AI in the GCC | Unlocking AI’s Potential for GCC Business Growth

AI in the GCC is rapidly evolving from a strategic ambition into a defining force reshaping the region’s economic and technological landscape.

Key Insights from AI in the GCC | Unlocking AI’s Potential for GCC Business Growth

Accelerated AI Adoption: The GCC region is poised for significant AI integration, moving beyond foundational models to advanced agent-based systems, mirroring global trends but with distinct local nuances.
Strategic Investment & Talent Focus: To truly harness AI’s power, GCC businesses must prioritize strategic investments in both technology infrastructure and, critically, in developing a skilled AI workforce.
Unique Regional Dynamics: The report highlights the importance of understanding specific economic, regulatory, and cultural factors within the GCC that will shape the trajectory and impact of AI adoption.

Introduction

As Gulf nations accelerate investment in digital infrastructure, data ecosystems, and innovation-driven agendas, artificial intelligence is becoming a catalyst for diversification, operational excellence, and global competitiveness. Yet, the path forward is not without complexity: fragmented data governance, talent shortages, and sector-specific adoption hurdles continue to shape how fast and how effectively AI value can be realized. At the same time, the region holds immense untapped potential, from leveraging sovereign data assets to pioneering AI applications in energy, logistics, finance, and smart cities. This deep dive explores the transformative impact of AI in the GCC, the unique challenges that define its adoption journey, and the high-value opportunities waiting to be unlocked.

This blog post has three main parts. The first part highlights the key points and findings from the McKinsey’s Global Survey on the state of AI in 2025, focusing on adoption trends, the proliferation of AI agents, value capture, strategies of high-performing organizations, and workforce impacts. The second part is a summary of key points and findings of McKinsey’s report “The state of AI in GCC countries: In pursuit of scale and value” that addresses the topic of AI in the GCC and provides tailor-made insights for GCC businesses. The last part is based on the first two parts and explores the transformative impact of AI in the GCC, the unique challenges that define its adoption journey, and the high-value opportunities waiting to be unlocked.

Part I: Key Findings from the “The State of AI in 2025: Agents, Innovation, and Transformation” by McKinsey

The McKinsey Global Survey on the state of AI, conducted between June 25 and July 29, 2025, reveals a landscape characterized by broadening AI usage but an uneven pace of progress in scaling and capturing enterprise-level value.

1. AI Adoption and Scaling Status

Widespread Use, Limited Scale: Nearly nine out of ten (88 percent) survey respondents report that their organizations are regularly using AI in at least one business function, an increase from 78 percent a year prior. However, the majority are still in the experimentation or piloting phase. Nearly two-thirds of respondents indicate their organizations have not yet begun scaling AI across the enterprise. Only about one-third of all respondents report scaling their AI programs across their organizations.
Deep Integration Lags: Most organizations have not yet embedded AI tools deeply enough into their workflows and processes to realize material enterprise-level benefits.
Scaling by Size: Larger companies (those with revenues of $5 billion or more) are more likely to have reached the scaling phase (nearly half of respondents) compared to smaller companies (29 percent of those with less than $100 million in revenues).
Functional Use: AI use is broadening across functions; more than two-thirds of respondents use AI in more than one function, and half report using AI in three or more functions. Historically prominent functions like IT and marketing and sales continue to lead, but knowledge management is now also one of the functions with the most reported AI use.

2. The Rise of AI Agents

High Curiosity: There is high curiosity surrounding AI agents—systems based on foundation models capable of planning and executing multiple steps in a workflow. Sixty-two percent of survey respondents say their organizations are at least experimenting with AI agents.
Scaling Agents: Twenty-three percent of respondents report their organizations are scaling an agentic AI system somewhere in their enterprise. However, use is not yet widespread, as most organizations scaling agents are only doing so in one or two functions.
Agent Adoption by Sector/Function: Agent use is most widely reported in the technology, media and telecommunications, and healthcare sectors. Within business functions, agent use is most commonly reported in IT and knowledge management.

3. Impact and Value Realization

Innovation as a Key Benefit: 64 percent of respondents say that AI is enabling their innovation, making it the measure most often cited for improvement. Nearly half of respondents also report improvement in customer satisfaction and competitive differentiation.
Limited Enterprise-Level Financial Impact: Just 39 percent of respondents report EBIT impact at the enterprise level attributable to AI. Where EBIT impact is reported, it is typically less than 5 percent.
Use-Case Benefits: Respondents report use-case level cost and revenue benefits.
– Cost reduction is most commonly reported in software engineering, manufacturing, and IT.
– Revenue increases are most commonly reported in marketing and sales, strategy and corporate finance, and product and service development.

4. Characteristics of AI High Performers

AI high performers—defined as respondents who attribute 5 percent or more of their organization’s EBIT to AI use and report seeing “significant value”—are pushing for transformative change and implementing robust best practices:

Ambitious Objectives: While 80 percent of all respondents set efficiency as an objective, high performers are more likely to also set growth or innovation as objectives for their AI initiatives. Organizations focusing only on cost may limit AI’s impact.
Transformative Agenda: High performers are more than three times more likely than others to expect their organizations to use AI to bring about transformative change to their businesses. Half of these high performers intend to use AI to transform their businesses.
Workflow Redesign: Redesigning workflows is a key success factor. High performers are nearly three times as likely as others to report they have fundamentally redesigned individual workflows in their deployment of AI.
Advanced Adoption: High performers are much more likely to report they are scaling their use of AI agents in most business functions. They are also more likely to be scaling or have scaled AI across the business (about three-quarters).
Senior Leadership and Investment: High performers are three times more likely to strongly agree that senior leaders demonstrate ownership and commitment to AI initiatives. They are also investing significantly more, with over one-third committing more than 20 percent of their digital budgets to AI technologies.
Risk Management: High performers are more likely to report negative consequences from AI use, particularly related to intellectual property infringement and regulatory compliance, likely because they deploy AI in mission-critical contexts. They are also more likely to protect against a larger number of risks. A leading practice for high performers is having defined processes to determine how and when model outputs need human validation to ensure accuracy (“Human in the loop”).

5. Workforce Impact and Talent Needs

Varying Expectations: Respondents have differing perspectives on AI’s impact on the overall workforce size in the coming year.
– 43 percent expect no change in the total number of employees.
– 32 percent predict an overall reduction of 3 percent or more.
– 13 percent predict an increase of 3 percent or more.
Hiring: Most respondents—especially those from larger organizations—noted that their organizations hired for AI-related roles over the past year. The most in-demand roles were software engineers and data engineers.

6. Managing AI Risks

Inaccuracy and Explainability: Inaccuracy is the AI-related risk that organizations most often report experiencing negative consequences from (nearly one-third of all respondents) and is a commonly mitigated risk. However, explainability, the second-most commonly reported risk consequence, is not among the most commonly mitigated
Increased Mitigation Efforts: Organizations are addressing more risks; on average, respondents report working to manage four AI-related risks today, up from two in 2022.

Part II: Summary of Key Points and Findings of “The state of AI in GCC countries: In pursuit of scale and value” by McKinsey

GCC countries are rapidly investing in AI infrastructure and positioning themselves as emerging global hubs for AI innovation. Governments and state-linked entities—such as the UAE’s G42, Saudi Arabia’s HUMAIN, and Qatar’s public-sector initiatives—are committing billions to cloud capacity, data centers, and strategic partnerships. This supply-side momentum is strong, yet demand-side adoption across GCC organizations remains uneven.

AI Adoption Is High, but Maturity Is Low

AI adoption in at least one business function increased from 62% (2023) to 84% (2025) among surveyed GCC organizations, nearly matching global averages.
However, only 31% have moved beyond pilots to achieve scaled deployment.
Most organizations are stuck in experimentation, and only 11% qualify as “value realizers” — those able to capture measurable financial impact (5%+ earnings attributed to AI).

Use Cases Expanding Across Functions

AI is most commonly deployed in service operations, marketing & sales, and increasingly product/service development, where end-to-end workflows are being redesigned.
Adoption spans all major sectors: energy and infrastructure lead, followed by financial services, consumer/professional services, TMT, and healthcare/education.

Rise of Agentic AI

60% of organizations report experimenting with or deploying AI agents — a step beyond generative AI.
AI agents automate workflows, make decisions, and show measurable impact on SG&A reduction and cycle-time improvements.

Barriers: Talent, Data, and Change Resistance

Organizations struggle to convert intent into impact due to three core challenges:

1. Talent & Operating Models

AI talent is being hired (data engineers, scientists, software engineers), but operating models are not optimized.
Value creators use centralized AI teams deployed into cross-functional squads; others lag in execution discipline.

2. Technology & Data

Only 37% of non–value realizers report having strong data and technology foundations.
Barriers include poor data quality, lack of scalable architecture, vendor lock-in, and insufficient automated infrastructure.

3. Change Management

Resistance to change is cited as one of the biggest blockers.
Value creators have structured adoption programs, clear KPIs, strong sponsorship, and workflow redesign efforts.

Top Risks Identified

Output inaccuracies, cybersecurity threats, privacy issues, and regulatory compliance are seen as the most significant risks of generative and agentic AI adoption.

What High-Performing GCC Organizations Do Differently

Value realizers outperform peers by excelling in:

Strategic alignment owned by top executives
Centralized talent models with agile pods
Robust tech & data infrastructure
Clear change management and adoption roadmaps

They also apply three practices to accelerate results:

Establishing accountability mechanisms tied to business KPIs
Using AI to build AI, accelerating development and reducing resource needs
Redesigning workflows, not merely automating existing tasks

Overall Insight

The GCC is at a turning point: AI adoption is widespread, leadership enthusiasm is high, and budgets are set to increase for 89% of organizations. Yet the region faces a widening gap between early adopters capturing real value and the majority who remain stuck in pilot mode. To unlock AI’s full economic potential, GCC organizations must strengthen data foundations, modernize operating models, and drive large-scale adoption with structured change management.

Part III: A Deep Dive into AI’s Transformative Impact, Unique Challenges, and Untapped Opportunities in the GCC

The landscape of artificial intelligence is evolving at an unprecedented pace. As outlined in McKinsey’s “The State of AI in 2025: Agents, innovation, and transformation” report, AI is no longer a futuristic concept but a present-day imperative shaping industries worldwide. For businesses within the GCC region, this global transformation presents a unique set of challenges and opportunities. This part leverages the insights from McKinsey’s report to explore how AI is set to redefine the operational and strategic frameworks of GCC businesses, highlighting the specific regional dynamics that will influence its adoption and impact.

AI in the GCC: The Transformative Power of AI in GCC Industries

The McKinsey report underscores that AI’s influence is expanding beyond automation, with intelligent agents and advanced predictive analytics becoming central to business operations. In the GCC, where economic diversification and technological advancement are strategic priorities, AI offers a potent catalyst for growth across various sectors.

Driving Efficiency and Innovation in Core Sectors

Energy and Petrochemicals

The GCC’s foundational energy sector can leverage AI for optimizing upstream and downstream operations, predictive maintenance of critical infrastructure, and enhancing supply chain efficiency. AI agents can analyze vast datasets from sensors to predict equipment failures, optimize drilling operations, and manage complex logistical networks, leading to significant cost reductions and improved output. Furthermore, AI can aid in the transition towards cleaner energy solutions by optimizing renewable energy grids and managing energy consumption more effectively.

Finance and Banking

In the financial sector, AI is already revolutionizing customer service, fraud detection, and personalized financial advice. GCC banks can deploy AI-powered chatbots and virtual assistants to enhance customer experience, utilize machine learning algorithms for more accurate credit scoring and risk assessment, and implement advanced cybersecurity measures. The report’s emphasis on AI agents suggests a future where autonomous financial advisors and portfolio managers become more common, offering tailored solutions to a diverse client base.

Healthcare

AI’s potential in GCC healthcare is immense, from improving diagnostic accuracy to personalizing treatment plans and streamlining administrative tasks. AI-driven platforms can assist in early disease detection, analyze medical images with higher precision, and help researchers accelerate drug discovery. For a region grappling with increasing healthcare demands, AI offers a path to deliver more efficient, accessible, and high-quality medical services.

Tourism and Hospitality

A burgeoning sector in many GCC nations, tourism and hospitality can benefit from AI through personalized guest experiences, dynamic pricing strategies, and optimized resource allocation. AI agents can manage bookings, provide multilingual concierge services, and analyze guest preferences to offer highly customized recommendations, thereby elevating the region’s competitive edge in global tourism.

AI in the GCC: Unique Challenges and Strategic Opportunities for GCC Businesses

While the benefits are clear, the adoption of AI in the GCC is not without its specific set of challenges. However, these challenges often present unique opportunities for those willing to innovate and adapt.

Navigating the Path to AI Integration

Talent Development and Skilling

One of the foremost challenges identified implicitly in the McKinsey report for any region, and particularly salient for the GCC, is the availability of a skilled AI workforce. The rapid evolution of AI demands continuous upskilling and reskilling of the existing workforce, alongside attracting global talent. This presents an opportunity for GCC nations to invest heavily in STEM education, foster AI research centers, and develop robust training programs to cultivate a local pool of AI experts.

Data Governance and Privacy

As AI relies heavily on data, robust data governance frameworks are crucial. GCC businesses must navigate complex data privacy regulations, both local and international, to ensure ethical and secure data handling. This challenge also provides an opportunity to establish global best practices in data ethics and privacy, positioning the region as a trusted hub for AI development.

Infrastructure and Digital Transformation

While many GCC nations boast advanced digital infrastructure, ensuring widespread access and integration of AI-ready infrastructure remains a challenge. Investing in cloud computing, high-performance computing, and 5G networks is vital. This digital transformation journey offers an opportunity to build future-proof infrastructure that can support the next generation of AI applications.

Leveraging Regional Strengths for AI Advancement

Government Support and Visionary Leadership

Many GCC governments have demonstrated strong commitments to technological advancement and economic diversification through national visions (e.g., Saudi Vision 2030, UAE Vision 2071). This top-down support provides a fertile ground for AI adoption, with substantial investments in smart city initiatives, AI strategies, and innovation hubs. This proactive governmental stance is a significant advantage, fostering an environment conducive to AI research and deployment.

Strategic Partnerships and Global Collaboration

The GCC’s strategic geopolitical position and strong international ties facilitate collaborations with leading global AI firms and research institutions. These partnerships can accelerate knowledge transfer, co-development of AI solutions, and access to cutting-edge technologies, enabling GCC businesses to leapfrog stages of AI development.

Best Practices of AI in the GCC

Saudi Arabia: Leading with HUMAIN AI and National Scale

Saudi Arabia has aligned its AI strategy closely with national priorities (Vision 2030) through the Saudi Data & Artificial Intelligence Authority (SDAIA). A best practice is building sovereign infrastructure and partnerships — for example, Humain (backed by Saudi’s Public Investment Fund) has struck a $5B deal with AWS to create an “AI Zone” for high-performance compute and to host locally tailored applications.

This helps the Kingdom retain data sovereignty, scale AI locally, and foster homegrown innovation. Second, Saudi has established a governance and readiness framework to institutionalize AI adoption: SDAIA launched an AI Adoption Framework and an AI Readiness Index to assess maturity in government agencies.
Third, talent development is being aggressively pursued; the “One Million Saudis in AI” (SAMAI) initiative recently exceeded its target, training over 1 million citizens in AI.
Finally, Saudi emphasizes ethical and responsible AI: it recently adopted the OECD AI Recommendation, integrating global standards into national policy.

United Arab Emirates: Ecosystem + Regulation + Talent

The UAE’s approach to AI is highly strategic: it combines strong institutional strategy, talent development, and ethical governance. First, its AI Strategy 2031 lays out eight clear objectives, such as building world-class infrastructure, growing research capacity, and promoting responsible AI.
Second, the UAE invests heavily in human capital: institutions like the Mohamed bin Zayed University of AI (MBZUAI) produce AI-literate graduates, and national programs upskill both students and government officials.
Third, the country blends public service transformation with AI: chatbots serve in government ministries to improve citizen service, and predictive analytics is used for urban planning and public sector decisions.
Fourth, it builds ethical and regulated AI deployment, anchoring development to legislative and governance principles to ensure transparency, safety, and alignment with national values.

Qatar: Strategic Partnerships + Data-Driven Public Services

Qatar is using partnerships and data infrastructure to scale AI in public services. A strong practice is collaborating with global AI firms: for instance, Qatar signed a multi-year agreement with Scale AI to build more than 50 AI applications for government services, including predictive analytics and automation.
This approach helps Qatar leapfrog in data labeling and AI maturity without building everything from scratch. It’s also investing in smart mobility, such as autonomous eVTOL flights, signaling deliberate use of AI to transform urban transport.
Additionally, in its national AI strategy, the government emphasizes ethical data use and regulation, ensuring that AI deployment in public services follows strong data governance and social value frameworks. (This aligns with broader Gulf trends in soft but principled AI governance.)

Oman: Incremental Innovation and Talent Ecosystem

While less publicly visible than its larger neighbors, Oman is making purposeful strides in AI through capacity building and sector focus. One best practice is building talent via national programs, aligning with Oman’s broader Vision 2040 — by investing in tech education and upskilling, Oman seeks to develop a pool of AI practitioners who can drive both public and private sector transformation. (This is supported by regional analyses that highlight Oman’s efforts in workforce development.)
Secondly, Oman is focusing on healthcare innovation: for example, Sultan Qaboos University Hospital is reported to use AI for early warning systems in ICUs, improving patient monitoring and care delivery.
Third, Oman emphasizes governance alignment: its national AI programs reflect a soft but principle-based regulatory approach, consistent with GCC-wide ethical strategies.
Finally, Oman is building infrastructure partnerships (e.g., via cloud and data partnerships) to ensure AI projects are technically feasible even without massive domestic computing capacity, laying the groundwork for scalable future AI deployments.

Future Trends in AI in the GCC

Building on the insights from the McKinsey report, several key trends are expected to shape the future of AI in the GCC.

Emerging AI Paradigms and Their Regional Impact

Autonomous AI Agents

The report emphasizes the rise of AI agents, and this trend will likely see significant traction in the GCC. These agents, capable of independent decision-making and task execution, will transform sectors like logistics, urban management, and customer service. Imagine autonomous AI agents managing smart city infrastructure, optimizing traffic flow, or even personalizing educational content.

Ethical AI and Trustworthiness

As AI becomes more pervasive, the focus on ethical AI development and deployment will intensify. GCC businesses will increasingly prioritize transparency, fairness, and accountability in their AI systems. This will involve developing robust ethical guidelines, explainable AI (XAI) models, and ensuring AI decisions align with societal values and cultural norms.

Localized AI Models and Arabic Language Processing

While global AI models offer broad utility, there will be a growing need for localized AI solutions tailored to the specific cultural context and linguistic nuances of the GCC. Investment in Arabic natural language processing (NLP) will be crucial for enhancing customer interactions, developing effective AI-powered educational tools, and ensuring inclusivity in AI services. Saudi tech company, HUMAIN AI is considered a best practice in this area which has been addressed in this blog post earlier.

AI-Powered Sustainability Initiatives

With a strong emphasis on sustainability and climate action (e.g., net-zero commitments), AI will play a pivotal role in achieving these goals in the GCC. This includes optimizing energy consumption, enhancing waste management systems, developing smart agriculture solutions for water-scarce environments, and supporting renewable energy integration. AI’s ability to analyze complex environmental data and predict outcomes will be indispensable.

Strategic AI Implementation: A Comparative View

To further illustrate the strategic nuances of AI adoption, the following table provides a comparative overview of key areas for GCC businesses, drawing parallels and distinctions based on the McKinsey report’s global insights and regional specificities.

Aspect of AI Adoption	Global Trend (McKinsey Report)	GCC Specificity & Opportunity	Associated Challenge
Investment Focus	Shift from foundational models to advanced agent-based systems and generative AI.	Government-led strategic investments in advanced AI infrastructure and innovation hubs.	Ensuring private sector investment matches public sector initiatives and drives diverse AI applications.
Talent Development	Critical need for AI specialists and upskilling existing workforce.	Emphasis on STEM education, attracting global talent, and establishing regional AI academies.	Brain drain, competition for global talent, and integrating AI skills across all educational levels.
Data Strategy	Focus on data quality, governance, and ethical AI practices.	Opportunity to establish leading standards in data privacy and ethical AI within a unique cultural context.	Harmonizing diverse local and international data protection regulations.
Sectoral Impact	Broad transformation across all industries, particularly in services and knowledge work.	High impact in energy, finance, healthcare, and tourism, leveraging national diversification strategies.	Overcoming legacy systems and fostering cross-sectoral AI adoption beyond traditional areas.
Regulatory Environment	Developing frameworks for AI ethics, safety, and accountability.	Proactive government involvement in setting AI policies and fostering innovation-friendly regulations.	Balancing rapid innovation with comprehensive regulatory oversight without stifling growth.

Frequently Asked Questions (FAQ)

What is the main takeaway from McKinsey’s “State of AI in 2025” report for GCC businesses?

The main takeaway is that AI is rapidly advancing, moving towards intelligent agents and transformative capabilities. For GCC businesses, this means a critical need to strategically invest in AI infrastructure, develop local talent, and adapt global AI trends to their unique regional context to seize significant growth and efficiency opportunities across various sectors.

What are some unique opportunities for AI in the GCC?

Unique opportunities include leveraging strong government support and visionary national strategies for AI development, fostering strategic international partnerships for knowledge transfer, and applying AI to address specific regional challenges like water scarcity (smart agriculture) and promoting sustainability goals. The push for economic diversification also creates fertile ground for AI innovation in emerging sectors like tourism and advanced manufacturing.

What challenges should GCC businesses prepare for when adopting AI?

GCC businesses should prepare for challenges related to talent development and retention, ensuring robust data governance and privacy protocols, and continuously upgrading digital infrastructure to support advanced AI applications. Additionally, integrating AI ethically and ensuring its decisions align with local cultural norms will be crucial.

How will AI agents impact GCC industries?

AI agents, as highlighted in the McKinsey report, will bring a new level of autonomy and efficiency to GCC industries. They can revolutionize logistics, optimize urban management in smart cities, personalize customer experiences in hospitality and finance, and enhance operational efficiency in the energy sector through predictive analytics and autonomous decision-making.

What role will localized AI models play in the GCC?

Localized AI models will be critical for addressing the specific linguistic and cultural nuances of the GCC region. This includes developing advanced Arabic Natural Language Processing (NLP) capabilities to improve customer service, create relevant educational tools, and ensure AI systems are culturally sensitive and inclusive.

Conclusion

The “State of AI in 2025” and “The state of AI in GCC countries: In pursuit of scale and value” reports serve as powerful guides for GCC businesses navigating the rapidly evolving AI landscape. By understanding the global shifts towards intelligent agents and generative AI, and by strategically addressing regional challenges while capitalizing on unique opportunities, the GCC stands at the cusp of a significant AI-driven transformation. The path forward involves sustained investment in technology and human capital, fostering innovation, and embedding ethical considerations at the core of AI development. The region’s proactive approach to digital transformation and strong governmental backing position it to not only adopt but also lead in certain aspects of AI innovation, ultimately fostering sustainable economic growth and societal advancement.

Sources

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McKinsey & Company, QuantumBlack, AI by McKinsey in collaboration with BDI, he state of AI in GCC countries: In pursuit of scale and value

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Telecom Review, Marking AI Appreciation Day: GCC’s Commitment to Innovation

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