For many years, the infrastructure and intelligence that support finance grew on their own. Payments, banking rails, and compliance systems were the main parts of finance. Most decisions were still made by people, with the help of static reporting tools. This separation often created delays between when financial activity occurred and when insights could be generated, limiting the ability of organisations to respond in real time.
In the Gulf, a region defined by rapid digitisation and state-backed innovation agendas, AI is getting embedded into financial infrastructure itself. This integration is already changing how businesses work at scale, manage risk, and use capital. It is also reducing the time between transaction and decision, enabling a more responsive financial environment.
From Systems of Record to Systems of Decision
Traditional financial systems were designed to just record transactions with data that was stored, reconciled, and reviewed after the fact. This often meant that insights were retrospective, relying on periodic reporting cycles rather than real-time access to information. AI changes that dynamic by turning infrastructure into a real-time decision engine, where insights are generated around the clock. Organisations can now act on live financial signals as they emerge. The implication is that financial infrastructure is beyond just about moving money efficiently. There is a concrete understanding of where money flows in real time and acting on it with precision. Infrastructure is evolving from a passive system of record into an active system of decision.
AI at the Point of Transaction
The integration of AI into payment and spend systems is one of the most significant advancements. Instead of analysing transactions after they occur, AI is now applied the moment a transaction is initiated to assess context, historical purchase behaviour, and policy constraints instantly. This changes the nature of control. Financial policies are no longer enforced retrospectively but embedded into the transaction layer itself, enabling organisations to prevent non-compliant spend, detect anomalies, and assess risk instantly. It also reduces reliance on manual audits and post-transaction reviews, which are often resource-intensive and delayed. The scale of this shift is reinforced by the rapid expansion of digital payments globally. According to the World Bank’s Global Findex Database, more than two-thirds of adults worldwide now make or receive a digital payment. In high-growth markets like the Gulf, where digital adoption is accelerating faster than the rest of the world, embedding AI into these flows transforms every transaction into both an execution and a data signal.
Each transaction contributes to a continuously evolving understanding of financial behaviour, improving forecasting and control.
Infrastructure as a Strategic Asset
There is a structural advantage in this transition for the Gulf’s financial ecosystem. Many institutions and fintech platforms in the region are not constrained by legacy systems. They are building on modern, API-driven infrastructure that allows AI to be integrated natively rather than layered on top. This reduces complexity and enables faster deployment of new capabilities. At a macro level, this shift supports the region’s wider economic priorities. The UAE aims to raise the digital economy’s contribution to GDP to around 20% within the next decade, with Dubai to transition 90% of all transactions to digital payment methods by the end of 2026. Saudi Arabia’s digital economy is already valued at $131 billion, representing around 15% of national GDP. Under Vision 2030, the Kingdom aims to expand this contribution by a further $13 billion by 2030. Financial infrastructure sits at the centre of these ambitions. Payments, lending, and liquidity flows underpin every sector, from logistics to real estate to e-commerce. Embedding AI into this layer amplifies efficiency across the entire system, turning infrastructure from a cost centre into a source of competitive leverage. It also enables organisations to extract greater strategic value from financial data, rather than treating it as a by-product of operations.
Intelligence built by industry
Different industries need financial infrastructure built around their operating realities. In travel, payments are especially complex because companies manage high transaction volumes, multiple suppliers, foreign currencies, booking systems, refunds, and tight reconciliation windows. This makes travel expense management a strong example of why AI-enabled finance cannot be generic. Qashio’s partnership with Visa reflects this shift, with the Visa Commercial Choice Travel programme and an Dh100 million investment to digitise payments for online travel agencies and travel management companies, while improving multi-currency payments, integrating with booking tools and GDS platforms, and improving reconciliation and liquidity.
The New Risk Paradigm
As AI becomes embedded in financial systems, the nature of risk is also changing. Traditional models relied heavily on historical data and periodic reviews. AI-driven systems operate continuously, recalibrating risk in real time based on live inputs. This allows organisations to shift from reactive risk management to proactive risk mitigation. This has measurable implications. Organisations lose approximately 5% of revenue to fraud each year. Reducing that leakage requires more than better reporting. It requires systems that can identify irregularities as they emerge and respond without delay. At the same time, increased reliance on automated decision-making introduces new considerations around transparency, governance, and auditability. Ensuring that decisions can be explained and validated becomes critical, particularly in regulated environments. In this context, trust becomes a function of system design rather than institutional messaging. It is built on how reliably these systems perform under pressure and how transparently decisions can be traced and understood.
From Automation to Autonomy
With AI in financial infrastructure, systems are no longer limited to executing predefined rules and are capable of learning from patterns, adapting to new conditions, and optimising financial outcomes over time. This changes the role of finance teams. Instead of focusing on manual oversight and reconciliation, they are setting parameters, validating outputs, and making strategic decisions to align with the company’s vision. The emphasis shifts from understanding what has already happened to determining what should happen next. This requires new skill sets, including data interpretation and system governance. The Gulf is entering a phase where financial infrastructure and AI are interdependent layers of the same system. With strong regulatory momentum, high digital adoption, sustained investment in emerging technologies and Collaboration between governments, financial institutions, and fintech players, the region is positioned to lead this transition. Ultimately, the integration of AI into financial infrastructure is reshaping how financial decisions are made, executed, and scaled in real time. Institutions that move early will gain more than efficiency; they will help define a financial system that is more adaptive, predictive, and resilient.
This opinion piece is authored by Armin Moradi, CEO and Founder of Qashio.
Source: Tahawul Tech