ESG consulting is getting harder
ESG advisory work now sits much closer to core business decisions than it did even a few years ago. Sustainability insights increasingly inform capital allocation, risk management decisions, and long-term business strategy. Clients are demanding far more from their ESG consultants (often on a smaller budget than before).
At the same time, the regulatory environment has become more complex. Consultants are navigating overlapping requirements across the Corporate Sustainability Reporting Directive (CSRD), the International Sustainability Standards Board (ISSB), and other regimes, often for clients operating in multiple jurisdictions. The work requires more rigour, clearer audit trails, and stronger internal consistency than before.
Rising expectations, shrinking room to manoeuvre
Despite higher stakes, many sustainability budgets are smaller than they were even last year. Political uncertainty and macroeconomic headwinds have led organisations to scrutinise advisory spend more closely.
ESG consultants are in a bind. Clients need more from them than ever, but on smaller budgets. The consultants that make it will need to work out how to scale their advisory offerings without also scaling headcount to the same extent.
In 2026, AI can make this possible.
Traditional consulting models are not suited to the new world of knowledge work
Most ESG consultancies still rely on labour-intensive workflows. Junior teams manually review long, complex documents. Senior reviewers reconcile inconsistent outputs. Methodologies live in spreadsheets, slide decks, and individual heads.
That model struggles as complexity and volume increase. Adding headcount raises costs and coordination overhead, but it does not reliably improve consistency or reduce delivery risk. As ESG advice becomes more exposed to regulatory and legal scrutiny, this fragility matters.
AI expands capacity while improving quality
Used well, AI is a way to protect analytical quality under pressure and to make expert judgment go further. AI absorbs the mechanical parts of ESG analysis so consultants can focus on interpretation, advice, and engagement. That includes repetitive document review, first-pass gap analysis, and cross-checking disclosures against multiple requirements.
Where AI creates the most leverage for ESG consultants
1 — Benchmarking and research for strategy
Benchmarking underpins much ESG strategy work, but it is time-consuming and fragile. Comparing policies, disclosures, and sustainability performance across peer groups often requires teams to extract and normalise information from dozens or hundreds of documents, each structured differently.
AI helps by reviewing large volumes of disclosures consistently and applying a consultancy’s methodology across every company in a peer set. It can surface patterns, outliers, and gaps that inform strategic recommendations without relying on one-off manual analysis. This allows benchmarking to function as a repeatable input into strategy, rather than a bespoke exercise rebuilt for every engagement.
2 — Reporting and regulatory compliance
Sustainability reporting and compliance work is where volume and complexity collide. Consultants must interpret evolving requirements, assess disclosures against multiple frameworks, and identify gaps with precision.
AI supports reporting and compliance by scanning sustainability reports, annual filings, and policies at scale, then flagging missing, weak, or inconsistent disclosures. When consultants can apply this same logic across every assessment, they get better consistency and, as a result, shorter review cycles.
Tools like Manifest Climate, which are designed specifically for ESG analysis, can assess disclosures against leading frameworks like TCFD, CSRD, and ISSB, offering a structured starting point for analysis across multiple regulatory regimes.
For larger consulting firms, there is often value in customization. Many firms put their own twist on frameworks like CSRD, layering in a qualitative lens, weighting certain elements differently or interpreting requirements in line with their advisory philosophy. AI can mirror this customized approach to analysis by embedding firm-specific methodologies directly into the compliance workflow. Instead of producing generic gap assessments, the analysis reflects how the consultancy actually interprets and advises on the regulation.
3 — Pre-investment due diligence and ongoing portfolio monitoring
For consultants with clients in financial services, ESG advisory work increasingly extends beyond reporting into investment decision-making and stewardship. Consultants are expected to support pre-investment due diligence, ongoing portfolio monitoring, and engagement strategies over time.
AI enables teams to review large deal pipelines without sacrificing depth, track portfolio companies as new disclosures emerge, and identify emerging risks that warrant engagement or escalation. Because analysis can be applied consistently over time, stewardship becomes a continuous process rather than a periodic review tied to reporting cycles.
4 — Business development and client acquisition
The same benchmarking and research capabilities that support strategy work can also strengthen business development. AI allows consultants to quickly analyze public disclosures across target companies, identify regulatory exposure, surface material gaps, and understand how companies compare to peers. This gives consultants a clear view of which companies are likely to need advisory support.
It also gives consulting firms a powerful reason to reach out to ideal customers. Instead of leading with a generic pitch focused on the consultancy, salespeople can walk into early conversations with specific, evidence-backed observations about a prospect’s disclosures. That level of insight, delivered almost instantly, can make a strong impression during scoping discussions and RFP processes.
Scaling up disclosure analysis in this way can also become a powerful data source for consultancies looking to publish original reports and become thought leaders in corporate sustainability.
How AI changes the economics of ESG consulting
When AI supports these core use cases, consultancies can take on more complex work without proportionally increasing headcount. Consultants can deliver insights and strategies to clients faster, but without compromising on rigor.
There are also second-order effects. Consultants may find that making first-pass analyses more thorough and consistent cuts down on the number of review cycles needed, and relieves the burden on senior reviewers, who no longer need to spend so much time correcting basic issues.
Being able to embed AI models with in-house frameworks and methodologies also means teams become less dependent on specific individuals with institutional knowledge, which is key to reducing operational risk and scaling advisory offerings.
Just as importantly, AI can improve output consistency and auditability, which matters in our particularly litigious times. As ESG advice carries greater regulatory and legal exposure, the ability to show how conclusions were reached is critical, and AI tools that do this give consultants the confidence they need when presenting work to clients.
| Case study: How PwC uses AI to support ESG advisory work As ESG advisory work becomes more complex, manual research and disclosure review can limit how quickly consultants deliver insight. At PwC, AI is being used to remove that bottleneck without diluting expert judgment. By combining Microsoft Copilot with Manifest Climate’s expert-curated sustainability data, PwC teams can query structured ESG disclosures in real time. Instead of spending hours reviewing reports, consultants get faster visibility into what clients are disclosing, how those disclosures align with regulatory requirements, and where material gaps exist. This approach shifts time away from mechanical research and toward higher-value advisory work, allowing PwC to deliver confident, decision-grade ESG insights without expanding team size. [READ MORE] |
Where AI can introduce risk if used poorly
Used without clear methodology or built-in guardrails, AI can introduce new risks into ESG advisory work.
The biggest problems arise when using popular generic tools like ChatGPT and Claude. These platforms pose two main problems to ESG consultants: opacity and data security.
The first problem, opacity, refers to a lack of transparency about how models are designed and conclusions are reached. With a tool like ChatGPT, consultants will never get true insight into how and why it reaches the conclusions it does. It’s a black box. However, purpose-built tools like Manifest Climate are designed differently. The platform is transparent about how its models are applied, clearly links conclusions back to source material, and provides confidence indicators so users can judge the strength of the underlying evidence.
The second problem is data security. ESG consultants regularly work with sensitive, non-public client information, which raises legitimate concerns about how that data is handled when using widely available AI platforms. Purpose-built solutions like Manifest Climate are designed with these constraints in mind, offering clearer governance, defined data-handling practices, and controls that help consultants understand how their data is used and protected.
What to look for in AI tools for ESG consulting
Not all AI tools are fit for purpose. ESG consultancies should look for solutions that reflect and enforce their proprietary methodologies, handle complex disclosures that vary in structure, and provide clear traceability back to source documents.
It is also important to distinguish between generic AI tools and platforms designed specifically for ESG workflows and regulatory interpretation. The difference becomes apparent once outputs are used in client-facing advice, audits, or regulatory conversations. Tools that cannot explain how an answer was derived quickly become a liability.
-> Manifest Climate was built to help ESG consultants deliver more with less. Find out more.
Scaling output, not headcount
The ESG consultancies that thrive will not be those that attempt to outgrow their competitors by adding junior staff members. They will be the ones who redesign their delivery models in ways that allow them to capture more market share without also adding to their bottom line.
There is also a human dimension to this approach. Manual review-heavy models contribute to burnout, long review cycles, and talent attrition. By reducing the grunt work, AI can make an ESG consultant’s working day more enjoyable and less cognitively taxing.
AI makes it possible to meet rising expectations, serve more clients, and protect quality, while helping teams enjoy their working hours just a little more.
How Manifest Climate supports scalable ESG advisory
The best AI tools for ESG consultants are not generic tools like ChatGPT and Claude, but specialist tools designed specifically for the kind of work sustainability professionals do on a daily basis.
That means tools that can handle complex regulations and proprietary methodologies, analyze disclosures at scale, and produce traceable, trustworthy edits that clients and regulators can stand behind.
Manifest Climate is built specifically to support ESG consultants and financial institutions. The platform helps teams apply their methodology consistently, analyse large volumes of disclosures with confidence, and surface decision-useful insight quickly.
For consultancies navigating higher stakes, tighter timelines, and growing complexity, Manifest Climate offers a way to scale expertise rather than headcount.
If you want to see how AI can support deeper ESG insight across strategy, compliance, and financial decision-making, you can explore Manifest Climate or request a demo.
