A look ahead at the fast-paced evolution of technology, regulation and business The scale of adoption in business Figure 3: Generative AI will transform work across industries Companies must reinvent work to find a path to generative AI value. Business Banking 54% 12% 24% 10% Work time distribution by industry leaders must lead the change, starting Insurance 48% 14% 26% 12% and potential AI impact now, in job redesign, task redesign and Based on their employment levels in the US in 2021 reskilling people. Ultimately, every role Software & Platforms 36% 21% 28% 15% in an enterprise has the potential to Lower potential for Capital markets 40% 14% 29% 18% Higher potential for Higher potential for augmentation or Non-language be reinvented, once today’s jobs are automation augmentation automation tasks decomposed into tasks that can be Energy 43% 9% 14% 34% automated or assisted and reimagined for a new future of human + machine work. Communications & Media 33% 13% 21% 33% Generative AI will disrupt work as Retail 34% 7% 12% 46% we know it today, introducing a new Industry Average 31% 9% 22% 38% 40% of working hours across dimension of human and AI collaboration industries can be impacted by in which most workers will have a “co- Health 28% 11% 33% 27% Large Language Models (LLMs) pilot,” radically changing how work is Public Service 30% 9% 35% 26% done and what work is done. Nearly every job will be impacted – some will Aerospace & Defense 26% 13% 20% 41% Why is this the case? Language tasks account for 62% of total worked time be eliminated, most will be transformed, in the US. Of the overall share of language tasks, 65% have high potential and many new jobs will be created. Automotive 30% 6% 13% 50% to be automated or augmented by LLMs. Organizations that take steps now to High Tech 26% 8% 16% 50% decompose jobs into tasks, and invest in training people to work differently, Travel 28% 6% 15% 50% alongside machines, will define new Utilities 27% 6% 15% 52% performance frontiers and have a big leg Source: Accenture Research based on analysis of Occupational up on less imaginative competitors. Life Sciences 25% 8% 17% 50% Information Network (O*NET), US Dept. of Labor; US Bureau of Labor Statistics. Industrial 26% 6% 14% 54% Notes: We manually identified 200 tasks related to language (out Consumer Goods & Services 24% 6% 13% 57% of 332 included in BLS), which were linked to industries using their share in each occupation and the occupations’ employment level Chemicals 24% 5% 14% 56% in each industry. Tasks with higher potential for automation can Natural Resources 20% 5% 11% 64% be transformed by LLMs with reduced involvement from a human worker. Tasks with higher potential for augmentation are those in 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% which LLMs would need more involvement from human workers. A new era of generative AI for everyone | 11