Alexandra Mihailescu Cichon is chief commercial officer of RepRisk
Over the past years, the language around sustainability has matured – less about morals and more about materiality; less about compliance and more about competitiveness; less about harm reduction and more about redesigning how value is created.
Yet the core issues remain: biodiversity, human rights, governance and supply chain resilience.
The fundamentals haven’t changed: business conduct risks translate into operational, reputational, and financial consequences. Whatever the rhetoric, capital allocation is about managing risk and capturing opportunity – and sustainability remains central to both.
What’s new is the unprecedented speed and scale at which technology is reshaping how we live, work and make decisions. In responsible investing, advances in technology and evolving data layers are driving efficiency, productivity and sharper insights.
Let’s explore two innovations – Agentic AI and geospatial intelligence – and how they are set to redefine the landscape in 2026.
Agentic AI
In 2025, technology crossed a threshold for responsible investment. Artificial intelligence evolved from a tool you prompt into a semi-autonomous coworker capable of planning and executing multi-step tasks.
This shift to agentic AI – where AI agents collaborate with humans – is no longer theoretical. Early adopters in finance are piloting workflows where delegation replaces instruction.
By 2026, these pilots will scale into full workflow redesigns. AI agents will manage end-to-end processes, while humans intervene for exceptions. The upside is speed and freeing human capacity for higher-value work.
The challenge is risk. Scaling this transformation demands responsible AI with robust permissions, audit trails and sandboxing.
For investors, this is a governance imperative. AI-driven workflows will underpin risk analysis, proxy voting, scoring and stewardship decisions.
In private markets, where transparency is limited, orchestrating AI agents with human oversight can expand coverage across sectors and geographies. Done right, this hybrid approach strengthens due diligence and mitigates conduct risk.
Best practice is modularity: delegating specific tasks to specialised models rather than relying on a single AI black box. This ensures outputs remain traceable and less prone to hallucinations.
For financial institutions, traceability is critical. Every decision – from credit scoring to proxy recommendations – must leave a verifiable audit trail. As regulatory scrutiny intensifies, boards and asset managers will prioritise AI systems that combine accuracy with accountability.
Responsible investment is not just about what decisions are made – it is about how they are made.
Geospatial intelligence
Alongside AI, geospatial intelligence moved decisively into the mainstream in 2025. As US public climate-science funding waned, demand for private earth-intelligence and AI-powered risk analytics surged – covering floods, wildfires and methane emissions.
According to Grand View Research, the global geospatial analytics market was valued at about $114 billion in 2024 and is projected to reach $226 billion by 2030, reflecting rapid adoption across insurance, agriculture and supply chains.
Generative AI now powers mapping tools like Google Earth, making geospatial data interactive and accessible. Users can ask plain-language questions – “where are the highest flood risks?” – and instantly see visual answers combining satellite, weather and population data.
What once required technical expertise is now broadly available, shifting geospatial data from static reference to real-time practical input.
For responsible investors, this adds a materiality lens: Physical climate risks translate directly into asset valuations, creditworthiness, and portfolio resilience.
Swiss Re’s sigma report estimates global insured losses from natural catastrophes at $145 billion in 2025, with total economic losses exceeding $300 billion – continuing a nine-year trend above that threshold.
These figures underscore why investors increasingly demand location-specific risk insights: to price exposure accurately, stress-test portfolios and engage on adaptation strategies.
As technology advances, AI agents and geospatial intelligence will increasingly underpin how organisations approach due diligence, manage risk and uphold responsible practices.
The opportunity lies in detecting risks earlier and delivering more granular insights – pinpointing vulnerabilities where they matter most.
The challenge remains data integration – linking these technologies seamlessly with enterprise platforms and business conduct datasets. In a world of systemic climate risk, how and where matters as much as what.
