Over the past six months, employees across industries, from marketers and developers to product designers, have discovered how generative AI can help them improve their jobs. This means creating exceptional content in a fraction of the time, accelerating IT coding and testing processes, and optimizing product simulation and design for higher quality. In other words, generative AI can give you “super powers.”
In our latest report, “The Economic Potential of Generative AI: The Next Productivity Frontier,” researchers at the company also believe generative AI could deliver an economic impact worth $2.6 trillion to $4.4 trillion annually. I predict it will.
“On a personal level, it’s very appealing because it can be used by almost anyone,” explains McKinsey Global Institute (MGI) partner Michael Chewie. “Generative AI has captivated the imagination of business leaders in a way that many technology trends don’t. Then you can open your browser and start asking questions.”
With the right prompts, ChatGPT can write a short story, summarize 1000 pages into a five-point plan, or even compose a song.
Generative AI is off to a great start, but experience shows that getting the most value out of the technology and implementing it across your organization takes time, talent, and effort.
Here, three experts, Alexander Sukharevsky, senior partner and global co-leader of QuantumBlack, McKinsey AI, and Lareina Yee, senior partner at McKinsey, share what they learned from their research and early adopters. increase.
Let’s start with the big question. What is McKinsey doing with generative AI today?
Alexander: We have been investing in AI for years, and generative AI is nothing new to us. Our first investment in this area was about five years ago. We continue to focus on creating and scaling enterprise-grade solutions. To achieve this, we have a large talent pool of over 1,500 data scientists and engineers in more than 50 countries and an extensive ecosystem of external partners. Earlier this month, we announced QuantumBlack Horizon, a suite of solutions purpose-built to help enterprises scale AI, including generative AI, in a secure and cost-effective manner.
From left, McKinsey senior partner Lareina Yi. Michael Chui, MGI Partner.Alexander Sukharevsky, Senior Partner at McKinsey and Global Co-Leader of QuantumBlack, McKinsey’s AI
Generative AI could give you ‘superpowers’, new McKinsey study finds
What can we learn from early adopter experiences?
Alexander: The CEO’s conversation has changed from “what’s this?” to what it was a few weeks ago. “What should my organization do about this problem and how do I get started?” We need to learn about technology, establish a common language, rethink business models, and possibly redefine our respective industries. It doesn’t take long, I think it’s exactly the “age of creators”.
Multiple industries will be completely transformed by using AI to lower barriers to entry, remove the middle ground from corporate structures, and deliver the same value proposition at a fraction of the current cost. The way organizations define opportunities and the speed of execution will distinguish future winners.
While there has been some fatigue with respect to AI implementations, the energy generated by generative AI has put AI projects back in the spotlight and has allowed companies to get back to the same basics: data quality and availability, IT architecture, technology, and data availability. Strengthened the need to fix availability. Translator features, and a rewired operating model. It’s not easy, but it’s essential for long-term success.
Let’s talk a little bit about research and major discoveries.
Michael: We used a methodology established in 2017 to analyze how automation technology is impacting the workforce. We surveyed 850 occupations in 47 countries covering about 80% of the world’s workforce. Each occupation was then categorized into 20-30 “sub-activities”. For generative AI, we analyzed tasks such as understanding natural language, communicating with others, and searching and gathering information.
We estimate that about 60-70% of the time people spend at work could theoretically be transformed by a combination of generative AI and other technologies. It may take years for this to happen, but the potential is very high. In fact, we’ve updated our model to match the speed at which these technologies may be introduced. Depending on the scenario, the pace of generative AI adoption could accelerate by a decade compared to previous projections.
When it comes to use cases, there is potential across the enterprise, but 75% of the potential value of generative AI is concentrated in four functions: customer operations, marketing and sales, software engineering, and research and development.
In general, employees can spend more time on the relationship and interaction aspects of their role, which is not being taken away by AI.
Lareina Yi, McKinsey Senior Partner
What does this mean for the average worker?
La Reina: We say generative AI gives people “super powers”. This means that many of the routine tasks people do at work can be automated, making them more productive and more interesting. This technology works as a coding assistant, researcher, and even editor.
In early use cases in call centers, we found generative AI helping short-tenured, say, Level 1 reps get promoted to Level 4 faster. AI enables them to handle increasingly complex situations faster, with techniques similar to those of more skilled workers, such as high-quality scripts and detailed customer context. Spend less time creating materials and more time interacting with customers. People are generally pretty excited about this.
Software developers can perform mundane tasks such as translating, debugging, and testing legacy code with generative AI, so they can spend more time developing new features.
Wealth managers can spend more time advising clients than analyzing and summarizing large amounts of technical content.
In general, employees can spend more time on the relationship and interaction aspects of their role, which is not being taken away by AI.
What are the implications for the organization as a whole?
Michael: It means a lot of changes are coming as we all need to change our activities. Some jobs will change, some will disappear, and new jobs will be created, such as agile engineers. It’s a great challenge and an opportunity to retrain your skills.
On the one hand, this creates a surplus of time that could be used to build another work-life balance, or even lead to the start of a four-day work week.
