The provident gap is not a technology failure – it is a challenge for institutional alignment.
By Ioannis Ioannou, associate professor of strategy and entrepreneurship in London Business School
In some parts of East Africa, AI tools are increasingly capable of predicting precipitation models, crop failure and soil degradation. Satellite imaging and automatic learning models shed light on planting schedules and the risk of flag pests early. These tools – developed by Agritech startups and increasingly integrated into the supply strategies for multinational agro -industries – offer resilience through foresight. But while global companies adjust the supply and exposure to coverage, small operators – who produce about a third of the world’s food – often lack the ways to act on the same ideas. Irrigation, credit and institutional support are rare. Provident is not the constraint. The capacity is.
This asymmetry indicates a deeper challenge: the growing gap between those who can anticipate disturbance and those who have the means to respond. Artificial intelligence is to reshape the way we assess climate risk, optimize the use of resources and sail the volatility of the supply chain. But it can also expand the existing disparities, less by directly harming the actors with low capacity than to accelerate the adaptive advantage of those already in advance. As foresight becomes central to the sustainability strategy, the question goes from who can see the risk of who can act on it – and who is positioned to do it more effectively than the others.
At the heart of this change is what I call the “provident gap”: the expansion of the distance between insight and the agency. The problem is not data availability. Many actors – municipalities, agricultural cooperatives, suppliers – now have access to forecasts, dashboards and models. The problem is that insight, in the absence of funding, technical tools or assaults, often leaves actors aware of the risks but unable to manage it. The result is an unequal resilience, where some accelerate while others have trouble keeping the pace.
AI could strengthen this model. Companies with advanced modeling to reconfigure supply, redirect investment and coverage operations. Suppliers in more vulnerable environments host the consequences. The risk moves, but does not decrease. It is a form of selective adaptation: people with resources strengthen their position, while others absorb the shock. Over time, these dynamic risks undermine both equity and stability. A transition that achieves risk without strengthening shared capacity creates fragility in the system.
Agriculture illustrates this dynamic, but the model extends far beyond. Cities with ways to invest in the planning of infrastructure integrated into AI improves energy efficiency and emergency interventions. Others, especially in the world South, operate with obsolete systems and limited technical capacity. In insurance, AI reshapes climate risk prices, pushing bonuses up or eliminating coverage in high -risk areas. And in supply chains, predictive analysis allows companies to revive disturbances, while those on the front line remain vulnerable.
These changes introduce a systemic risk which is often underestimated. When only certain actors adapt, disturbance costs can be helped in sectors and geographies. Fragility at the margin – with regard to small operators, subcontractors or overexclusted public agencies – can be rejected outside. Consider the 2022 floods in Pakistan: extreme weather conditions have forced global retailers to move orders and revive logistics, but small suppliers have been faced with months of operational paralysis and loss of income. Without adequate capacity to absorb shocks at all levels, the system as a whole becomes more brittle. Concentrated resilience cannot guarantee collective stability.
This reveals a central tension. AI is often promoted as an inclusion force, but without governance aligned for this purpose, it may do the opposite. The provident gap is not a problem. It reflects the underlying disparities in capital, capacity and institutional design. Without deliberate attention to how foresight is distributed – and the way in which the action is activated – the gap will increase.
What does a fair transition look like in these conditions? Conventional framing has focused on costs, advantages and protections, in particular for workers and communities. These remain important. But in the context of AI, justice must also mean access to adaptability. The transition cannot only depend on who already has the tools to respond. He must help others acquire them. It is not only a question of equity. This is a condition for managing the risks shared in a connected world.
This perspective has direct implications for institutions. First, we need investment in public provident infrastructure. The predictive tools must be designed and deployed with a large conviviality in the mind. This includes climate models with free access, data collaborators and analyzes adapted to subressource parameters. National adaptation plans and resilience strategies should be based on intelligence which reflect the constraints of the real world. Above all, this infrastructure should not remain compartmentalized in ministries or multilateral organizations. It must be made accessible to people on the front line of disruption – local governments, cooperatives and civic organizations with the credibility of acting and the trust to be mobilized.
Second, we need IA-Action partnerships. Companies using AI to manage their exposure should contribute to the adaptive capacities of suppliers, entrepreneurs and local communities. It is not a philanthropic gesture. This is a practical approach to reducing risk concentration through the value chain. Some companies already explore shared data platforms with suppliers or financing adaptation initiatives in the largest objectives linked to ESG. But these efforts remain isolated. What is necessary is a change in the state of mind – from extracting risks to risk co -management.
Third, we must update our understanding of fiduciary responsibility. Boards of directors and investors must wonder if the strategies compatible with AI strengthen resilience at the system level or simply strengthen protection at the level of the company. Do companies redistribute the risk through lower links or do they invest in wider capacity? These are strategic questions, not questions of conformity. The trustee obligation, in this context, should include attention on how forecasting tools influence risk allocation – and if they contribute to the creation of stable, inclusive and credible long -term value.
It is also worth recognizing that AI is not only a predictive tool. Generative models and large linguistic systems are increasingly shaping the way knowledge is accessible, decisions are supported and strategies are refined. These technologies can also widen the forms of adaptability, especially when designed for public or integrated benefit in front -line decision -making. But the existence of such potential does not deny the gap of foresight. He changes his contours. While AI becomes more anchored in business strategy and public infrastructure, the question remains: which can use these tools significantly – and under what conditions?
The trajectory of AI in sustainability is not predetermined. It will reflect the choices concerning governance, design and responsibility. The provident gap is not a technology failure – it is a challenge for institutional alignment.
AI is often evaluated by its ability to predict, automate or optimize. But in the context of sustainability, a different question is more important: does it support a transition that strengthens resilience through the system? The foresight concentrated without distributed capacity creates a fragility. Resilience must extend beyond the company, the sector or the region.
Those who shape the role of AI in the transition – business managers, investors, regulators – define more than tools. They shape the trajectories. The key problem is no longer whether AI can improve foresight. This question has been settled. The real question is whether we align this provident on the ability to act – with an emergency and deliberately, deliberately.
This is where leadership will be measured. Not by whom saw the risk first, but by whom the others were ready upon arrival.
Ioannis Ioannou is an associate professor of strategy and entrepreneurship at London Business School. His research focuses on the sustainability of businesses and the strategic integration of ESG issues by business and capital markets.
