Productivity gains will grow as people use AI

The integration of AI into various business processes and functions is expected to yield significant productivity gains, fundamentally altering how work is performed and enhancing both the efficiency and the quality of outputs. Studies and analyses from Nielsen Norman Group, McKinsey, and the World Economic Forum highlight various dimensions of these gains, from individual task performance to broader economic impacts.

The Nielsen Norman Group’s research indicates that deploying generative AI across all business users could potentially increase productivity by around 66%, with more complex tasks leading to bigger AI gains. Notably, the quality of work also improves with AI assistance, suggesting that AI does not merely increase the speed of work but also its quality. This is exemplified in the business domain, where documents composed with AI support were rated significantly higher in quality than those without (https://www.nngroup.com/articles/ai-tools-productivity-gains/).

From an economic perspective, McKinsey’s analysis estimates that generative AI could add between $2.6 trillion and $4.4 trillion annually across various use cases, augmenting the value generated by non-generative AI and analytics significantly. This projection encompasses a wide range of business functions, with customer operations, marketing and sales, software engineering, and R&D standing out as areas where generative AI could deliver a majority of its value. The research underscores the potential for generative AI to drive substantial gains in productivity by taking over tasks that typically consume significant amounts of a knowledge worker’s time, such as information retrieval and data analysis, thus allowing employees to focus on higher-impact tasks (https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier).

Furthermore, the World Economic Forum discusses the “productivity J-curve,” a concept suggesting that new technologies, including AI, often initially lead to a dip in measured productivity due to investments in complementary goods like business processes and skills. However, this investment phase is followed by significant gains in productivity as the technology is fully integrated and utilized (https://www.weforum.org/agenda/2023/05/can-ai-actually-increase-productivity/#:~:text=URL%3A%20https%3A%2F%2Fwww.weforum.org%2Fagenda%2F2023%2F05%2Fcan).

These findings collectively underscore the transformative potential of AI on work and productivity. By automating routine tasks, enhancing the quality of work, and enabling employees to focus on more complex and creative tasks, AI is poised to drive significant efficiency gains across various sectors. However, the realization of these gains is contingent upon overcoming initial investment hurdles and effectively integrating AI into existing work processes.