Science & Technology


In a 2016 interview with al-Arabiya television, Saudi Arabia’s crown prince Mohammed bin Salman did not mince words when he said: “We have developed a case of oil addiction.” This is the central economic dilemma facing Saudi Arabia and the other oil-producing countries of the Middle East – their dependence on the energy sector to drive growth. A recent report by Accenture Research examines how artificial intelligence can help Saudi Arabia and others to successfully diversify their economies away from oil.

According to an International Monetary Fund report prepared for the annual meeting of the Arab Ministers of Finance in 2016, Saudi Arabia’s petroleum sector accounted for 43 percent of the kingdom’s gross domestic product (GDP) and 80 percent of its export earnings. That said, the contribution of the energy sector to the Saudi economy has been falling significantly – from over 65 percent of GDP in the 1990s to 43 percent by 2015. The deterioration began in mid-2014 with the slump in oil prices, which created both current account and fiscal deficits. This forced the Saudi Arabian Monetary Authority, constrained by the country’s fixed exchange rate regime, to draw on the country’s reserves and to issue debt to finance the dual shortfall. Annual real GDP growth has fallen from 10 percent in 2010 to a forecast 2.7 percent this year.

The only way out of this dilemma is to diversify the economy away from oil. But to achieve this goal, how much should oil ultimately contribute to Saudi Arabia’s GDP? Using a regression equation and GDP time series data from 1980, Accenture Research calculates optimal real GDP, divided between oil and non oil sectors to 2030. This modelling reveals that for the kingdom to achieve faster growth and to reduce the strain on public finances, oil’s contribution to GDP must continue to drop to around 30 percent by 2030. The model further suggests that to do this, the oil industry will need to grow at a compound annual growth rate (CAGR) of just under 2 percent, while non-oil related industries need to grow at more than twice that rate, a CAGR of 5.8 percent, for a combined GDP (oil plus non-oil) CAGR of 4.3 percent to 2030. If diversification does not take place at the anticipated rate, and oil prices remain low, the kingdom’s economy will grow at a CAGR of 2.6 percent to 2030, thus missing the Vision 2030 national development plan targets.

Many of the region’s governments have responded with a number of interconnected strategies. These include economic diversification aimed at developing non-oil sectors to provide sustainable growth and employment and reduce reliance on the public sector for jobs; significant upgrades in education and training to prepare the next generation for the jobs of the future; and the streamlining and modernization of regulation and governance. What all these strategies have in common is a commitment to artificial intelligence (AI). According to Accenture, AI has the potential to add 1.1 percentage points to Saudi Arabia’s economic growth rate representing $215 billion in annual gross value added (GVA) to the economy by 2035 (GVA is a close approximation of GDP). Moreover, Accenture’s analysis shows that AI can help address a wide range of economic and social challenges ranging from volatility of oil prices, to rapid urbanization, and to water scarcity and food security.

Accenture suggests AI can drive growth in at least three important ways. First, it can create a new virtual workforce, what Accenture calls “intelligent automation.” Second, AI can complement and enhance the skills and ability of the existing workforce and physical capital. Third, like other previous technological advances, it can drive innovations inthe economy. Over time, this becomes a catalyst for broad structural transformation as economies using AI not only do things differently, they will also do different things.

Intelligent automation

Accenture notes that AI-powered intelligent automation is already creating growth through a set of features not found in traditional automation solutions. One feature is its ability to automate complex work tasks that require agility and adaptability. For example, robots from Fetch Robotics already in use in warehouses use lasers and 3D depth sensors to navigate safely and work alongside human workers. Used in tandem with people, they can handle the vast majority of items in a typical warehouse. Another feature is AI’s ability to solve problems across industries and job titles. Amelia, an AI platform from IP soft in New York with natural language processing capabilities, can support maintenance engineers in the field because it has “read” all the manuals. Amelia has also learned the answers to the 120 questions most frequently asked by mortgage brokers. A third feature is the self-learning aspect of AI. Whereas traditional automation capital degrades over time, intelligent automation assets constantly improve. For example, more and more companies are using “chat bots,” intelligent virtual assistants, to improve customer interactions. Chat bots can recognize gaps in their own knowledge and take steps to close them. When they cannot answer a customer’s question, they escalate the issue to a human colleague, then observe how the person solves the problem.

Labor and capital augmentation

Accenture suggests that a significant part of AI-driven economic growth will come not from replacing labor and capital, but in enabling them to be used more effectively. “Relay”, an autonomous service industry robot developed by San Jose, California-based Savioke, made more than 11,000 guest deliveries in the five large hotel chains where it was deployed, freeing hotel staff to focus on parts of their role that add the most value. AI can also augment labor, complementing human capabilities, offering employees new tools to enhance their natural intelligence. For example, an AI start-up in China has launched a legal semantic case search service. According to the case description and key word input, it retrieves the most relevant case histories with their full written judgments, as well information regarding participants, proceedings, investigations, defense and other matters, saving lawyers from the time consuming search process. For industries where physical capital represents a large sunk cost, AI, using analytics and advanced machine learning, can also improve capital efficiency by reducing factory downtime, for example. Augmenting and in many cases, creating human capital is a primary focus of AI strategies in Saudi Arabia and other countries in the region as two dominant trends converge: the diversification of these economies, which creates the need for a more knowledge-intensive, higher-value-added workforce in virtually every sector; and a growing burden of youth unemployment, made even more acute by the saturation of the public-sector labor market, a favoured source of jobs in the past. If more productive work and employment opportunities are to be created to meet these needs, it is critical that this new workforce is educated and has the right skills.

Innovation diffusion

At the heart of Saudi Arabia’s Vision 2030 is the technology sector. The clearest sign of this commitments NEOM, a planned $500 billion,26,500 square-kilometer “megacity”: part technology and R&D hub, part international trade center, part business and advanced manufacturing zone. “Everything will have a link with artificial intelligence and the internet of things – everything,” the crown prince told Bloomberg last year. Envisioned as a quasi-independent special zone, with its own laws, regulations and judiciary (though it will remain under the kingdom’s sovereignty), its primary purpose is to attract as much global investment, business and talent as possible, particularly in fields like biotechnology, advanced and additive manufacturing, and robotics. It is also intended to showcase the latest examples of machine learning, data mining and cognitive computing, AI tools that will enable the sort of interdisciplinary, cross-industry innovations in areas like energy and water, transport and food production that NEOM was created to incubate. Its planners are confident that NEOM will ultimately pay for itself, predicting that it will eventually contribute as much as $100 million a year to the Saudi economy. But it is not the only Saudi project devoted to AIpowered innovation. The National Digitization Unit (NDU) was established to pursue a range of initiatives and public private partnerships with the goal of further developing the kingdom’s digital environment and creating 200,000 jobs in the process. Among the NDU’s corporate partners are SAP and GE. At the same time, the kingdom’s Future Investment Initiative has been charged with, among other goals, identifying which industries will be transformed most by AI and how to smooth the transition of workers disadvantaged by technological disruption.


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