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The increasingly heated generative AI (GenAI) race has sparked excitement and investment in a technology that has the potential to change the world profoundly. We expect to see widespread adoption of this technology across the corporate world over the next 6 to 12 months, along with rapid progress in the field.
Although these sudden advances come with serious regulatory concerns – among them the threat of deepfakes, harmful content, and exacerbated economic inequality and bias – the technology’s potential economic impact remains substantial.
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Executive summary
Accurate predictions are difficult at this early stage, but our conservative top-down estimate predicts that by 2030, the GCC region could realize approximately $9.9 of economic growth for every $1 invested in GenAI. At that rate, the overall economic impact of GenAI could reach $23.5 billion per year by 2030 in the GCC area. These estimates, along with our calculations of the likely impact on each country and industry are based on PwC’s “Global Artificial Intelligence Study,” and they account for the market size and forecast impact of GenAI, the forecast GDP growth of GCC countries, the adoption rates of AI in GCC economies, and the differentiated impact of GenAI on particular industries.
GenAI-fueled improvements in efficiency and effectiveness will likely have the greatest effect in Saudi Arabia and the UAE, with annual impact of $12.2 billion and $5.3 billion, respectively. Other countries in the region will also benefit, with Qatar gaining $2.6 billion, Kuwait $1.6 billion, Oman $1.3 billion, and Bahrain $0.6 billion. The largest affected industry is likely to be media and entertainment, with $8.5 billion of likely economic impact across the GCC region, followed by banking and financial services at $3.5 billion, healthcare at $3.8 billion, with IT and telecommunications at $2.9 billion.
Given this expected impact and the accelerating pace of new GenAI advances, executives in the Middle East should seize the opportunity without delay. Companies that merely watch risk falling behind, while their forward-thinking counterparts that adopt GenAI stand on the verge of gaining a significant competitive edge.
GenAI is more than an advanced chatbot. These large language models (LLMs) trained on extensive textual and, of late, multimodal data, perform a multitude of linguistic tasks, including generation, editing, summarizing, translation, and classification. The ability of LLMs to be fine-tuned for specific applications represents a compelling advantage. For example, Google’s recently launched Med-PaLM2, a healthcare-centric model, exemplifies this, outperforming medical professionals in crafting some comprehensive clinical evaluations. More broadly, GenAI is poised to trigger a seismic shift in business, impacting functions from sales and marketing to customer service and compliance.
However, the power of GenAI models comes with limitations. Currently, these models are not yet a suitable tool for intricate numerical analysis or critical decision-making processes. Additionally, there are potential ethical challenges, with risks of bias, unethical usage, and significant computational costs. Mismanagement could lead to the generation of misleading or harmful outputs.
Hence, strategic deployment of GenAI is crucial for maximum impact.
- 1Executives should choose GenAI use-cases that align with their strategic goals and provide tangible value. Achieving early, if small, wins can rally support, so it is wise to avoid costly and risky “big bang” approaches. Concentrate on a handful of key use cases, take into account organizational maturity, data availability, and the regulatory environment.
- 2On organizational maturity, CEOs must collaborate with their chief data, information, and technology officers to swiftly tackle any deficiencies in data capabilities, especially those linked to data governance, such as quality, availability, and completeness. This extends to the data tech stack – notably, adopting cloud-native capabilities – to exploit the predominantly cloud-based innovative GenAI models.
- 3Talent is also key to success in the GenAI world, which is a challenge in the Middle East because of local shortages of advanced data science skills. The race for this talent is global, so building strong strategic partnerships will be vital for GCC companies that want quickly to deploy experienced talent and capabilities, while attracting and retaining top in-house data science talent.
GenAI is not just another tech buzzword – it is a revolution set to redefine the business landscape. Grasping GenAI’s capabilities can catapult organizations ahead, giving early adopters a formidable competitive advantage. Adopting GenAI and building the required underlying capabilities is not a quick or cheap fix. It calls for sustained and long-term investments to drive an enterprise-wide transformation. The race is on, and the prize – a share of a multibillion-dollar market impact in the Middle East – is too significant to be ignored.
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