Biodiversity blind spots: Why the next frontier of sustainability needs GeoAI
For years, biodiversity sat just outside the core of most corporate sustainability strategies. It was acknowledged but rarely measured, recognized...
Regenerative agriculture is no longer just a fringe idea. Once regarded as a niche approach championed by a handful of pioneering farmers and NGOs, it has since become central to sustainability strategies in food, agriculture, and consumer goods. Large-scale producers are exploring new methods to restore soil, enhance biodiversity, and reduce reliance on chemical inputs. Major brands are setting ambitious targets for regenerative sourcing, and increasingly, investors and regulators are watching closely.
The appeal is clear. Regenerative agriculture promises a method to decarbonize farming systems while enhancing long-term productivity and resilience. It provides companies with a path to fulfill climate and nature commitments without compromising commercial outcomes.
But as momentum increases, so does the pressure. These strategies must now transcend mere aspiration. Businesses are being asked not only to invest in regenerative practices but also to demonstrate that they are effective.
And that is where the challenge begins.
Over the past few years, regenerative agriculture has shifted from pilot programs and press releases to mainstream sustainability targets. From global FMCG companies to specialty commodity traders, commitments to regenerate land, restore soil health, and reduce climate impact are now integrated into core business strategies. These goals are often linked to broader frameworks like Science-Based Targets for Forest, Land, and Agriculture (FLAG) or national incentives for nature-based solutions.
Yet, despite the surge in ambition, companies are struggling with a common problem: how to measure what matters. Definitions of “regenerative” vary by region, crop, and supply chain. Indicators like soil carbon, biodiversity, and water retention are often challenging to assess consistently across different geographies. Many of the metrics used today rely on self-reporting, sampling, or local certification systems that lack scale and comparability.
For sustainability teams, this creates a growing tension. The more investment flows into regenerative practices, the greater the pressure to demonstrate results. However, without consistent, verifiable data, it becomes challenging to show whether progress is being made, where it is occurring, and how it can be improved.
This is not a technology gap; it’s a visibility gap.
As regenerative agriculture transitions from pilot to program, the cost of uncertainty escalates. Without clear visibility into how practices are being adopted and the impact they’re having, even the most well-intentioned strategies begin to lose momentum.
For many companies, this lack of clarity manifests in familiar ways: delayed reports, inconsistent claims from suppliers, or challenges in answering questions from investors and auditors. In practice, sustainability teams may be working diligently to support farmers and collect field data, but the information they gather often arrives too late or lacks the necessary granularity for effective decision-making.
Meanwhile, expectations continue to rise. Regulators are tightening requirements for environmental disclosures. Buyers want sourcing data that goes beyond certification. Consumers and advocacy groups seek evidence, not just commitments.
If organizations scale regenerative programs without establishing systems to track and verify what’s actually happening, they risk more than just missed targets. They risk losing trust within their supply chains, in the market, and across their teams.
Visibility is no longer optional; it’s the foundation of credibility.
To scale regenerative agriculture effectively, companies need a better way to understand what’s happening across the landscapes they depend on. They require more than data points collected from a few plots or sporadic field visits. They need a system that demonstrates how practices are evolving, where outcomes are improving, and where support is still needed.
GeoAI—geospatial artificial intelligence—provides a new lens.
By combining satellite and drone imagery with machine learning, GeoAI can detect and monitor regenerative indicators across large areas with a level of consistency and frequency that manual methods can’t match. Shade trees, cover crops, hedgerows, soil exposure, and land use shifts can all be analyzed visually over time. Instead of relying on fragmented reports or one-off audits, teams receive continuous insights into the adoption and performance of regenerative practices.
This visibility helps close the loop between strategy and action. It enables sustainability leaders to identify high-impact areas, prioritize investments, and demonstrate progress with confidence. Additionally, it fosters a common language across procurement, ESG, and technical teams—connecting outcomes in the field with goals in the boardroom.
When regeneration becomes visible, it is scalable.
The challenge for many organizations isn’t deciding whether to invest in regenerative agriculture; it’s figuring out how to implement it on a large scale without losing sight of what’s actually working.
For companies like Nespresso, this has meant using GeoAI to track changes in agroforestry practices across coffee farms in Brazil. At Fazenda Três Meninas, for example, satellite imagery combined with machine learning has been used to detect shade trees, hedgerows, and cover crops over time. This data doesn’t just validate progress on a single farm; it lays the groundwork for broader program design, helping to replicate success and monitor adoption across an entire region.
British American Tobacco applies similar methods across its global leaf operations, supporting over 90,000 directly contracted farms. Their focus on regenerative agriculture includes practices that improve soil health, reduce erosion, and increase water retention. GeoAI provides a way to monitor these outcomes more consistently and with greater reach than manual inspections ever could.
These aren’t isolated projects. They represent a shift in mindset—from relying on limited, self-reported information to building systems that generate continuous, independent evidence. They also demonstrate how regeneration can move from aspiration to execution, supported by the right tools, data, and partnerships.
Regenerative agriculture holds enormous promise. It provides a means to rebuild soil health, enhance supply chain resilience, and align sustainability with long-term value. However, without a method to monitor what’s actually happening in the field, that promise can’t be delivered with confidence.
As expectations grow, so does the need for better systems—not only for reporting outcomes but also for viewing them in real time, understanding them in context, and using that insight to enhance both strategy and implementation.
That’s why visibility matters. It’s not merely a tool for compliance; it’s a foundation for leadership, trust, and the transformation that regenerative agriculture aims to achieve.
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