Breaking barriers: Maximizing Saudi Arabia's gen AI investment

Inhibitors and accelerators: The forces driving AI momentum

To dig deeper into these mechanics, we’ll now examine how business leaders rate inhibitors and accelerators within their region. By doing so, our study provides a detailed temperature check that leaders can use to take advantage of what’s working well in their local environment, while strategizing on overcoming challenges.

A look at Saudi Arabia’s gen AI accelerators

Respondents were asked which factors inhibit or accelerate their organization's adoption of generative AI. Score represents a percentage point difference to the country's momentum score compared to the global baseline.

Base: 50 senior business leaders in Saudi Arabia
Source: Cognizant and Oxford Economics
Figure 2

A key reason for Saudi Arabia businesses’ higher-than-average momentum is the flexibility of their operating models. The country has been initiating efforts to improve its use of AI and data as far back as 2020, and is now home to several AI startups. And since the establishment of the Saudi Data and Artificial Intelligence Authority (SDAIA), which serves as the national authority for data and AI, Saudi businesses have had the support of a centralized hub for AI’s organization, development and implementation, promoting the adoption of AI solutions across several industries.

Indeed, the SDAIA’s efforts are being recognized; Stanford University AI Index for 2024 ranked Saudi Arabia among the leading nations globally for developing a national strategy on AI, putting the region in a prime position to embrace generative AI.

Saudi businesses are also positive about their data readiness, but it seems there is work to be done here. In keeping with a global trend that emerges across our research, businesses in Saudi Arabia know they have significant quantities of data waiting to be better leveraged—but aren’t confident they can yet do so in an operational setting.

Consider that 42% of businesses rate their data security as needing improvement, alongside 32% that believe their data accessibility needs improvement. In line with this, Saudi Arabian authorities have initiated programs to streamline the kingdom’s data protection laws with European AI data safety regulations after recognizing the need to preserve data security.

Optimism about the quality of output is also pushing gen AI adoption forward, as evidenced by the increasing number of companies willing to insert generative AI-driven capabilities into their customer-facing offerings. For example, Al Rajhi Bank, a leading Islamic bank in Saudi Arabia, integrated an AI-powered chatbot named "Rajhi" that leverages natural language processing to understand customer inquiries and assist with tasks.

The availability of compute power in the region is also viewed as a boon to adoption. In recent years, government initiatives and investment, combined with growing recognition of big data and the Internet of Things, have fueled growth of Saudi Arabia’s data center sector. One report named Saudi Arabia the fastest-growing data center market in the Middle East, with live IT capacity rising 29.7% to 109MW during 2023 alone.

The bottom line: Saudi businesses have access to the infrastructure needed to embrace generative AI.

Understanding Saudi Arabia’s gen AI inhibitors

Respondents were asked which factors inhibit or accelerate their organization's adoption of generative AI. Score represents a percentage point difference to the country's momentum score compared to the global baseline.

Base: 50 senior business leaders in Saudi Arabia
Source: Cognizant and Oxford Economics
Figure 3

The cost and availability of talent is the greatest inhibitor to adoption in Saudi Arabia. With many of Vision 2030’s objectives directly or indirectly linked to AI, the kingdom’s shortage of people actually skilled in the technology is inevitably hindering progress.

How to address the skills gap? In our research, 42% of Saudi businesses believe direct funding to retrain and reskill employees would be the best approach. Outside of the workforce, the Saudi government is also ensuring that the next generation of AI talent is geared up for the future, with 86% of universities offering bachelor’s degree programs related to AI, and 42% offering specialized AI-focused programs.

Businesses in the region are also concerned about the maturity of generative AI-related technologies, which is further slowing adoption. This becomes clear when we take a closer look at how Saudi businesses are using the technology today. Many appear cautious about fully integrating the tech into their operations; even while 30% of businesses have deployed generative AI to produce customer-facing communications, only 18% have used the technology to engage directly with customers and consumers, and only 8% to automate existing processes.

Consumer perceptions also raise concerns. According to recent research, while employees across Saudi Arabia recognize the benefits AI can bring—for example, freeing them from physically demanding or dangerous jobs (52%)—nearly half (48%) fear losing their jobs to artificial intelligence. Nonetheless, 51% believe robotization opened opportunities for employees to retrain for more interesting and higher paid jobs, making it critical for businesses to play a key role in facilitating this transition to ensure employees can thrive in an AI-driven workplace.

Many businesses are also concerned that their existing technology stacks will obstruct adoption plans, requiring investment in modernizing applications and infrastructure to fully capitalize on the tech's potential. Data security is a critical factor here, often seen as a major barrier to adoption. 54% of executives in the region say their data security needs improvement or is currently nonexistent.

Specifically, numerous companies are reluctant to adopt generative AI due to data privacy issues—62% say this needs improvement or is nonexistent in their company.

Sector spotlight: Stark differences in industries’ gen AI adoption priorities

Of course, there are many use cases and strategies for using generative AI. As we’ve said, Saudi businesses are slightly more focused on realizing innovation gains (46%) with generative AI than productivity gains (44%). However, a look at what’s driving their business cases sheds new light on what these businesses are trying to achieve with generative AI.

The metrics Saudi businesses say will be most important for justifying generative AI expenditures include increasing revenues and discovering new revenue sources, both of which were named by at least 47% of respondents and both of which align with innovation. At the same time, nearly half (49%) of respondents named cost savings as a top metric, which is traditionally more aligned with productivity (see Figure 4).

The distinction between productivity and innovation seems more blurred with generative AI. Traditionally, businesses have equated productivity gains with cost-cutting: driving down the cost of output by reducing the number of people needed to get work done. While generative AI-driven automation will likely lower headcount to some degree, that is no longer the only end goal. Instead, our data points to a shift toward redirecting the savings gained through productivity to funding endeavors focused on growth.

Increasing revenue and driving down cost fuel gen AI business case justification

Q: Which of the following metrics are most important in terms of justifying your organization’s generative AI business cases? (Percent of respondents naming each as a top-three choice)

Base: 50 senior business leaders in Saudi Arabia
Source: Cognizant and Oxford Economics
Figure 4

Using this more granular view of productivity goals and business drivers, we analyzed the differences in how industries intend to use the technology. Rather than focusing on the distinction between productivity vs. innovation, we grouped the metrics into two high-level categories of business use cases:

• Enhancing current business performance (revenue, cost savings, time-to-market, productivity)
• Building something new (new revenue sources, new or improved products, innovation)

We then assigned each of the metrics a score to see the relative gap between a number-one-ranking metric and a number-three-ranking metric. By calculating the average score across industries, we could clearly see how each industry’s responses deviated from the baseline.

Our analysis reveals stark differences among Saudi industries in terms of the business use cases they’ll likely prioritize (see Figure 5).

Industries diverge on business cases

Note: This figure depicts each industry’s relative deviation from a baseline of “zero,” using a ranked scoring of the top three metrics they cite as important for justifying their generative AI use cases. It reveals a weighted view of each industry’s overall priorities for gen AI deployment.

Base: 50 senior business leaders in Saudi Arabia
Source: Cognizant and Oxford Economics
Figure 5

• The healthcare sector in Saudi Arabia is leaning heavily into enhancing current organizational performance. For example, startup SDM has worked on filling existing gaps in the Saudi health sector to increase efficiency and accessibility to healthcare services in remote communities across the kingdom.
   
  SDM leverages AI technology to carry out comprehensive mass detection of chronic diseases through retinal imaging analysis of the eye. Because this approach does not require physicians to be onsite, it enables health providers to reach tens of thousands of previously unreachable patients.
  
  Similarly, MiniGPT-Med—a generative AI model focused on improving the accuracy of medical diagnostics—could make Saudi Arabia a global AI leader in the healthcare sector. By merging image analysis with clinical data, it enhances diagnostic accuracy and speed for early disease detection. This model analyzes large data sets, spotting patterns humans might miss, thus improving patient outcomes and reducing costs. Offering accurate, quick results helps healthcare professionals, especially in under-resourced regions, ensure quality care access. These advancements align with Saudi Vision 2030, highlighting the kingdom's tech progress and leadership in AI healthcare.
  
  
• Transportation companies are also indexing toward enhancing what they have. Saudi startup Riyadh Air recently announced plans to use generative AI to enhance its digital booking experience. The idea is to allow customers to plan their entire trip through the carrier’s digital platforms, integrating travel and hospitality brands.
  
  
• The resources sector, meanwhile, is far more likely to be focused on building something new with generative AI. State-owned oil and gas company Saudi Aramco, for instance, has unveiled its first generative AI model, Aramco Metabrain AI. The model, boasting 250 billion parameters and trained on seven trillion data points, aims to analyze drilling plans, geological data, historic drilling time and costs, as well as recommend the best well options. With this information, the tool will also provide precise forecasts for refined products, including pricing trends, market dynamics and geopolitical insights.
  
  
• Similarly, the public sector is also focused on advancing new capabilities in its gen AI adoption. A recently announced partnership between IBM and the SDAIA aims to develop the kingdom’s gen AI capabilities. The SDAIA announced that its Arabic language AI model, ALLaM, will be trained on IBM’s platform to run more efficiently and to add new language skills to IBM’s offerings, including the ability to understand multiple dialects of Arabic.

Business constraints to gen AI adoption: Talent shortages and shaky tech foundations

A remaining question is whether businesses are ready to drive real value from these business cases.

The answer, according to our research, is mixed. To better understand how prepared executives believe their business is to adopt generative AI, we asked them to rate their organization’s maturity on a scale of 1 to 4 by selecting a statement that best described their organization in the following five areas, from low maturity to high:

• Organizational agility
• Leadership commitment
• Skills and talent
• Strategy and approach
• Technology and infrastructure

The message from business leaders in Saudi Arabia is evident: Leadership commitment is high, and strategies are robust. However, the fundamental operational and technological building blocks necessary to adopt the technology are lacking (see Figure 6).

Leadership support is sound, but fundamentals are lacking

Respondents were asked to rate the maturity of their organization's operations in relation to generative AI. (Percent of respondents rating each as a 3 or 4, with 4 representing the highest level of maturity.)

Base: 50 senior business leaders in Saudi Arabia
Source: Cognizant and Oxford Economics
Figure 6

Unsurprisingly, given that talent shortages sit high on the list of the biggest inhibitors impacting the region, respondents assign low ratings to the maturity of their business’s skills availability and talent strategy. Ranking even lower than this is confidence in their technology and infrastructure.

While Saudi businesses rate their data quality and cloud compute power highly (46% and 42% rate these areas as good or excellent, respectively), other foundational aspects score lower, including compliance with company policies and customer privacy, data security and regulatory compliance.

Without seamless accessibility, generative AI algorithms may encounter limitations in extracting valuable information, resulting in inaccurate or incomplete outputs. Nonetheless, progress against this seems to be in motion with Saudi Arabia’s recent Personal Data Protection Law, now enforceable by the SDAIA, which aims to take control on crucial aspects of data protection.

Path to success: Strategic recommendations for Saudi Arabian businesses

Saudi Arabia has much to offer when it comes to generative AI momentum. But businesses here must apply focused attention to take full advantage of the kingdom’s accelerators and overcome its inhibitors.

To navigate the road ahead, executives should prioritize the following actions:

• Address local talent shortages: While Saudi Arabia’s ambitions and investments toward the adoption of generative AI are overwhelmingly positive, a shortage of local talent is significantly impacting progress. Bridging this gap and fostering public trust in generative AI will be vital in defining Saudi Arabia’s position as a global AI powerhouse.
  
  In addition to focusing on attracting international talent, businesses need to begin investing in robust talent development programs, including in-house training, university partnerships and mentorship initiatives, to ensure local talent doesn’t fall behind.
  
  Businesses in the region can adopt further strategies such as forging stronger connections with academia, the public sector and startups. For instance, they could set up AI research labs in partnership with universities and private entities, akin to the STC Group AI Lab. Additionally, businesses can drive innovation forward by creating interdisciplinary working groups that include various stakeholders and experts, collaborating with universities to develop relevant academic programs and providing research grants to support university projects.
  
  
• Forge public-private partnerships: The Saudi government has made its stance on AI clear. With multi-billion-dollar investments dedicated to AI R&D projects, businesses have plenty of opportunities to collaborate across these initiatives to expedite their deployment of generative AI solutions.
  
  Crucially, Saudi Arabia aims to position itself as a global hub for AI through its National Strategy for Data & AI, attracting significant investments in AI research and development. Generative AI technology is being implemented across various sectors such as healthcare, enhancing diagnostics and personalized medicine; education, creating personalized learning experiences; and energy, optimizing production and consumption through predictive maintenance and smart grid technologies.
  
  To support AI startups and businesses, the creation of industrial groups akin to Germany's IHK (Industrie- und Handelskammer) is proposed, along with fostering public-private partnerships for AI adoption in various industries. It will be crucial to strengthen the SDAIA to guide and oversee AI initiatives, as well as developing a robust regulatory framework similar to the NIST framework to ensure the ethical and responsible use of AI.
  
  
• Enhance data security and compliance: Despite hailing from a region recognized as one of the most technologically advanced economies on the planet, Saudi businesses recognize there is more work to do. Using our data to pinpoint an area to focus on, it’s clear that developing a strong data security, compliance and core infrastructure footing will help businesses leverage their data quality.
  
  To address this, businesses should invest in robust data security measures and ensure compliance with relevant regulations to build trust and facilitate the adoption of generative AI.

*The full list of regional factors we evaluated includes: the flexibility of the existing operating model, market demand for gen AI-enabled products and services, data readiness, quality of output from gen AI, availability of compute power, cost/availability of gen AI-related technologies, shareholder/investor sentiment, regulatory environment, sustainability, national infrastructure, cost/availability of capital, data privacy and security, existing technology infrastructure, current and prospective employee perceptions, flexibility of the existing business model, maturity of gen AI-related technologies, consumer perceptions and cost/availability of talent.

Learn about the impact of generative AI on jobs and the economy in our report New work, new world.