McKinsey & Company’s new report identifies 63 use cases for generative AI which can add $2.6 to $4.4 trillion in annual growth. Discover which business areas are most likely to benefit in this quick summary of the full report.
In 2020, generative AI made waves throughout the world of life sciences. AlphaFold, an AI programme developed by DeepMind, solved the 50-year-old challenge of predicting protein structures — the so-called ‘protein-folding problem’.
But four years earlier, another AI programme; AlphaGo, also developed by DeepMind, defeated the Go grandmaster. So, despite the current novelty, generative AI has been a long time in the making.
Recently generative AI such as Midjourney and ChatGPT have captured the public imagination. These projects democratised AI and transformed the public discourse. But can they create sustainable business value too?
McKinsey’s new report not only answers that question in the affirmative but also identifies 63 unique ways in which generative AI can boost global productivity. Read on to find out more.
Generative AI can augment the capabilities of knowledge workers
The most important way in which generative AI can help you ramp up business growth is by augmenting the capabilities of individual workers. It can take over, automate and expedite repetitive parts of their job, thereby freeing them up for more substantive work.
McKinsey’s report identifies activities taking up 60 to 70 percent of employee time that have potential for automation. This is a rise from their previous estimation of about 50 percent. The potential comes from AI’s burgeoning ability to understand natural language and discern intent, a capacity pivotal for 25 percent of total work time. Understandably, the report predicts most of this impact among knowledge workers who are required to have niche educational requirements coupled with higher wages.
While the picture looks promising, global transformation is likely to take time. The report predicts that half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045. What’s more imminent are localised transformation in specific sites or companies. But which areas of business are most likely to benefit?
Generative AI can transform the most knowledge-intensive areas of business
The report predicts that 75 percent of all benefits from generative AI will be realised in four main business areas.
1. Personalising and automating customer operations
Generative AI can provide sales and customer service agents with a deeper and more accurate understanding of customer intent to improve satisfaction and increase sales. Other use cases identified by the report include an automated self-service platform which can help customers solve problems or get to the right person quickly. These use cases can improve productivity at a value of 30 to 40 percent of the current costs.
2. Enhanced performance in marketing and sales
The report identifies several interesting use cases for marketing and sales, including faster content ideation and drafting, more accurate testing and data insights, deeper search personalisation and better lead prioritisation. These can increase marketing productivity at a value of 5 to 15 percent of current marketing spend. Correspondingly, sales could see a 3 to 5 percent growth in productivity.
3. Time and resource gains in software engineering
Software development contains many repetitive processes, most of which generative AI can either automate or expedite. Both new and seasoned developers can use generative AI to rapidly create new code, improve old code and complete on-going code. It can also be used to automate testing – often a laborious task. The increase productivity through generative AI could save 20 to 45 percent of current spending.
4. Research & Development will experience a windfall
As noted in the introduction, generative AI is already solving some of the hardest challenges in life sciences. It can help identify complex biologic and biosimilar drugs, expedite drug trials and development, and bring down the cost of production. But in an industry-agnostic sense too generative AI can also improve product quality, optimise designs for manufacturing and reduce costs in logistics and production. These gains are valued between 10 to 15 percent of overall R&D costs.
The report forecasts that these benefits will be realised across a host of industries.
Generative AI can yield high dividends across a gamut of industries
The report identifies several use cases for sectors including banking, technology, retail and life sciences. For example, the banking and financial services industry can see an additional growth of $200 billion to $340 billion annually through greater adoption of generative AI. This could help banks speed up applications, improve customer experience, model risks more accurately and make better decisions.
Likewise, retail and consumer packaged goods stand to gain anywhere between $400 billion to $660 billion annually. The retail use cases in the report include immersive customer experiences, enhanced buying journey, and better management of inventory and supply chain.
Challenges ahead for generative AI adoption
Enabling generative AI usage across the economy could increase productivity by 0.1 to 0.6 percent every year until 2043, compensating for declining employment growth as populations age.
Despite the extraordinary promises that this technology holds, this report identifies several challenges ahead. Working from human prompts, generative AI is only as good as its users. To fully tap into its benefits, companies must invest significantly in reskilling or upskilling their employees; and the report predicts that many employees may have to change occupations. Employers must manage the risks and resistance that this could cause. Business leaders must also be sensitive to the disparities that this technology can create or perpetuate.
As McKinsey Global Institute partner Michael Chui, says:
“These powerful tools hold immense potential for the global economy, especially in the face of demographic challenges. But generative AI language capabilities also pose risks, capable of both enhancing human interactions and causing harm through misunderstandings, manipulation, and conflict.”
That said, we are at the cusp of a new era, the era of generative AI. You can find all the 63 use cases for 16 business functions in the full report here.
