Generative AI Tools Drive Explosive Growth: McKinsey Report

Learn how gen AI transforms business and society in McKinsey's latest report

Artificial intelligence (AI) has advanced rapidly in the past decade, with breakthroughs in computer vision, natural language processing, speech recognition, and machine learning. However, the most recent and remarkable development in AI is the emergence of generative AI (Gen AI), which can create new content or data from scratch, such as text, images, music, code, and more.

Generative AI is powered by foundation models, large and complex neural networks that can learn from massive and diverse datasets and perform multiple tasks across domains. Foundation models have enabled new capabilities and vastly improved existing ones across various modalities, including images, video, audio, and computer code.

Generative AI has captured people's attention worldwide in a way that previous AI achievements did not, thanks to its broad utility and preternatural ability to converse with a user. Generative AI applications such as ChatGPT, GitHub Copilot, Stable Diffusion, and others have demonstrated remarkable capabilities to communicate and create. These tools have sparked curiosity and experimentation among consumers, businesses, and policymakers alike, offering new possibilities for innovation, productivity, and entertainment.

But how widespread is the use of generative AI? How will it impact different industries, functions, and regions? And what are the challenges and risks that need to be addressed to ensure its responsible and beneficial use?

A new report by McKinsey & Company aims to answer these questions by analyzing the current state and prospects of generative AI. The report is based on the latest annual McKinsey Global Survey on AI, conducted in mid-April 2023 and involved more than 2,000 executives, experts, and users of generative AI tools from various sectors and regions.

The main findings of the report are:

Generative AI is already widely used and expected to grow rapidly. According to the survey, one-third of the respondents say their organizations use generative AI regularly in at least one business function, and 40 percent say they will increase their investment in AI overall because of advances in generative AI. The most common use cases are content creation (such as marketing materials, reports, and presentations), data analysis (such as data cleaning, classification, and visualization), and communication (such as chatbots, email generation, and translation).

Leading companies are already ahead with generative AI. The survey reveals that the organizations that have already embedded AI capabilities in their core processes and products have been the first to explore generative AI's potential. These organizations are called AI high performers, accounting for 22 percent of the respondents. They are already outpacing others in adopting generative AI tools, reporting higher value from generative AI use cases, and expecting more disruption from generative AI in their industries.

AI-related talent needs shift, and generative AI's workforce effects are expected to be substantial. The survey predicts that generative AI will affect up to 60 percent of all work activities by 2030, with varying degrees of automation potential. Some activities will be fully automated (such as data entry), some will be augmented (such as content editing), and some will be newly created (such as content curation). This will require workers to adapt their skills and roles to the changing demands of the labor market. The survey estimates that up to 375 million workers globally may need to switch occupations or learn new skills by 2030 due to generative AI.

With all eyes on generative AI, AI adoption and impact remain steady. The survey shows that while generative AI might spur the adoption of other AI tools, there are few meaningful increases in organizations' adoption of these technologies. The percentage of organizations adopting AI tools has held steady since 2022, and adoption remains concentrated within a small number of business functions. Moreover, the impact of AI on business performance has mostly stayed the same since 2022. The survey suggests barriers to scaling AI across organizations, such as data quality and availability, model robustness and reliability, human oversight and control, privacy and security, fairness and bias, accountability and transparency, regulation and governance, and social and cultural implications.

The report concludes that generative AI is a powerful and disruptive technology that has the potential to drive explosive growth across sectors, regions, and functions. However, it also cautions that generative AI is not a silver bullet and requires careful management and coordination to maximize its value and minimize its risks. The report urges leaders and decision-makers to embrace generative AI as a strategic priority and invest in its development and adoption while ensuring its alignment with human values and societal goals.