Exploring the ESG Space: 2026 and Future Projections

Current Market State

The ESG market has reached a critical point in 2025 as it transitions from an optional narrative to an operational requirement. However, this projection predates the significant political headwinds that emerged in 2024-2025. The ESG software market space is expected to grow from $4.1 billion (2025) to $8.9 billion (2030) at 16.9% CAGR [1].

The current market shows significant pressure both from a customer and investor perspective requiring higher demand for sustainability, ethics, and corporate responsibility transparency across the whole supply chain [2]. Customers show interest in moving beyond annual reports to continuous ESG performance tracking while all ESG data should be digitally tagged through XBRL Taxonomy [3]. Transparency and traceability are still major concerns in the ESG space with 94% of investors believe corporate sustainability reports contain unsupported claim [4].

A paradoxical trend has emerged recently. While ESG fundamentals remain strong, companies are increasingly downplaying public ESG commitments. 80% of large and multinational companies are revising ESG strategies due to political adjustments [5]. Furthermore, anti-ESG sentiment peaked in certain US markets, with some states restricting ESG-aligned investments [6]. At the same time, 90% of executives expect ESG-related resistance to persist [7]. This phenomenon of "greenhushing" has accelerated, where companies continue sustainability initiatives but avoid public ESG terminology.

The main conclusion? The future of ESG remains volatile and unpredictable. The need and demand are here. The scientific evidence speaks for itself. However, there is still resistance, lack of trust, and uncertainty on how the ESG market will finally end in the next decade. In this study, the aim is to address the following topics:

The 2026 Landscape

Investment Flows

The 2026 market projection demonstrates significant impact in favor of the ESG market that is expected to rise during 2026. Despite the political pressure shown in the ESG market during 2025, ESG-related assets under management were projected to reach $33.9 trillion by 2026, from $18.4 trillion in 2021 (12.9% CAGR) [8]. Asia-Pacific ESG ETFs are at $50 billion (10% annual growth) with Taiwan accounting for 50%+ of Asia-Pacific ESG assets. Furthermore, China's clean energy ETFs are expected to rebound with extended EV subsidies [9].

Technology Market Expansion

As with every major domain today, AI is set to play a significant role in the ESG ecosystem. The use of AI not only covers the space in ESG as a supporting mechanism, in many cases forms the backbone of such tools, showing a growing trend from $1.24 billion (2024) to an estimated $14.87 billion by 2034 at 28.2% CAGR [10]. The generative AI segment is capturing approximately 41.8% of the market share with cloud-based solutions dominating with 12%+ CAGR through 2032. Large enterprises represent 68.1% of ESG software demand. Digital reporting with XBRL tag requirements from 2026 will be a trend [11].

Regulatory Milestones in 2026

The EU regulatory landscape is undergoing significant recalibration. In December 2025, the Council and the European Parliament reached a provisional agreement to simplify both the Corporate Sustainability Reporting Directive (CSRD) and the Corporate Sustainability Due Diligence Directive (CS3D). The revised framework significantly narrows the scope of mandatory reporting, applying CSRD obligations primarily to very large companies with at least 1,000 employees and €450 million in net turnover, while listed SMEs are removed entirely [12]. Transitional exemptions are granted to companies that fall out of scope. For CS3D, the thresholds now target firms with at least 5,000 employees and €1.5 billion turnover, with the greatest influence over global value chains [13]. The CS3D transposition deadline is postponed to July 2028, with company compliance required by July 2029 [14]. The revised CS3D also adopts a risk-based due diligence approach and removes the obligation to adopt a mandatory climate transition plan [15]. While these changes aim to reduce administrative burden, they also represent a deliberate shift from broad, unverifiable ESG claims that create significant enterprise risk toward more focused, materiality-based sustainability targets that are realistic, traceable, and aligned with transparent reporting requirements.

In Asia-Pacific many regulations are coming into force. In China, ~450 listed companies must publish mandatory sustainability reports starting with FY 2025 [16]. Singapore mandates climate-related disclosures for all listed companies starting FY 2025, with all companies required to report Scope 1 and 2 GHG emissions [17]. In Japan AI-driven ESG scoring systems are gaining traction, with academic research demonstrating AI-based scoring can cover ~3,800 listed firms compared to traditional agencies covering only ~430 companies [18]. In India, ESG is intensifying with the top 250 listed companies now facing mandatory reporting [19].

California has enacted groundbreaking state-level climate disclosure laws requiring large companies doing business in the state to report GHG emissions (SB 253,>$1B revenue) and climate-related financial risks (SB 261, >$500M revenue). SB 261 enforcement is temporarily paused pending federal appeals court review [20]. Most large US companies are maintaining their climate targets despite political pressure [21]. Greater emphasis is given to demonstrating ROI from sustainability investments with a shift from “ESG” terminology to “sustainability” in communications [22].

Emerging Themes for 2026

Biodiversity loss and ecosystem collapse is ranked as the second most critical long-term risk after extreme weather events [23]. Purpose-driven work is critical for 86-89% of Gen Z and Millennials, with roughly half willing to turn down assignments or employers over ethical concerns including environmental practices, diversity issues, and employee well-being [24]. Supply chain transparency ranks among the most critical issues, with Walmart's Project Gigaton model expanding, with over 5,900 suppliers involved [25]. Drought and unsustainable water and land practices are accelerating water stewardship efforts, especially in water-scarce areas[26].

AI integration definitely holds a pivotal role presenting both opportunities and risks requiring ethical governance. The WEF Global Risks Report 2025 ranks adverse outcomes of AI technologies as the number 6 long-term risk [27], and AI-driven misinformation as the dominant short-term risk[28].

Our Analysis

The outreach campaign targeted 206 companies across a wide range of sectors, aiming to evaluate their involvement in sustainability and ESG-related software solutions. By engaging organizations of different sizes and industries, the analysis sought to identify which sectors and company sizes are most willing to adopt and most in need of sustainability and ESG-related tools.

The effort generated strong initial engagement demonstrated in figure 1, with 12.14% (i.e., 25 companies) direct engagement and 22.82% (i.e., 47 companies) indirect engagement. For the rest of the companies (no active engagement), Frojigo conducted internal research using publicly available information to ensure they were accurately represented in the analysis.

Approximately one in three businesses choose to communicate directly or indirectly, indicating significant early interest. This implies that ESG and sustainability solutions are being actively explored by organizations of all sizes and sectors. The outreach showed that many businesses are receptive to discussions and eager to learn where new solutions in this field may lead.

From the 206 companies assessed, 47.09% (97) are enterprises with more than 1,000 employees, 22.33% (46) are large companies with 250–999 employees, 17.48% (36) are medium-sized organizations with 50–249 employees, and 13.11% (27) are small companies with up to 49 employees.

An interesting observation is revealed when looking at the companies that engage directly or indirectly during the analysis. Among these participants, enterprises represent nearly half of all engagement at 47.42% (46 out of 97). In comparison, engagement from large, medium, and small companies accounted for 26.09% (12 out of 46), 19.44% (7 out of 36), and 25.93% (7 out of 27), respectively. This pattern indicates that enterprises show the strongest interest in the sustainability market and exploring emerging solutions in this field, due to the regulatory, strategic, and operational pressures they are facing.

At a sector-level overview, new information emerges. Of the 206 companies approached, the distribution by sector is demonstrated as follows: Banking/Finance (20), Energy/Utilities (55), Consumer Goods (52), Manufacturing/Industrial (32), IT/Technology (17), Hospitality/Services (16), and Transportation/Logistics (14).

Engagement rates vary across these groups. The number of companies that participated through direct or indirect engagement is shown in figure 5: Banking/Finance (6 out of 20), Energy/Utilities (25 out of 55), Consumer Goods (10 out of 52), Manufacturing/Industrial (12 out of 32), Technology/IT (7 out of 17), Hospitality/Services (5 out of 16), and Transportation/Logistics (7 out of 14). In relative terms, this corresponds to engagement levels of 30.00%, 45.45%, 19.23%, 37.50%, 41.18%, 31.25%, and 50.00% respectively.

The strongest interest comes from the Transportation/Logistics, Energy/Utilities, and IT/Technology sectors. These sectors show engagement rates exceeding 40% , suggesting that organizations operating in heavily regulated and operationally complex environments are actively seeking new tools potentially offering direct stakeholder engagement and improved transparency in their reporting processes.

What Customers Want

Our analysis, revealed key pain points and gaps in sustainability practices that organizations are actively seeking to address.

The Role of AI

Artificial intelligence (AI) is increasingly being leveraged to enhance ESG performance by enabling organizations to integrate complex, multi-source data into continuous, actionable insights, moving beyond traditional, static reporting methods.

As the demand for transparency, accountability, and sustainability intensifies, the field of reporting is undergoing a major transformation. Traditional reporting models are no longer sufficient to reflect the full scope of modern corporate performance, particularly when ESG factors are involved. The growing intersection of AI and ESG is reshaping disclosure practices, with AI-driven automation, real-time analytics, natural language processing (NLP), and predictive modelling enabling more dynamic, accurate, and forward-looking reporting processes [29]. A recent study developed a digital framework that integrates AI, Process Mining, and Robotic Process Automation to improve ESG risk evaluation in sustainable construction management [30]. Through a simulated case study of 100 construction projects, the framework demonstrates how automated data collection through web scraping and business intelligence tools can be combined with predictive analytics to improve ESG data consistency and support evidence-based decision-making [31]. AI's NLP capabilities unlock the value in unstructured text sources such as company annual reports, sustainability reports, media articles, and regulatory documents by extracting key ESG-relevant themes, sentiment, and narrative. This enables companies to systematically analyze stakeholder discourse, detect emerging ESG risks, and interpret regulatory language [32].

Using AI models, organizations can run continuous materiality assessments rather than static, periodic ones. The reports are stored in a structured format, which makes it easy to reproduce and appropriate for audit and verification. This allows stakeholders to review transparent and traceable outputs instead of relying on opaque algorithmic decisions [33]. This approach helps companies stay aligned with evolving double-materiality standards, as required by regulatory regimes like ESRS. Authentic AI adoption can become a strategic asset for corporate sustainability performance, but only when organizations implement it with guidance by "Trustworthy AI" principles to mitigate risks [34]. Together, these steps show how the system converts complex and inconsistent sustainability disclosures into standardized compliance outcomes, with the potential to evolve toward real-time recalibration of ESG issues as new data, stakeholder signals, and regulatory developments emerge.

AI and machine learning models can be used for predictive ESG risk analysis by leveraging historical ESG disclosures, environmental data, and financial indicators. A recent study showed that advanced AI techniques, including ensemble and deep‑learning models, significantly outperform standard regressions in forecasting a firm's carbon‑risk exposure; by capturing complex, non‑linear relationships embedded in ESG disclosures [35]. This capability aligns with broader trends in AI-driven sustainable finance, where predictive analytics play a key role in shaping long-term strategy and supporting stakeholders navigating evolving sustainability reporting standards. AI-driven report generation can significantly reduce the burden of manual ESG disclosure by automatically synthesizing structured and unstructured data into framework-aligned narratives. AI systems are increasingly seen as essential for improving reporting quality while reducing manual effort and adaptation time to evolving ESG standards.

By effectively integrating AI models, companies can transform ESG management from a periodic, compliance-focused exercise into a dynamic, continuous strategic asset that drives proactive decision-making, real-time risk monitoring, and long-term value creation for both stakeholders and the organization.