As we commemorate Earth Day this year, it's important to confront our planet's harsh realities. Despite the numerous efforts of scientists, activists, and the tech-savvy younger generation, the ecological crisis deepens, underscored by persistent natural resource deterioration and escalating climate challenges. Today, we are driven more than ever to harness innovative technologies, including artificial intelligence (AI), to advance environmental, social, and corporate governance (ESG) initiatives and attain sustainability for a better future.

Learn “How Organizations Are Using NLP To Detect Greenwashing.”

Deteriorating Natural Resources

Over the past decades, our natural reserves have alarmingly diminished. By March 2024, the Earth’s average surface temperature has increased to approximately 54.9°F (12.7°C), a seemingly minor increase that masks significant polar ice melt and accelerated climate change.

Greenhouse gas emissions have increased to 37.4 billion metric tons in 2023. According to the United Nations, this is caused by burning fossil fuels, industrialization, food production, over-consumption, and manufacturing.

The loss of biodiversity is growing so fast that we now have around 44,000 species extinct due to climate change, drought, and floods. For example, plastic waste is considered the main contributor to ocean acidification, along with oil and toxins dispensed in the ocean by transportation and shipping companies. Moreover, mass production and mass consumption of food, fast fashion, furniture, and more are, along with urbanism, major factors leading to deforestation and natural resource depletion.

Human Concerns and Environmental Anxiety

These issues not only affect nature but also human well-being. A recent study shows that younger generations face a new form of anxiety called environmental anxiety. It results from their fear of where this crisis leads them and the unclear and ambiguous future. For example, we'll likely suffer from clean water scarcity by 2050, which might produce diseases and epidemics. At this rate, the weather will become hotter, damaging nature and causing massive wildfires. As a result, some areas might become inhabitable, causing mass migration and immigration, resulting in overpopulated cities.

Leveraging AI and ESG for a Sustainable Future

Innovative technologies such as AI are revolutionizing our approach to sustainability. AI tools analyze large amounts of data to monitor ESG metrics effectively, helping organizations to make informed decisions that align with sustainability goals. These technologies facilitate smarter resource management, reduce waste through predictive analytics, and improve energy efficiency. By integrating AI with ESG initiatives, businesses can enhance their operational efficiency and contribute significantly to environmental conservation.

Learn “How Successful Investors Are Using AI to Get ESG Data: A Quick Guide.”

Hope for Change

Despite these daunting challenges, there is room for optimism. From awareness campaigns to employing technology for recycling and reusing resources to building robotic animals to prevent animal captivity, researchers and organizations are doing their best to limit environmental damage. Governments are altering laws and regulations and signing treaties in partnership with active associations and organizations, which are joining efforts to improve life on Earth. Emerging businesses strive to leave an environmental and social footprint by integrating the United Nations' Sustainable Development Goals (SDG) within their corporate culture.

Conclusion

In sum, if we, as a whole, take proper action, the current climate threat could diminish within the next few decades. Helping us get there are more affordable means for renewable energy generation and organic produce and public awareness. We're all capable of making a difference through funding organizations, monitoring our waste and consumption, or participating in local community actions and initiatives. Also, we can learn more about how to help protect wildlife. But NOW is the time to take action to guarantee a better future for us and future generations.

Happy Earth Day!

SESAMm has a large data lake of more than 20 billion articles (growing by 5–10 million a day) and 14 years of data in 100 languages. But its size alone is not what makes it good; it’s a refined process to find the exact data you want that makes it better.

Here’s an example to help explain the point. We’re sometimes asked for help researching data to forecast and monitor the commodities market, even by large companies with their own commodities desk of traders and quant researchers. Why would they seek help from outside their firm?

Simply put, traders want an edge. They want information advantages that others are likely to miss, so they look to alternative data from various sources, anything that adds value and is from different angles. And, as it turns out, commodities are a more challenging segment to analyze when it comes to alternative text data. Unlike for companies, commodity texts are scarcer and need more domain knowledge to unravel their implications. A simple sentiment analysis doesn’t bring enough relevant information.

For a more in-depth view,  join us as we discuss NLP-derived alternative data, its benefits, challenges for researchers, and why bigger isn’t always better in the world of data.

Read the full article on Quant Finance.

In theory, a portfolio with no ESG controversies signals low risk. In practice, experienced analysts treat it as a warning sign. The absence of alerts often reflects not resilience, but limited coverage, fragmented data, or incomplete aggregation. What looks like reassurance may instead point to a gap in visibility.

This dynamic came up repeatedly during our recent webinar, Private Markets in 2026: Macro Trends, ESG Shifts, AI Innovation and What It Means for Deal-Flow. The discussion highlighted how gaps in coverage and aggregation can shape investor perception, particularly when portfolios appear “quiet,” not because risks are absent, but because relevant information is not being captured.

This dynamic matters more than ever as private market due diligence intensifies. With fewer deals, longer holding periods, and higher selectivity, investors are spending more time scrutinizing assets before acquisition and monitoring them for longer after entry. Yet the informational foundation behind many ESG assessments has not caught up with these expectations.

When "No Data" Becomes "No Risk"

Private assets operate under persistent disclosure constraints. Unlike public companies, most private firms do not produce standardized, recurring ESG disclosures, nor do they benefit from consistent analyst coverage. These gaps are structural and unlikely to disappear in the near term.

In this context, silence is ambiguous. A clean ESG screen may indicate the absence of material issues, but it may just as easily signal that no relevant information was captured. Language limitations, fragmented sources, and uneven coverage across geographies and asset types all contribute to this uncertainty.

This dynamic is particularly visible in secondary transactions. Deal teams often need to assess large portfolios under tight time pressure, with limited access to management and incomplete identifiers. In such cases, relying on the absence of signals can create false confidence rather than reduce risk.

How Weak Coverage and Duplicated Signals Create Blind Spots

Even when information exists, it is not always immediately actionable. Adverse media has become a valuable substitute where structured ESG data is limited, offering outside-in visibility into private assets. However, it is not without challenges. Without robust aggregation and cross-language consolidation, the same issue can appear repeatedly across multiple articles, jurisdictions, and languages, creating duplication rather than clarity. At the same time, gaps in coverage or weak filtering can allow other material risks to go undetected.

At the same time, some portfolios appear unusually quiet simply because the underlying assets fall outside the scope of traditional datasets. ESG and reputational expectations in private markets remain fragmented, with bespoke workflows driven by LP-specific requirements. This lack of convergence makes it difficult to distinguish between genuinely low exposure and analytical gaps.

More data does not automatically resolve this problem. Without traceability, source quality, and a way to assess financial, legal, or operational materiality, increased volume can add noise without improving decisions. In that environment, silence can be just as misleading as signal overload.

What Meaningful ESG Visibility Looks Like Under Disclosure Constraints

A core takeaway from the webinar was that point-in-time ESG assessments are no longer fit for purpose in private markets. A single diligence exercise conducted at entry cannot capture emerging governance failures, litigation, reputational issues, or supply chain risks over multi-year holding periods.

Instead, meaningful ESG visibility combines three elements:

• Broad coverage, to avoid portfolios appearing "low risk" simply because assets are not captured.
• Aggregation and severity assessment, to separate isolated news from controversies with real financial or operational implications.
• Continuous monitoring, so the original risk thesis evolves as new information emerges rather than remaining static.

This approach reframes ESG from a compliance exercise into a source of informational advantage. Rather than concluding that no alerts mean no risk, investors use ESG signals to guide follow-up questions, prioritize deeper diligence, and identify issues that were not visible at entry.

Replacing False Comfort with Informed Uncertainty

Private markets will continue to operate with imperfect information. Disclosure gaps, opaque supply chains, and bespoke reporting demands are inherent to the asset class.

Treating “no issues detected” as a conclusion creates false comfort. Treating it as a hypothesis, contingent on coverage quality and monitoring depth, aligns ESG analysis with how risk actually emerges in private assets.

SESAMm’s AI Technology Reveals ESG Insights

Discover unparalleled insights into ESG controversies, risks, and opportunities across industries. Learn more about how SESAMm can help you analyze millions of private and public companies using AI-powered text analysis tools.