By Miracle Agholor

Every day, global digital systems generate more than 330 million terabytes of data; from financial transactions and satellite imagery to social behaviour, health records, and machine interactions. Yet most people still think of data as a byproduct of technology. In reality, data has become the most valuable economic asset of the modern age, and agentic artificial intelligence is rapidly learning how to extract, interpret, and monetize it at unprecedented scale.

This is not a distant future. It is already happening.
The world’s most valuable companies are no longer oil producers or manufacturing giants. They are data-first firms. In 2024, Alphabet, Amazon, Microsoft, and Meta collectively generated hundreds of billions of dollars in revenue, much of it driven not by physical goods, but by data intelligence—predictive models, targeted advertising, automated decision-making, and behavioural forecasting. Data is not just supporting these businesses; it is the business.

What has changed recently is the emergence of agentic AI—systems capable of acting autonomously, setting goals, making decisions, and adapting strategies with minimal human input. Unlike traditional AI tools that wait for prompts, agentic AI systems can initiate actions, coordinate with other systems, and optimize outcomes continuously. When combined with vast datasets, they become economic actors in their own right.

In financial markets alone, algorithmic and AI-driven trading now accounts for over 70% of equity market activity in the United States. These systems analyse enormous volumes of market data in real time—price movements, sentiment signals, macroeconomic indicators—and execute decisions faster than any human could. Hedge funds and asset managers using advanced AI models have reported efficiency gains of 20–30%, not through better intuition, but through better data utilization.

Beyond finance, data mining has quietly become one of the most profitable activities in the global economy. Consumer data fuels advertising markets worth over $700 billion annually. Location data, biometric data, and behavioural data are increasingly traded, modelled, and monetized—often invisibly. The companies that dominate these spaces are not necessarily those with the best products, but those with the deepest data reservoirs and the most advanced AI systems to exploit them.
Agentic AI accelerates this trend. These systems can identify new data sources, refine models without supervision, and discover patterns humans would never see. In effect, data becomes a self-compounding asset: the more data an AI system consumes, the better it becomes; the better it becomes, the more value it extracts; the more value it extracts, the more data it attracts.

This creates a powerful feedback loop—and a growing imbalance.
While corporations and advanced economies race ahead, many developing regions remain data-rich but value-poor. Vast amounts of raw data are generated in emerging markets, yet the economic benefits are often captured elsewhere, where compute power, AI infrastructure, and regulatory leverage reside. Data colonialism, once a theoretical concern, is now an observable economic pattern.

Policymakers are struggling to keep pace. Regulatory debates still focus on privacy and ethics—important issues, but insufficient on their own. The deeper question is who owns data, who profits from it, and who controls the AI agents acting upon it. Without clear frameworks, agentic AI risks concentrating economic power even further, transforming data wealth into a force that deepens inequality rather than drives shared prosperity.
Yet the opportunity is enormous. If governed responsibly, data and agentic AI could unlock productivity gains across healthcare, education, agriculture, and public services. McKinsey estimates that AI could add up to $4.4 trillion annually to the global economy. The challenge is ensuring that this value does not accrue to a narrow group of firms and nations.

The future economy will not be defined solely by capital or labour, but by data intelligence, the ability to collect, interpret, and act on information at scale. Agentic AI is the engine driving that transformation. The question is no longer whether data will shape economic power, but whether societies will shape the rules under which that power operates.
If data is the new currency, then agentic AI is learning how to mint it, move it, and multiply it. What remains undecided is who benefits, and at what cost.

Miracle Agholor, an expert, wrote in from Lagos