Saudi Arabia’s AI maturity is rising. Now comes the real test of value.
Findings from PwC’s AI performance study
As the Kingdom is entering a more decisive phase of AI adoption, organisations are outpacing global peers across several dimensions of AI maturity. The next challenge is not scale, but value: turning AI momentum into stronger returns and lasting competitive advantage.
Executive summary
In the global race to scale artificial intelligence (AI), Saudi Arabia is positioning itself for a step change. Backed by national ambition, large-scale investments and accelerated enterprise adoption, the Kingdom is moving beyond AI readiness into enterprise execution.
Across sectors, AI is becoming embedded in operations, customer experience, risk management and digital infrastructure. The momentum is being reflected in global benchmarks. The Kingdom ranks fifth globally and first in the region for AI sector growth under the 2025 Global AI Index1 and is among the top 10 countries in the 2025 Stanford AI Index, performing strongly across key measures of capability and readiness.2
Survey findings reflect this trajectory. Organisations in the Kingdom are reporting stronger intermediate outcomes from AI than the global average – including gains in organisational agility, customer experience and trust, employee productivity and operating model transformation. However, these gains are not yet being reported as financial returns as consistently as they need to. This does not indicate weak AI progress. Rather, it suggests many organisations are still in the transition from AI adoption to enterprise-wide value realisation.
This becomes clear when we compare organisations in the Kingdom with those that PwC research identifies as ‘AI leaders’3 – global high performers in the top quintile of AI-driven performance.
What differentiates these leading organisations is not the number of AI pilots underway, but their ability to scale high-value use cases, monetise outcomes and embed AI into day-to-day business decision-making. Stronger governance, prioritisation and execution discipline are helping these organisations translate AI investment into sustained revenue growth, efficiency gains and competitive advantage.
While we have organisations in Saudi Arabia as part of the ‘AI leaders’ cohort, the findings point to opportunities for others to strengthen their position by learning from the capabilities and practices that distinguish these leading performers.
The survey explores the areas where organisations in Saudi Arabia score just below these ‘AI leaders’ on the AI Fitness Index, PwC’s measure of an organisation’s ability to generate value from AI. The index assesses both how companies use AI and the foundational capabilities that make AI reliable and scalable, including strategy and governance.
The rankings provide a clear roadmap for further progress, showing where organisations can embed AI more deeply into day-to-day business use, translating their efforts into measurable value.
This report is written for organisation leaders in Saudi Arabia who are now focused on a more fundamental question: How to convert AI activity into measurable business value?
In this context, the survey investigates two critical areas:
- Whether companies in the Kingdom are getting measurable returns from AI
- What lessons can be drawn from ‘AI leaders’ or the ‘high performers’ globally who are in the top quintile of AI-driven performance4
“It is encouraging to see the progress organisations in Saudi Arabia are making in the areas that matter most for AI maturity: clearer strategy, stronger governance and broader use of data. What stands out as well is how closely the public and private sectors are moving together through investment, regulation and capability building. Across adoption, skills development and private investment, the Kingdom is performing strongly against much larger economies, which points to real long-term potential as AI scales across a diverse economy.”
Key findings
% of respondents in Saudi Arabia say their AI vision is aligned to business objectives, compared with % globally.
% indicate they are more likely to have their organisation leaders directly accountable for AI outcomes, compared with % globally.
% have documented Responsible AI frameworks in place, compared with % globally.
% report large or very large improvements in employee productivity from AI, compared with % globally.
% of respondents in Saudi Arabia report strength in attracting technical AI specialists, compared with % globally.
The AI fitness index
The survey examines two key dimensions – AI foundations and AI use – which together form the AI Fitness Index, PwC’s measure of an organisation’s ability to generate value from AI.
* According to PwC research, ‘AI leaders’ are organisations in the top 20% of AI-driven financial performance. This performance is measured through two sector-adjusted indicators: the share of revenue attributable to AI or AI-related initiatives, and the share of cost-efficiency gains attributable to AI or AI-related initiatives. Based on this definition, ‘AI leaders’ account for 235 of the 1,217 global respondents, including organisations from Saudi Arabia.
Section 1 An AI fit nation: from readiness to reinvention
According to PwC research, AI fitness is the combination of two things: the foundations that make AI scalable, and the ways in which AI is applied to create value. On both counts, organisations in Saudi Arabia are moving ahead of the global average. Findings reveal a market that has built much of the practical base required for AI deployment and is now using AI in broader, more strategic ways. The result is not merely higher activity, but a more consequential form of adoption, one that is beginning to influence how organisations operate, compete and grow.
The first measure of AI fitness among organisations in Saudi Arabia is strategic clarity. Organisations in Saudi Arabia are increasingly positioning AI as a core driver of business transformation rather than a standalone technology initiative. They outperform global averages across key measures of strategic alignment (see Figure 2), including AI vision aligned to business objectives (78% vs 65%), leaders directly accountable for AI outcomes (67% vs 54%), systematic tracking of AI’s business impact (53% vs 46%), and having a roadmap for AI initiatives across short- and long-term horizons (64% vs 62%).
This strategic clarity is reinforced at a national level. AI is being embedded into growth agendas, operating-model transformation, and long-term planning, rather than treated as an IT capability. HUMAIN, for example, was launched by Saudi Arabia’s PIF to operate across the full AI value chain.5 A similar positioning is evident across major organisations: stc embeds AI within its innovation and digital expansion agenda6 and Aramco is investing in AI to accelerate industrial transformation.7
What distinguishes organisations in Saudi Arabia is that this clarity of vision is beginning to shape how resources are deployed. Strategy is increasingly acting as a filter for investment decisions, determining where capital is committed, scaled or reallocated.
Investment discipline across the value chain
According to survey findings, Saudi Arabia’s performance on AI investment highlights a more deliberate and structured approach compared with global peers. The Kingdom’s advantage lies not in perceived budget sufficiency, where it remains broadly in line with the global average, but in how investment is allocated, managed, and evolved over time.
Organisations in Saudi Arabia remain broadly in line with their global peers in reporting that their current level of AI investment is sufficient to achieve their AI goals (see Figure 3). However, respondents demonstrate greater flexibility in reallocating financial and human capital towards higher-value AI opportunities (60% vs 55% globally), while also committing a larger share of their revenue to AI than their global peers (8% vs 6%). This investment extends beyond technology alone, covering the full set of capabilities across the value chain required to make AI effective in practice, including internal teams, tools and platforms, governance frameworks and data services.
Operational readiness gains momentum
Relative to the global average, organisations in Saudi Arabia are clearly ahead in the capabilities that make AI usable in day-to-day operations. They are significantly stronger in running scalable cloud-based platforms (see Figure 4) with real-time data availability (76% vs 59% globally), enabling employees to access and use high-quality data (53% vs 38%), and redesigning workflows to integrate AI (51% vs 32% globally).
This strength is reinforced by visible infrastructure momentum, with Google Cloud expanding its Saudi footprint through the Dammam cloud region,8 Microsoft confirming its Saudi Arabia data centre region and Amazon Web Services (AWS) expanding local cloud capability through outposts in the Kingdom.9
A distinctive data advantage
The same pattern extends to data. Organisations in Saudi Arabia exhibit a distinctive data advantage, rooted not in traditional structured data strength but in their ability to mobilise a broader and more diverse set of data types.
Compared with the global average, companies in Saudi Arabia are leveraging richer and more experimental data sources. They are ahead in the use of unstructured data (44% vs 37% globally), proprietary data (60% vs 45% globally), public data (56% vs 37% globally), and particularly synthetic data (53% vs 22% globally), while maintaining parity on structured data (see Figure 5).
In the Kingdom we see a visible progress in expanding data access and data-sharing infrastructure through Saudi Data and Artificial Intelligence Authority (SDAIA)’s Digital Data Marketplace and National Data Catalog,10 while city-scale platforms such as the Royal Commission for Riyadh City (RCRC) Open Data Portal11 to support urban planning show that public data is increasingly being operationalised in machine-readable, usable environments under formal data rules.
Workforce momentum
Organisations in Saudi Arabia demonstrate a broad-based workforce advantage relative to global peers, particularly in areas that enable AI adoption and collaboration. They significantly outperform on attracting technical AI specialists (67% vs 42% globally) (see Figure 6), encouraging experimentation through incentives (56% vs 37% globally), enabling cross-functional collaboration between data, IT, and business teams (56% vs 42% globally), and building trust in AI-generated insights (47% vs 36% globally). They also maintain an advantage in leadership commitment (60% vs 54%) and role-based learning (49% vs 41%).
This momentum is being reinforced by a growing national talent pipeline. SDAIA Academy12 is developing data and AI capability through structured training and bootcamps,13 while Misk14 is helping translate that into practical technical skills through programmes, such as the Samsung Innovation Campus AI Program focused on AI, machine learning, and data processing.
The Kingdom is materially ahead of the global average in realising operational benefits from AI, particularly in employee productivity. 60% of Saudi respondents report large or very large improvements from AI on employee productivity, compared with 46% globally. This suggests that AI is already having a strong practical effect on how work gets done, enabling employees to operate faster, use time more effectively, and improve day-to-day performance.
That outcome is reflected in how organisations are choosing to deploy AI. Compared with global peers, they are less likely to use it for drafting (7% vs 15%) or routine task execution with human approval (11% vs 20%) (see Figure 7). Instead, they are more likely to deploy systems that analyse, predict and recommend (47% vs 36%), or coordinate multiple tasks within structured workflows (29% vs 20%). At the same time, fully autonomous and self-optimising systems remain limited and broadly in line with global levels (7% vs 9%), suggesting that organisations in Saudi Arabia are prioritising controlled, high-impact deployment over full autonomy.
Governance as a strategic differentiator
One of the clearest strengths in AI maturity among organisations in the Kingdom is governance and risk management. Their outperformance over global peers is especially evident in robust security protections (78% vs 60% globally), documented Responsible AI frameworks (62% vs 47% globally), role-based data and AI access controls (64% vs 54%), and formal regulatory engagement and compliance processes (69% vs 60%), alongside a more moderate advantage in the presence of cross-functional governance boards (51% vs 44%).
The strength in Responsible AI frameworks (see Figure 8) is particularly significant. Clear, documented frameworks help turn intent into consistent standards and decision-making rules across the AI lifecycle, from selecting use cases to deployment and ongoing monitoring. This is increasingly being operationalised across a broader governance ecosystem. SDAIA’s AI Adoption Framework and AI Ethics Principles position ‘Responsible AI’ as a cross-sector discipline. In parallel, platforms such as SITE Cloud15 are explicitly designed around sovereign AI, cybersecurity and compliance, while DEEM Cloud’s integration of IBM watsonx.ai and SDAIA’s ALLaM model16 reflects a broader push to enable secure and trusted AI deployment for government entities.
Strong ownership, with scope to accelerate experimentation
Where the picture becomes more nuanced is innovation. Organisations in Saudi Arabia are significantly ahead of the global average in embedding AI innovation ownership within business units (69% vs 46% globally), which suggests that AI is relatively close to operating priorities and business needs (see Figure 9).
There is now the opportunity to strengthen experimentation as AI adoption matures. Respondents in Saudi Arabia are at parity with the global average on providing dedicated infrastructure to support AI experimentation (38% vs 39% globally). The most visible AI announcements in the Kingdom are concentrated around building capability and infrastructure: AI factories, cloud hubs, digital platforms and enterprise AI enablement, rather than around a dense pipeline of publicly visible product iterations, rapid pilot-to-scale cycles, or frequent portfolio resets, suggesting that there is more opportunity for owners to test, iterate and scale ideas at speed.
Findings also suggest that organisations in the Kingdom have a more episodic approach to innovation management. They are likely to review AI initiatives less frequently than the global average, limiting the ability to prioritise and scale successful use cases, while discontinuing weaker ones.
This dynamic helps explain why organisations in Saudi Arabia report a slightly longer time to value from pilots, at seven months compared with six months globally. The issue doesn’t necessarily indicate a lack of pilot activity; in fact, a higher share of respondents in Saudi Arabia say they have participated in AI pilots that delivered value (71% vs 66% globally) and fewer say they have not participated at all (9% vs 15%). Instead, it indicates that organisations in Saudi Arabia appear advanced in deployment readiness but less mature in rapid experimentation-to-scale discipline.
This is consistent with the findings, which suggest that organisations in the Kingdom are placing less emphasis than their global peers on customer- and product-facing innovation (see Figure 10), new product and service development (38% vs 48% globally), updates to existing products and services (36% vs 51% globally), and customer experience innovation (47% vs 60% globally).
What is notable, however, is that although organisations in the Kingdom may not be innovating faster than their global peers, they are creating value where AI is being deployed. Survey respondents were more likely than the global average to report improved customer experience, satisfaction or trust (67% vs 39%) and to have created or enhanced new products and services (49% vs 33%) when they leveraged their organisation’s full AI portfolio.
Organisations in the country are also ahead of their global peers in more transformation-oriented innovation, including business model or revenue stream innovation (44% vs 36%), operating model and process redesign (64% vs 57%), and slightly on ecosystem or cross-sector collaboration (27% vs 25%). AI is, therefore, primarily applied to optimise operations, infrastructure, and systems, from network efficiency at STC17 to industrial and digital transformation at Aramco Digital18, and smartcity platforms such as the Smart Riyadh Operations Center.19
These findings show that organisations in Saudi Arabia have built many of the conditions required for AI to scale: clearer strategy, stronger governance, broader data use, growing workforce momentum, and improving operational readiness. The next question is how those foundations are being used. It is one thing to be prepared for AI deployment; it is another to apply AI in ways that reshape growth, competitiveness, and business models.
“One of Saudi Arabia’s real strengths in AI is the alignment taking shape between national ambition and enterprise strategy. AI is no longer being treated simply as a technology initiative; it is becoming part of how organisations think about growth, transformation and competitiveness. That creates real momentum but sustaining it will depend on disciplined execution and the ability to scale what is working.”
Section 2 Beyond efficiency, using AI in strategic ways
The second dimension of AI fitness is how AI is actually used to create value. Here, the pattern in Saudi Arabia becomes increasingly strategic. Organisations are using AI not only to drive efficiency, but also to influence revenue growth, customer responsiveness, resilience, decision quality and cross-sector collaboration.
While operational efficiency remains the primary entry point, cited by 33% of respondents, AI use in the Kingdom is extending well beyond cost optimisation into areas that shape growth, competitiveness, and resilience (see Figure 11).
Compared with global peers, organisations in Saudi Arabia are more likely to deploy AI to drive revenue growth and market share (18% vs 12% globally), improve customer experience and trust (13% vs 8% globally), support business model transformation (13% vs 9% globally), and strengthen risk and compliance (9% vs 5% globally). This indicates that AI is not being treated solely as a productivity lever, but as a tool to influence how organisations grow, compete, and respond to changing market conditions, laying the groundwork for convergence across sectors.
AI sector for convergence
Organisations in Saudi Arabia are beginning to reflect what PwC’s research, Value in Motion: The Middle East’s time to lead is now, describes as a broader economic shift. Transformative forces, such as AI and climate change, are changing the way we live and work, creating new customer needs and preferences, forging new markets, enabling new business models, attracting new competitors and blurring the boundaries of sectors and industries.
In the Kingdom, businesses are increasingly using AI to enable this convergence across sectors, moving beyond traditional industry boundaries to compete, collaborate, and create value in new ways (see Figure 12). Survey findings indicate that organisations in Saudi Arabia are broadly in line with global peers in using AI from a 'moderate to a large extent' to compete beyond their own sector (51% vs 52% globally). They are also more likely than their global peers to use AI in a similar way to cooperate or collaborate with those outside their sector to a moderate or large extent (62% vs 51% globally).
This points to a more ecosystem-oriented model of AI adoption, one that aligns closely with the ‘domains of growth’,20 where value is created through coordination across industries rather than within them.
PwC economists have estimated that over the next decade, the Middle East’s GDP could reach US$4.57trn by 2035, with traditional sectors reconfiguring into these domains. This is reflected at the enterprise level as well. CEOs in Saudi Arabia are increasingly looking beyond traditional sector boundaries to create value, in line with the Kingdom’s diversification agenda. A notable 63% of CEOs surveyed earlier this year said they had entered new industries in the past five years, up from 47% theprevious year. Looking ahead, in the next three years, 84% of CEOs in the Kingdom anticipate deal value to come from sectors outside their core industry.21
According to the findings of the AI Performance Study, more than half of the respondents in Saudi Arabia indicated they used AI to identify emerging value pools, higher than 38% of their global peers.22
Early signs of reinvention
So, what are the early signs of AI enabling deeper reinvention? The clearest changes are at the operating-model level, where more than half of respondents (53%) report large or very large improvements from AI in how their organisations run, compared with 35% globally – reflecting changes in how work is executed, processes are structured, and decisions are made on a day-to-day basis.
Progress is also evident at the business model level, with 42% of respondents reporting significant improvements from AI, compared with 30% globally. However, the impact remains more pronounced in operations than in how organisations create and capture value. This reflects a typical maturity path: operating model transformation tends to materialise earlier, while business model change takes longer to scale, prove, and translate into sustained commercial outcomes.
Organisations in Saudi Arabia are also ahead of global peers in using AI to reconfigure value chains and business capabilities (38% vs 32%), pointing to a broader shift from isolated use cases towards enterprise-wide transformation (see Figure 13).
Where outward-looking, growth-focused use of AI is concerned, organisations in the Kingdom are ahead of the global average in responding to shifting customer needs (64% vs 46%). In fact, a notable 67% of respondents say that using AI across their organisation has significantly improved customer experience, satisfaction or trust, compared with 39% globally. This suggests that organisations in Saudi Arabia are more effective at using AI to deliver customer-facing outcomes, such as more personalised experiences, faster responses, higher service quality, and stronger customer confidence.
In parallel, respondents indicated they are deploying AI extensively in resilience and risk management, from climate risk modelling (40% vs 25%) to supply chain disruption (53% vs 28%), as well as in core control functions such as cybersecurity (62% vs 47%) and financial risk (47% vs 32%). These patterns indicate that AI is being embedded in areas of strategic importance, shaping both where organisations compete and how they operate.
”AI is becoming a catalyst for reinvention across the Kingdom’s economy. It is helping organisations look beyond incremental improvement and think more broadly about new value creation, new partnerships and new operating models. That matters because the long-term opportunity is significant, especially when adoption is scaled responsibly and tied closely to productivity, trust and business transformation.”
Section 3 Intermediate outcomes are strong, reflecting broader measures of value
As the survey findings indicate, the strongest areas of outperformance are organisational agility, customer experience, employee productivity, operating model transformation, reduced risk, higher decision-making quality, reduced energy use or waste and the creation or enhancement of new products and services.
This suggests organisations are leveraging AI to move beyond experimentation to deliver practical, enterprise-wide effects. Respondents also report faster speed-to-market, stronger decision-making, measured progress in automation, better compliance and risk outcomes, highlighting AI’s role in helping reshape both operating models and business models.
However, two counterweights help explain why these gains are not yet fully translating into financial returns:
First, many of the strongest benefits reported in Saudi Arabia are intermediate outcomes: faster decisions, better customer experience, stronger resilience, greater productivity, and operating-model improvement. These are important sources of future value, but they do not always convert immediately into revenue, margin improvement, or reported ROI.
Second, monetisation discipline may still be catching up with deployment progress. This means that organisations are creating value through AI before they are fully measuring, attributing and capturing it financially.
This is not a question of underinvestment. Organisations in Saudi Arabia allocate a similar share of functional budgets to AI as their global peers (11% vs 12%). But even then, they report a lower approximate return on investment at the functional level for this share of AI spending than the global average (30% vs 37%).
There is an opportunity here about value capture. Many organisations in the Kingdom appear to be realising benefits through stronger adoption, better prioritisation, and more effective embedding of AI into operations, but those gains are not yet translating into financial returns as consistently as they could. The next step is to turn operational progress into measurable economic value by using AI to reconfigure processes, reshape ways of working and open up new revenue streams.
“For organisations in Saudi Arabia, the AI value is no longer theoretical. Many organisations are already seeing tangible benefits in how they operate, how they serve customers and how quickly they can respond to change. It is normal for operational gains to appear before financial metrics fully catch up. The real opportunity now is not just to scale spot improvements. It is to use AI to drive broader business transformation, rethinking how the organisation creates value and delivers outcomes.”
Section 4 Assessing the opportunity to reach the next level of maturity
In this survey, we looked at ‘AI leaders’ globally who are more likely to use AI to accelerate time to market with new products and services, transform their business and operating models, engage in higher-quality and more automated decision-making, and improve customer experience and trust. These are the pathways through which AI compounds: when they improve together, financial performance soars.
While some organisations in Saudi Arabia are already part of the ‘AI leader’ cohort, the findings point to opportunities for others to strengthen their position by looking at the capabilities and practices that distinguish these leading performers (see Figure 14).
Building on the AI Foundations
The same pattern appears in data utilisation. Saudi Arabia is at parity with ‘AI leaders’ on proprietary data, nearly level on unstructured data, and ahead on both public and synthetic data. The main gap is in structured data (47% vs 60%). In effect, Saudi Arabia has built a practical stack for deployment, but not yet the full architecture for repeatable scale.
The findings across these six dimensions make it clear that the Kingdom’s nextphase of AI maturity is unlikely to be defined by building entirely new capabilities. Rather, it will be by making the existing ones work harder, faster and moreconsistently and at scale.
Section 5 Next steps
Section 6 Looking towards 2030
Looking towards 2030, organisations in Saudi Arabia broadly align with a balanced view of AI’s future impact. More than half of respondents believe AI will deliver breakthroughs in science, healthcare and productivity, but that the gains may be unevenly distributed, with some economies and communities advancing while others face job displacement and widening inequality. Regulation and cooperation are expected to evolve, but not always evenly, leaving progress accompanied by new risks.
At the same time, nearly a third of respondents (31%) align with a more optimistic view: one in which AI is responsibly scaled across industries, unlocking unprecedented productivity, accelerating scientific discovery and helping to narrow inequality.
This points to a market that is confident in AI’s upside, but clear-eyed about its risks. As the World Economic Forum has noted,23 AI’s future isn’t straightforward. It promises transformation, yet its future is unlikely to follow a single path. Its impact will be defined by a series of tensions, between speed and safety, scale and inclusion, innovation and control. For organisations in Saudi Arabia, the road ahead is to scale AI in ways that are commercially effective, operationally resilient and socially responsible.
Saudi Arabia’s AI maturity is rising. Now comes the real test of value.
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