Across the GCC, banks and financial institutions have embraced generative AI with speed and enthusiasm. Developers are using code assistants, leaders are demanding productivity gains, and transformation programmes increasingly include “GenAI enablement” as a visible workstream.
Across the GCC, banks and financial institutions have embraced generative AI with speed and enthusiasm. Developers are using code assistants, leaders are demanding productivity gains, and transformation programmes increasingly include “GenAI enablement” as a visible workstream.
But the truth is clear: high adoption has not yet converted into high impact. Most organisations are still stuck in pilot mode — achieving small pockets of efficiency without translating them into material business value.
This briefing outlines what the market is learning, and what banks and regulators in the region need to do next.
While two-thirds of software organisations now use GenAI tools, the measurable gains remain modest — typically 10–15% efficiency improvements at the individual
developer level.
Most banks still run legacy development processes, heavy governance cycles, and disconnected teams. This means any time saved through AI is simply absorbed into existing inefficiencies — never flowing through to faster delivery, reduced risk, or improved compliance outcomes.
GenAI applied to old processes yields old results.
Financial institutions in the region operate under three pressures that magnify the problem:
Basel, cyber resilience, AI governance, model risk, and new supervisory frameworks require faster, more consistent software releases — not sporadic AI-assisted coding.
GenAI cannot generate value if upstream architecture, testing, security reviews and change controls still operate in slow, manual ways.
Banks must ensure any AI usage is tightly governed, explainable, and fully auditable — not a free-form experiment at the developer’s desk.
These realities mean the GCC cannot rely on tool-level adoption alone. The sector must move towards AI-native engineering, where GenAI is woven into processes, not layered loosely on top.
The institutions beginning to see meaningful payoff treat GenAI as a transformation catalyst, not a tactical enhancement.
They commit to:
Embedding AI across design, architecture, coding, testing, security, documentation, and deployment.
Removing redundant handoffs, compressing review cycles, and structuring delivery around rapid iterations supported by AI accelerators.
Introducing AI firewalls, secure model access, granular entitlements, audit logs, and risk-aligned controls — enabling safe adoption at scale.
Reskilling teams, redefining roles, and creating norms where AI is a permanent co-worker, not a novelty.
The result isn’t just faster output — it’s better engineered, more secure, regulator-ready software, delivered consistently.
For banks, this is a chance to unlock real transformation:
For regulators, the shift is equally strategic:
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Generative AI will not transform your organisation because you have tools. It will transform your organisation when you redesign how you deliver software, how you govern technology, and how you align development with regulatory expectations. The Gulf’s most forward-looking banks are now moving decisively from pilots to payoff. With the right architecture, controls, and operating model, GenAI becomes not an experiment — but a competitive advantage.
