Prolific AI technologies like ChatGPT have taken the world by storm with their incredible ability to analyze natural language and make deeply human decisions. This latest advancement in AI is rapidly transforming businesses and businesses, forcing companies, governments and individuals to assess its impact in real time.

Our most recent McKinsey Global Institute productive AI and productivity research found that productive AI can create the equivalent of $2.6-4.4 trillion in annual global corporate profits. There were 63 use cases that we predicted would increase productivity for generative AI, including supporting customer interactions, creating creative content for marketing and sales, and generating software code based on natural language prompts, among many other tasks. This will increase the value of AI and analytics productivity by 15% to 40% compared to previous generations of the technology; an amount that will roughly double as productive AI becomes more prevalent worldwide.

We estimate that productive AI will likely have the greatest impact on banking, hi-tech and life sciences as a percentage of total industry revenue. In banking, for example, the technology could create value equal to an additional $200 billion to $340 billion per year if all use cases are tracked. This does not mean that other industries cannot benefit greatly from the adoption of productive AI. In total, retail and consumer goods companies, for example, could generate an additional $400-660 billion in annual revenue from the use of manufacturer AI.

Across all industries, nearly three-quarters of the value of productive AI will come from four business areas: customer service, marketing and sales, software development, and research and development. In some of the use cases we discovered, the technology acted as a virtual expert, providing information and making suggestions, for example, to answer a retail customer’s question or develop creative content for marketing purposes. In other cases, the tech may be a virtual co-author, creating candidate molecules for teams working on new drug development, or recommending and editing code for a software engineer.

Much of the value of productive AI will come from productivity gains in the economy as technology-affected workers move into new jobs. We estimate that productive AI could increase workforce productivity by 0.1% to 0.6% per year by 2040. Combined with other technologies, workforce automation can add another 0.2 to 3.3 percentage points to productivity gains.

Along with other technologies, the existing capabilities of generative AI have the theoretical potential to automate business activities such as writing emails or answering customer questions, which currently take between 60% and 70% of employees’ time at work. In contrast, we predicted earlier in 2017 that technologies available at the time could automate activities that took up half their time.

This is largely due to the capabilities of natural language and generative AI, which are essential for business activities that take about a quarter of total work time and exceed the capabilities of previous AI generations. The ability of generative AI to communicate with the user and draw conclusions from that conversation also means that it will have a greater impact on knowledge work, which plays a larger role in occupations with higher salaries and educational requirements. This is a distinct difference from the influence of legacy artificial intelligence that greatly automates manual tasks.

Additionally, the pace of workforce transformation is likely to increase as a result of the greater potential of technical automation. We have developed scenarios to predict the actual rate of adoption of these technologies in the global workforce and have been updated to account for the impact of productive AI. the midpoint is about ten years ahead of our 2045 or 2017 projections. And while adoption may take decades in workforces around the world, individual companies can transform their operations much faster with productive AI for competitive advantage.

Employees will need support in learning new skills that will help them work with generative AI and, in some cases, change roles. Corporate leaders can start by reviewing core business processes and assessing where generative AI can best be applied and how employees can work with it, and identifying what new skills and abilities they may need. Only by actively managing the transition to generative AI and assessing risks can the important economic prospects of generative AI be fully realized. Source