AI has made remarkable progress since its inception (late 1950s to 1960s) and presents an attractive outlook, but we must not overlook its challenges. Perhaps we can consider "managing the inherent risks associated with generative AI, defining skills, recruiting specialized human resources, new workforce utilization capabilities, and revising core business processes such as retraining and developing new skills" as the challenges in this field.
It should be noted that generative AI can contribute trillions of rials to the national economy by influencing four main areas: "customer operations," "marketing and sales," "software engineering," and "research and development."
According to the latest report by global management consulting firm McKinsey, in 63 case studies across the world, the use of generative AI tools can annually add between $2.6 trillion to $4.4 trillion to the global economy. To put it into perspective, the entire Gross Domestic Product (GDP) of the United Kingdom in 2021 was $3.1 trillion. It’s conceivable to estimate the impact of AI on enhancing the productivity of economies between 15 to 40 percent.
McKinsey also noted that if the impact of using generative AI tools on the software currently in use is added, this impact will double. Imagining such an influence on banking systems and software in the country, which often have outdated structures and are heavily dependent on sanctioned hardware, could mark a turning point in the development of the software market in the country.
Undoubtedly, solutions based on generative AI will lead to significant transformations in existing structures and cooperation with knowledge-based and innovative groups in this area will replace the use of old and costly infrastructures.
Based on this data, it can be said that 75 percent of the value generated by generative AI in the economy is related to the four main areas of "customer operations," "marketing and sales," "software engineering," and "research and development." For example, generative AI's ability to support customer interaction, create creative content for marketing and sales, and provide intelligent financial services on various platforms using natural language notifications can replace traditional services in bank branches and financial institutions.
Currently, AI is being used more significantly in various industries such as retail customer services, comprehensive banking, and life sciences, and can help improve productivity and economic growth. On the other hand, the financial industry and advanced technologies are among the industries that can generate the most value from their revenues through generative AI.
Among these industries, perhaps banks are one of the most popular industries to utilize AI, in such a way that its use in providing services, mobile banking, enhancing security with intelligent fraud detection, e-commerce, etc., has made it attractive for practitioners in this field. McKinsey also estimates that if the banking industry utilizes generative AI, it will witness value creation between $200 billion to $340 billion. This technology can also reduce the time required for tasks such as code production and optimization, thus improving the efficiency and satisfaction of developers.
Under these circumstances, while the world and developed countries are looking to gain a share from the applications of AI in the digital economy and other areas, training, learning, and application are essential for expanding the use of AI in Iran's economy. Not only should AI not be seen as a threat or risk, but efforts should be made to align our activities with AI and benefit from its commercial advantages.
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