Artificial intelligence (AI) can play a crucial role in assisting leaders and their teams in making strategic, as well as immediate, data-driven decisions and taking effective action. Research has shown that generative AI adoption in marketing reveals promising productivity gains with marketers estimating generative AI can save them the equivalent of over a month per year, making room for more meaningful work. Some estimates are forecasting that AI has the potential to automate 40% of the average workday
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The latest report from McKinsey on the economic potential impact of generative AI points to what may be the next productivity frontier. The report studied 16 business functions, examining 63 use cases in which the technology can address specific business challenges in ways that produce one or more measurable outcomes.
Here are some of the key forecasts on the impact of generative AI from the McKinsey report:
- McKinsey’s latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases analyzed by McKinsey — by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. This would increase the impact of all artificial intelligence by 15 to 40%.
- About 75% of the value that generative AI use cases could deliver falls across four areas: Customer operations, marketing and sales, software engineering, and R&D.
- Generative AI will have a significant impact across all industry sectors. Banking, high tech, and life sciences are among the industries that could see the biggest impact as a percentage of their revenues from generative AI.
- Generative AI has the potential to change the anatomy of work, augmenting the capabilities of individual workers by automating some of their individual activities. Current generative AI and other technologies have the potential to automate work activities that absorb 60-70% of employees’ time today. The acceleration in the potential for technical automation is largely due to generative AI’s increased ability to understand natural language, which is required for work activities that account for 25% of total work time.
- The pace of workforce transformation is likely to accelerate, given increases in the potential for technical automation. Our updated adoption scenarios, including technology development, economic feasibility, and diffusion timelines, lead to estimates that half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045, or roughly a decade earlier than in our previous estimates.
- Generative AI can substantially increase labor productivity across the economy, but that will require investments to support workers as they shift work activities or change jobs. Generative AI could enable labor productivity growth of 0.1 to 0.6% annually through 2040, depending on the rate of technology adoption and redeployment of worker time into other activities.
- The era of generative AI is just beginning. Excitement over this technology is palpable, and early pilots are compelling. But a full realization of the technology’s benefits will take time, and leaders in business and society still have considerable challenges to address. These include managing the risks inherent in generative AI, determining what new skills and capabilities the workforce will need, and rethinking core business processes such as retraining and developing new skills.
Value potential of generative AI by business function will vary. McKinsey’s analysis of 16 business functions identified just four –customer operations, marketing and sales, software engineering, and research and development — that could account for approximately 75% of the total annual value from generative AI use cases.
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One very important takeaway from the McKinsey report is this: “In addition to the potential value generative AI can deliver in specific use cases, the technology could drive value across an entire organization by revolutionizing internal knowledge management systems.”
The impact of generative AI by business functions do vary but the report notes very compelling specific examples: Generative AI could increase sales productivity by 3-5% of current global sales expenditures. Across 63 use cases, generative AI has the potential to generate $2.6 trillion to $4.4 trillion in value across industries.
The McKinsey report concludes with forecasting the impact of generative AI on the future of work, noting that over the years, machines have given human workers various “superpowers”.
For many industries, generative AI, trust, data security and improved digital experiences are key priorities to improve the overall customer experience. To learn more about the potential impact of generative AI on the economy, you can review the robust McKinsey report here.
Artificial Intelligence