GCC AI Execution Challenge - Roland Berger Report Reveals Strategy-to-Scale Gap Across Gulf Organizations

A comprehensive new report from Roland Berger reveals that while nearly four out of five organizations across the Gulf Cooperation Council now embed artificial intelligence in their strategic plans, the region faces a critical execution challenge in translating AI ambition into enterprise-scale impact. The findings, based on insights from senior decision-makers across public and private entities, expose a widening gap between strategic intent and operational delivery.

EXECUTIVE SUMMARY

The Roland Berger AI Across the Gulf report, published in February 2026, presents a nuanced picture of AI maturity in the GCC. On one hand, the data shows remarkable strategic alignment: 50% of organizations already have a documented AI strategy aligned with national priorities, and a further 29% have strategies under development. Investment appetite remains strong, with 85% of organizations expecting AI budgets to rise in the coming year and close to 40% foreseeing significant increases. On the other hand, fewer than one in three organizations have built an AI operating model or clear governance process, and only 28% have established a dedicated ethics or compliance board.

STRATEGIC FOUNDATIONS: STRONG BUT INSUFFICIENT

The report identifies a clear shift in how GCC organizations perceive AI's value proposition. While AI was previously viewed mainly as a driver of operational efficiency, its value is now increasingly recognized across four dimensions. In efficiency, organizations want AI to speed up decision-making and improve its quality, not just reduce costs and boost productivity. In experience, they expect AI to enhance customer and citizen interactions in line with national goals for best-in-class government service delivery. In value creation, organizations look to AI for revenue growth and innovation through new digital services and business models. In risk and compliance, AI is expected to improve monitoring, detect anomalies, and reduce exposure.

COUNTRY-LEVEL INVESTMENT DYNAMICS

The investment landscape varies significantly across GCC member states. Saudi Arabia and the UAE show the strongest momentum, with 89% of organizations in each country planning to raise AI spending. Qatar follows closely at 86%, while Bahrain has a far smaller share of organizations expecting increases. Oman and Kuwait show similarly cautious profiles, although a majority of organizations in both countries still plan to raise their AI budgets in the next 12 months.

Nizar Hneini, Managing Director and Head of Digital and Services at Roland Berger, noted that AI has crossed the boundary between aspiration and commitment, stating that it is no longer treated as discretionary spending but as part of the core investment base required to deliver transformation.

THE EXECUTION GAP: BEHAVIORAL BARRIERS

Despite strong foundations and investment appetite, the report finds that many organizations struggle to fully advance their AI uptake. The biggest blockers of operational readiness are foundational rather than strategic. Data quality remains the primary concern, followed by technological readiness and funding beyond the pilot phase. Resistance to change affects 42% of organizations, cross-functional silos impact 40%, and weak performance management slows 39% of adoption efforts.

Critically, barriers vary by country. In Saudi Arabia, common constraints include technology readiness and data quality. In the UAE, resistance to change is more pronounced, reflecting the challenge of transforming established organizational cultures. In Qatar, talent gaps rank higher on the agenda, suggesting that the country's rapid AI infrastructure buildout has outpaced its human capital development.

PATH TO SCALE: OPERATIONAL MODEL REQUIREMENTS

The report outlines several requirements for organizations to bridge the strategy-to-execution gap. First, organizations need dedicated AI operating models that define clear ownership, accountability, and decision rights for AI initiatives. Second, data governance frameworks must be strengthened to ensure the quality, accessibility, and security of training data. Third, change management programs must address the behavioral barriers that prevent adoption at scale. Fourth, performance management systems need to incorporate AI-specific metrics that track both technical performance and business impact.

IMPLICATIONS FOR GCC COMPETITIVENESS

The execution challenge has significant implications for the GCC's global AI competitiveness. While the region has established strong strategic and financial foundations, the inability to scale AI beyond pilots risks creating a gap between the GCC and leading AI economies. The report suggests that the next phase of AI maturity in the Gulf will be determined not by the size of investments or the ambition of strategies, but by the ability to embed AI into day-to-day workflows, decision-making processes, and organizational cultures.

For policymakers, the findings reinforce the importance of complementing top-down AI strategies with bottom-up capability building. National AI strategies must be accompanied by practical toolkits, training programs, and governance frameworks that enable organizations to move from strategy to execution. The GCC's AI future depends not just on building infrastructure and attracting investment, but on developing the organizational capabilities to deploy AI at scale.