United Arab Emirates: Paving the way to become a global generative AI hub

Against this backdrop, businesses in the UAE believe generative AI is critical to their future success, according to our research. Buoyed by their conviction, they plan to spend over $47.3 million on this powerful technology this year alone, a little over the global average of $47 million.

But in spite of positive intentions and above-average spend, UAE businesses appear somewhat concerned about their ability to execute on their generative AI strategies, with 76% of businesses in the region believing they aren’t moving fast enough in their adoption journey. Forty-four percent believe adoption delays could hand the advantage over to their competitors, while 50% believe it will limit their personal productivity.

To better understand what generative AI adoption will look like globally, we conducted a study of 2,200 business leaders in 23 countries and 15 industries, including 50 in UAE. The study assessed a wide range of generative AI adoption trends, including investment levels, use cases, how critical gen AI strategies are to business success and organizational readiness to adopt the technology.

We also analyzed 18 regional and internal business factors that will either inhibit or accelerate business adoption of gen AI (see the end of the report for the full list of factors). Respondents evaluated each factor’s potential impact on their generative AI strategy, rating it as either positive or negative on a scale of high to low impact.

As for where UAE businesses’ generative AI investments will be aimed in the near term, we looked at two distinct uses of the technology: productivity, such as helping people work more quickly and get more done, and disrupt-the-business innovation, which involves more sweeping change to business and operating models (see Figure 1).

UAE bucks the global trend in several areas. Foremost, businesses in the region are much less likely to focus their efforts on business innovation. They are also slightly below the global average in emphasizing business productivity as core to their strategy. In contrast, redesigning operating models sits slightly higher on the agenda than the global average.

However, our study also reveals a change in what productivity means when pursued with generative AI. The end goal is not efficiency and cost-cutting as has been the case with previous automation endeavors. This new dynamic requires fresh thinking around understanding business use cases of generative AI, which we’ll address later in this report.

Greater focus on productivity than innovation

Q: Which of the following best describes the role generative AI will play in your organization's business strategy in the next two years? (Percent of respondents naming each as a top-3 choice)

Base: 50 senior business leaders in UAE
Source: Cognizant and Oxford Economics
Figure 1

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 UAE 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 UAE
Source: Cognizant and Oxford Economics
Figure 2

Businesses in the region are bullish about the flexibility of their operating model, and are continuing to experiment in this area. Perhaps the most compelling example is the ongoing pivot to hybrid and flexible working practices. As a result of successful change in this area, regional executives also believe they can adapt their processes to get the most out of generative AI.

They are equally optimistic about the readiness of their data to power the technology, naming this as the second highest accelerator for adoption. At the same time, they seem far less sure about the readiness of their overall technological infrastructure.

In effect, businesses recognize they have huge swathes of valuable data dotted around their business but are less sure about their technological capabilities to enable generative AI to use it. Digging deeper into the data, we see the nuances of this challenge laid bare. Leaders are more likely to rate the quality and cleanliness of their data as good or excellent (42% of respondents sit in this category). However, only 20% of respondents have a similarly positive view of the accessibility of their data. The risk is that any momentum gained through high data readiness will be stalled by challenges with legacy technology.

Another accelerator for gen AI adoption among UAE businesses is their assessment of market demand for the tech (albeit viewed as less of an accelerator than the global average). Businesses in the region recognize that the market has spoken, making it essential to embed the technology in their operations and offerings.

Businesses also feel positive about the availability of compute power in the region. Cloud infrastructure continues to grow as more businesses migrate to the cloud, and the UAE boasts one of the world’s most powerful high-performance computers, giving businesses reassurance that their AI workloads have ample support.

Finally, the region is something of an outlier in its recognition of shareholder and investor sentiment as an accelerator (most countries highlight it as an inhibitor). Alongside the government’s commitment to investment in the space, retail investors in the region are also ramping up spending on AI, pushing businesses to scale up initiatives to win over backers.

Understanding UAE 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 UAE
Source: Cognizant and Oxford Economics
Figure 3

As with many of the countries analyzed, the cost and availability of talent is the greatest inhibitor to adoption in UAE. This isn’t new for the region; for a long time, a shallow talent pool has threatened to hamper UAE’s plans to become an AI superpower.

The government is working to overcome this by introducing a series of measures ranging from overhauled visa rules to the establishment of the Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi in 2019—moves that continue to drive momentum in deepening the country’s AI talent pool.

Also inhibiting generative AI adoption is the perceived maturity of generative AI solutions. While executives seem bullish about the capabilities of available solutions, they are looking for a wider and deeper array of generative AI tools to unlock the next level of value and tackle more complex business challenges. Digging into the data, the areas UAE businesses are most eagerly experimenting with are writing and testing software code, adding new revenue sources, generating customer-facing communication and engaging directly with customers.

UAE businesses also flag concerns with current and prospective employee perceptions of generative AI. Even before the advent of gen AI hype, workers in UAE perceived AI as a threat to their jobs.

Leaders are similarly concerned about consumer perceptions—and with good reason. Research suggests consumers in UAE are concerned about companies using AI ethicially, and say it’s important to know whether they’re communicating with AI or a human—underscoring the importance of careful and thoughtful deployment.

Finally, despite viewing shareholder and investor sentiment as in place, leaders believe it will come at a price—and that the cost and relative availability of capital may slow adoption.

Sector spotlight: Stark differences in industries’ gen AI priorities

Of course, there are many use cases and strategies for using generative AI. As we’ve said, UAE businesses are primarily focused on realizing productivity gains with generative AI, at least in the next two years. However, a look at what’s driving their business cases sheds a new light on productivity from how it’s been seen historically.

Traditionally, businesses have equated automation 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 end goal. Instead, as seen through the metrics respondents will use to drive business cases, we see a shift toward redirecting productivity gains into funding endeavors that increase revenues or lead to entirely new revenue streams.

The metrics UAE respondents say will be most important for justifying generative AI expenditures include increasing revenues, discovering new revenue sources and creating new products and services, all of which were named by at least 46% of respondents (see Figure 4). Conversely, metrics like cost savings and time-to-market were cited by 36% and 10% of respondents, respectively. In other words, the concept of productivity no longer stops at cost-cutting—businesses appear to be redirecting productivity gains into initiatives aimed at growth.

Revenue is a top metric for justifying gen AI use cases

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 UAE
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 UAE 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 UAE
Source: Cognizant and Oxford Economics
Figure 5

The resources sector in UAE is more likely to swing toward enhancing its current business performance. For example, the Abu Dhabi National Oil Company used AI to generate $500 million of additional value through 2023—with a focus on initiatives that generate greater automation, optimization of processes and improved efficiency.

The communication, media and technology sectors are similarly focused on using gen AI to enhance existing offerings. UAE telco e&, for example, is embedding generative AI to improve the customer experience and optimize internal operations, including HR, to enhance overall performance and enable faster decision-making.

The banking sector is more balanced, with businesses both enhancing what they have and building something new. UAE’s largest bank, Emirates NBD, is working on a range of use cases to foster innovation and boost customer service—while also driving up worker productivity. For example, the firm uses Microsoft Copilot to automate repetitive tasks, generate content and assist employees with complex decision-making.

Similarly, First Abu Dhabi Bank recently announced a partnership with Microsoft to enhance its products and back-end operations. The bank is exploring banking-as-a-service (BaaS) and risk-as-a-service (RaaS) as collaboration areas, and is considering using the technology to automate lending, payment and digital processes across its retail, corporate and investment banking functions.

UAE’s transportation sector is similarly more inclined to use generative AI to create new offerings. Etihad Airways, for example, is working to enable customer bookings using the tech. Customers will be able to book flights just by typing in the basic details of the service they require, with a gen AI-enabled app doing the rest. Similarly, as early as October 2023, global airline Emirates was examining the use of gen AI to enhance the customer experience and training for cabin crew.

In the retail and consumer goods space, grocery delivery company talabat is enhancing the customer experience by leveraging OpenAI’s ChatGPT to support customers in their search for recipes, identifying ingredients needed as they plot out their meal. The innovative app will also provide cooking instructions, nutritional information and complementary dishes.

Meanwhile in the entertainment sector, Miral is using gen AI to build customer-facing services that offer guidance and information to visitors of the company’s theme parks and experiences. The goal is to provide consumers with a personalized and seamless experience that helps them plan their day and navigate various locations.

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 UAE 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 UAE
Source: Cognizant and Oxford Economics
Figure 6

Examining where the biggest challenges are, it’s perhaps unsurprising that businesses in the region believe the availability of skills and talent are cause for concern—given that talent also ranks as a major inhibitor to gen AI implementation.

UAE is also one of the most pessimistic regions when assessing its technology and infrastructure. Only 14% of businesses rank their tech estate in the top two levels of maturity, compared to a global average of 32%.

Path to success: Strategic recommendations for UAE businesses

The UAE government has a clear vision for becoming a hotbed of AI innovation—stemming from years of investment in education, infrastructure and economic development. But businesses here must apply focused attention to take full advantage of the country’s accelerators and overcome its inhibitors.

Based on our analysis, executives should prioritize the following actions:

1. Invest in talent: Businesses in the UAE have grappled with talent challenges for some time. The government is aware of this; in a recent interview, the UAE’s minister of state for AI said that unlike other regions that have a huge legacy workforce, Dubai has had to build up its talent pool from scratch, noting that the government plans to invest $6.5 billion to upskill young Emiratis.
   
   Businesses have a crucial role to play in this journey. With all regions pulling from a shallow global pool of AI expertise, relaxing visa rules and upbidding for talent may prove to be costly, short-term thinking. (Consider that software engineers in Dubai can earn up to 30% more than peers in London and Amsterdam.)
   
   Instead, businesses should work to plug talent gaps by blending hiring with reskilling and upskilling. Encouragingly, 62% of UAE businesses plan to upskill employees in specific roles to develop gen AI skills in their workforce, while 40% plan to focus efforts on hiring specialized talent.
   
   
2. Forge public-private partnerships: The UAE government has been proactive in promoting AI through various initiatives, such as the UAE Artificial Intelligence Strategy 2031. This provides ample opportunity for businesses in the region to uplevel their adoption efforts by participating in government-led AI initiatives and pilot projects. This includes collaborating with entities like the UAE Ministry of AI and taking advantage of regulatory sandboxes that allow for the testing of AI applications in a controlled environment.
   
   There are also opportunities to develop partnerships with public-sector organizations to co-develop AI solutions. For example, collaborating with Smart Dubai or the Dubai Future Foundation can give UAE businesses access to unique datasets and advanced AI infrastructure. And much like supporting the central talent strategy, businesses should work to actively participate in the development of AI policies and regulations by providing feedback and sharing insights. This ensures that the regulatory framework evolves in a way that supports innovation while mitigating risks.
   
   
3. Embed data governance and ethical frameworks into the business: Finally, two of the greatest inhibitors to gen AI adoption today center on the perceptions of both consumers and employees. As AI becomes more integrated into business operations, ethical considerations and data governance will become increasingly important. Without a strong ethical framework and robust data governance practices, businesses risk losing consumer trust and facing regulatory penalties.
   
   UAE businesses are concerned about their existing infrastructure’s capability to support compliant use of generative AI. Just 14% rate their ability to comply with company rules, policies and frameworks as “good” or “excellent.” And only 8% have an established governance model with ethics considerations in place. This highlights the need to invest in data governance and ethical frameworks as adoption in the region ramps up.

*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.