PricewaterhouseCoopers estimates that AI could contribute $15.7 trillion to the global economy by 2030, with $6.6 trillion likely to stem from increased productivity.
The Middle East is anticipated to account for 2 percent, or $330 billion, of the total global benefits of AI in 2030.
However, to achieve this potential, specific areas of AI must thrive. Economy Middle East delves into this and more in this interview with Renen Hallak, founder and CEO of VAST Data, an AI data platform company.
How can regional businesses and governments prepare for the AI era?
The Middle East is one of the fastest-growing regions in the world for AI adoption, with companies like G42, who recently announced their partnership with VAST Data, leading the charge. As regional enterprises focus more on AI applications, what is required is a streamlined data platform that simplifies data management and processing, provides fast file access and GPU-optimized performance for neural network training, and offers a global namespace spanning hybrid multi-cloud and edge environments to enable federated deep learning.
While generative AI and Large Language Models (LLMs) have introduced the world to AI, they are limited to performing routine tasks. The true promise of AI will be realized when machines can replicate the process of discovering new ideas, achieving in a matter of days a level of specialization that previously took decades.
By taking advantage of a true, AI-automated discovery platform, organizations can leverage their proprietary data sets to deliver immense value to their customers and, in turn, differentiate their businesses.
What steps should organizations take to adapt and embrace AI-driven advancements?
Enterprises require streamlined and consolidated solutions that offer the requisite usability and reliability, seamlessly integrating evolving AI functions to meet contemporary data storage and computational processing demands.
Organizations should consider these key steps:
- First, defining clear objectives by identifying specific business problems AI can address and establishing Key Performance Indicators (KPIs) is crucial.
- Second, ensuring data readiness is essential. Data should be well-prepared, clean, and easily accessible, as high-quality data is vital for successful AI implementation. Investing in AI talent or providing training for existing employees is also important.
- Lastly, continuous evaluation of the ROI of AI initiatives is necessary to justify further investment and ensure that AI efforts yield the desired results.
How can we build a data platform to withstand the needs of today’s LLMs and take advantage of Gen AI applications?
To take advantage of generative AI applications, organizations must establish straightforward and cost-effective ways to store and retrieve large amounts of data. Current data platforms have significantly simplified the deployment of infrastructure for business intelligence and reporting applications. However, they are not designed for deep learning applications.
The true potential of AI can be realized when machines can capture, synthesize, and learn from data to achieve a level of specialization in a matter of days rather than decades.
The next step in this journey is to use a data computing platform designed for AI-assisted discovery. To achieve optimal AI-driven deep learning, it’s essential to have direct access to data from the natural world, the ability to store vast amounts of structured and unstructured data in an easily accessible manner, the intelligence to transform unstructured raw data into an understanding of its underlying characteristics, and a mechanism to build on an organization’s global knowledge, query it and generate a better understanding of it.
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How can we democratize AI and make its capabilities more accessible to businesses of all sizes?
There are a few considerations:
- First, consolidating the necessary infrastructure for AI implementations into a unified data system instead of several disparate systems. This allows data scientists to easily access insights from a massive dataset with AI tools and platforms that do not require extensive technical expertise. This, in turn, enables organizations to effectively differentiate their business.
- Second, providing cost-effective, cloud-based AI solutions that allow businesses to access AI resources on a pay-as-you-go basis, and to start with a “right-sized” system that can seamlessly grow as needed, making it more affordable.
- Third, offering accessible AI education and training resources to empower individuals and organizations to learn and apply AI effectively.
- Lastly, making pre-trained AI models and APIs readily available for integration into various applications to reduce entry barriers for smaller businesses.
How much potential is there for the Middle East to become a global AI innovation hub, and what is the anticipated growth of AI adoption in the region?
The Middle East has great potential as a global AI innovation hub, driven by increased investment in AI research, development, and partnerships with international players. The region’s governments actively promote AI adoption through policies and initiatives, fostering an environment conducive to innovation.
The expected AI adoption in the Middle East is significant, particularly in vital sectors such as healthcare, finance, energy, transportation, and more. The UAE’s introduction of the National Strategy for AI 2031, it has consistently achieved AI milestones, and according to PwC AI could contribute up to 13.6 percent of the UAE’s GDP by 2030. Additionally, the UAE is set to benefit commercially with a return rate of almost 990 percent from investments in generative AI alone, amounting to $5.3 billion by 2030.
Saudi Arabia’s National Centre for AI (NCAI) aims to position the country as a global leader in AI by 2030, aligning with the Kingdom’s Vision 2030. The government’s National Strategy for Data and Artificial Intelligence (SDAIA) outlines plans to develop a comprehensive AI ecosystem.
With strong government support, a talented workforce, and a fast-growing digital economy, the region is well-positioned to contribute significantly to AI development.
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