The Deep dive: implications of AI on technology, finance and regulation in 2026

By Puja Sharma

The deep dive’ is our bi-weekly exploration of a relevant topic, hot trend, or new product. For Prime subscribers only.

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As 2026 unfolds, artificial intelligence is no longer evolving quietly in the background of digital systems. It is moving decisively into the centre of economic activity, reshaping how technology platforms operate, how financial systems manage risk, and how regulators attempt to keep pace. According to the World Ethical Data Foundation (WEDF), the coming year will be defined by three AI-driven shifts that will have tangible consequences for banks, FinTechs, enterprises, and policymakers worldwide.

Drawing on its global research and policy engagement, WEDF argues that 2026 marks a transition point: AI stops being just an efficiency tool and starts behaving like an autonomous participant in digital and financial ecosystems.

Digital civil disobedience reaches platforms and payment systems

For John Marshall, 2026 will be the year digital civil disobedience becomes visible and unavoidable. As digital environments grow more restrictive—through tighter platform controls, surveillance-heavy architectures, and increasingly prescriptive regulation—users and developers will begin to actively bypass imposed constraints.

While this trend may appear cultural or ideological on the surface, its implications for technology and finance are practical and immediate. Modified applications, alternative interfaces, and unofficial integrations will increasingly sit outside sanctioned ecosystems. In payments and financial services, this could manifest as workarounds to platform rules, shadow FinTech tooling, or unofficial transaction flows that challenge fraud controls, compliance frameworks, and consumer protection mechanisms.

Marshall suggests that hacking will return to its original ethos: making systems do what people need them to do, rather than what platforms allow. Even if adoption remains limited initially, the impact will be felt by banks, payment processors, and digital platforms tasked with maintaining security, resilience, and regulatory alignment in an environment where users no longer fully accept imposed boundaries.

Who is under the radar?

Fully AI-run companies test financial frameworks

Another defining moment of 2026, according to Cade Diehm, will be the emergence of a genuinely AI-operated company. This would not be a partially automated enterprise, but a small business where ownership, management, marketing, customer engagement, payments, and accounting are all handled by artificial intelligence.

The business itself may be short-lived, Diehm predicts, potentially collapsing within a year. But its significance lies less in commercial success and more in the regulatory and financial questions it raises. Who is legally accountable when an AI runs a company? Who signs financial statements? How do banks conduct KYC, onboarding, or credit assessment when there is no human decision-maker? How do auditors, insurers, and tax authorities engage with a non-human entity?

Even a brief appearance of such a company in 2026 would expose gaps in corporate governance, financial regulation, and compliance regimes that were designed around human responsibility. For financial institutions, it signals an approaching need to rethink onboarding, risk assessment, and accountability in an era where economic activity may increasingly be initiated and managed by machines.

Why does it matter now?

Agentic AI becomes a governance and financial risk issue

Perhaps the most complex challenge of 2026 will come from agentic AI—systems capable of making decisions, taking actions, and interacting with other systems independently. Anna Babkina warns that agentic AI will force regulators to move beyond overseeing individual models toward governing entire ecosystems.

In financial services, the risks are particularly acute. Autonomous agents may optimise trading strategies, manage liquidity, automate lending decisions, or resolve disputes in real time. While these capabilities promise efficiency, they also blur accountability across data sources, APIs, counterparties, and decision chains.

Current regulatory frameworks remain largely model-centric, focusing on transparency, bias, and explainability at the algorithm level. But financial systems operate across interconnected networks, where the behaviour of one agent can cascade rapidly through markets and payment rails. In 2026, the absence of clear frameworks to describe, monitor, and govern agentic behaviour at scale will become a pressing concern for central banks, market regulators, and compliance teams.

Babkina argues that agility will be critical. With agentic systems being developed at extraordinary speed, governance will need to evolve iteratively rather than wait for perfect regulation. For finance, this may mean new approaches to oversight, real-time monitoring, and systemic risk management.

Why this matters for technology and finance in 2026

Taken together, these three developments point to a clear conclusion: in 2026, AI is no longer just supporting economic activity—it is actively shaping it. Digital disobedience challenges platform control, AI-run companies test the boundaries of corporate and financial law, and agentic systems introduce new forms of systemic risk.

For technology providers, FinTechs, banks, and regulators, the challenge will be balancing innovation with accountability. Systems built for efficiency and scale must now contend with autonomy, unpredictability, and blurred responsibility. The institutions that adapt fastest—by rethinking governance, compliance, and infrastructure—will be best positioned to operate confidently in an AI-driven economy.

2026, WEDF suggests, will not be the year AI becomes smarter. It will be the year AI becomes consequential.