a minor operational inconvenience. No, it’s a structural problem with the way double materiality has been approached, and it’s prompting the need for a fundamental change.
The Manual Model Is Breaking Down
The pattern is recognisable. An external team is brought in to run the assessment. They conduct the analysis, gather the data, apply their methodology, and deliver a deck and a set of static outputs. Then they leave. The IP, the logic, and the reasoning behind the scores leaves with them.
What remains is a snapshot, a point-in-time view of impacts, risks, and opportunities that begins to age the moment it is produced. When questions arise (and they certainly will arise) the organisation struggles to explain how it got to where it did. That is not a defensible position.
Regulators are not asking consultants to justify materiality positions; they are asking companies. Auditors are not reviewing the consultant's methodology, they are reviewing yours. The responsibility is internal, even when the work has been outsourced. This misalignment between accountability and ownership is at the heart of why the manual model is failing.
Beyond defensibility, there is a deeper issue. Double materiality is not a static exercise. Your business changes, the regulatory environment changes, climate hazards, supply chain dynamics, and market conditions all shift continuously. A materiality assessment that reflects the world as it was eighteen months ago is not a reliable basis for decision-making today.
Four Structural Shifts That Define a Technology-Led Approach
The transition from manual DMA to a technology-enabled capability is not simply a matter of digitising existing processes. It involves a different way of thinking about what a double materiality assessment is for, and who owns it.
Shift one: From arms-length project to internal capability
The old model treats double materiality as a project to be outsourced. The emerging model treats it as a capability to be owned. Technology takes on the heavy lifting (data collection, aggregation, synthesis), freeing the internal team to focus on the decisions that matter: engagement, judgement, and the reasoning that needs to be documented and defended. When the methodology is embedded in the platform rather than in a consultant's head, the organisation can explain exactly how it got to its conclusions. That explainability is the foundation of defensibility.
Shift two: Double materiality as live risk management
A well-executed DMA is not a compliance artefact; it is a live risk register. The material topics it identifies are the same topics that should be feeding into enterprise risk management. The impacts, risks, and opportunities it surfaces should be tracked as signals change: new regulations, operational developments, emerging science, shifts in the market. A DMA that sits in a silo, disconnected from the broader risk management architecture, is an opportunity wasted.
Shift three: Continuous tracking rather than periodic snapshots
Materiality does not pause between reporting cycles. The world does not pause. Technology enables a fundamentally different operating model; one where the platform is always on, monitoring signals, updating context, and flagging changes that require attention. This does not mean the organisation is constantly producing new outputs. It means the organisation is always working from a current and accurate picture of its material landscape, rather than one that is months or years out of date.
Shift four: From deterministic scoring to probabilistic assessment
Most material topics are inherently forward-looking. Climate hazards, supply chain disruption, regulatory change; these are not certainties, they are probabilities. Yet traditional DMA approaches treat them as if they can be captured by a score on a one-to-five scale, determined at a single point in time by a panel of individuals. Technology and AI enable a different approach: grounding the assessment in probability and exposure data, drawing on a wide range of signals, and presenting that information in a way that supports human judgement rather than trying to replace it.
The Role of AI: What It Does, and What It Doesn't
This is worth addressing directly, because the role of AI in this context is frequently misunderstood in both directions; either overstated as something that automates decision-making, or dismissed as a marginal efficiency tool.
The reality is more precise. AI is genuinely good at the production tasks that currently consume the majority of a sustainability team's time: collecting data, aggregating it across sources, synthesizing evidence into a coherent picture, and presenting that picture in a way that is actionable. In a typical manual DMA, around 80% of the team's effort goes into exactly these activities. That is 80% of time spent before any meaningful analysis has even begun.
Technology shifts that ratio. When AI is doing the production work, the team can focus on what actually requires human expertise: reviewing the evidence, challenging the outputs, engaging with stakeholders, exercising judgement, and documenting the rationale for decisions. Every materiality determination, from individual topic scores to the overall materiality matrix, remains a human decision. AI provides the information, humans make the calls.
It is also worth noting how AI operates in a well-designed system. Rather than relying on a single model, a mature AI-driven DMA platform draws on multiple AI agents working in parallel; examining the same information from different angles, comparing conclusions, and surfacing the points of convergence and divergence. The output is not a single number or recommendation, but a richer, more nuanced view of what the evidence actually shows. That is what enables better human judgement, not a replacement of it.
The Return on Investment
The value of a technology-led approach operates at several levels simultaneously.
Quality improves because everything is centralised, evidence is traceable, and methodology is consistent. Positions are explainable because the reasoning behind them is documented in the platform, not scattered across emails and consultant slide decks.
The time investment changes materially. The deep dive that used to consume months of effort begins to feel like a refresh, because the foundations are already in place. For organisations that have set up their platform correctly, the consensus emerging from the market is that a deep-dive DMA is warranted roughly every three years, with lighter-touch refreshes in the years between. When the continuous monitoring is working, even a full refresh feels manageable.
And perhaps most importantly, sustainability starts to function as a live decision-making tool rather than a compliance obligation. The materiality assessment is no longer a static report sitting in a folder. It is a dynamic view of what is happening to the organisation's impact and risk landscape, available to inform decisions as they arise.
That is the shift that matters most. Not from manual to digital, but from periodic to continuous. From a project mindset to a capability mindset. From owning the output to owning the process.
The effort involved in maintaining that capability, once established, is surprisingly low. The ongoing marathon, as it turns out, is far less demanding than the sprint it replaces.
Ready to see what a technology-enabled DMA looks like in practice?
Socialsuite's AI-powered Double Materiality Assessment platform brings together continuous monitoring, probabilistic scoring, and AI-assisted analysis — all in a system your team owns, understands, and can defend. Book a demo and see it for yourself →
This article is adapted from the Socialsuite webinar "From Manual DMA to Technology Refresh: Rethinking Double Materiality for a Dynamic World," hosted on 12 May 2026. The full recording is available on demand at https://www.socialsuitehq.com/webinars/from-manual-dma-to-technology-refresh-rethinking-double-materiality-for-a-dynamic-world .
Dr. Tim Siegenbeek van Heukelom is Chief Impact Officer at Socialsuite, where he leads the company's sustainability vision and helps shape software and advisory solutions for double materiality, climate risk, sustainability reporting, and ESG regulatory readiness.
