Embrace the generative AI era: Six adoption essentials Figure 4: Generative AI will transform work across every job category Take a people-first approach Office and Administrative Support 57% 6% 14% 23% Work time distribution by major Success with generative Sales and Related 49% 13% 14% 24% occupation and potential AI impact 2AI requires an equal attention on Based on their employment levels in the US in 2021 people and training as it does on Computer and Mathematical 28% 32% 23% 17% technology. Companies should Business and Financial Operations 45% 14% 35% 6% therefore dramatically ramp up Lower potential for Higher potential for Higher potential for augmentation or Non-language investment in talent to address Arts, Design, Entertainment, Sports, and Media 25% 26% 26% 22% automation augmentation automation tasks two distinct challenges: creating Life, Physical, and Social Science 27% 20% 25% 28% AI and using AI. This means both building talent in technical Architecture and Engineering 21% 24% 25% 30% competencies like AI engineering and enterprise architecture Legal 33% 9% 58% 0% and training people across the Occcupation Average 31% 9% 22% 38% In 5 out of 22 occupation organization to work effectively with AI-infused processes. In our Management 30% 9% 44% 17% groups, Generative AI can analysis across 22 job categories, Personal Care and Service 29% 8% 31% 32% affect more than half of all for example, we found that hours worked LLMs will impact every category, Healthcare Practitioners and Technical 22% 15% 40% 22% ranging from 9% of a workday at Community and Social Service 29% 7% 59% 6% the low end to 63% at the high end. More than half of working Healthcare Support 27% 8% 31% 34% hours in 5 of the 22 occupations Protective Service 29% 6% 23% 43% can be transformed by LLMs. Educational Instruction and Library 23% 8% 50% 19% Food Preparation and Serving Related 25% 5% 9% 61% Source: Accenture Research based on analysis of Occupational Transportation and Material Moving 23% 4% 7% 66% Information Network (O*NET), US Dept. of Labor; US Bureau of Labor Statistics. Construction and Extraction 15% 4% 7% 75% Notes: We manually identified 200 tasks related to language (out Installation, Maintenance, and Repair 16% 1%9% 75% of 332 included in BLS), which were linked to industries using their share in each occupation and the occupations’ employment level Farming, Fishing, and Forestry 8% 8% 17% 66% in each job category. Tasks with higher potential for automation can Production 14% 2% 8% 76% be transformed by LLMs with reduced involvement from a human worker. Tasks with higher potential for augmentation are those in Building and Grounds Cleaning and Maintenance 9% 0% 7% 84% which LLMs would need more involvement from human workers. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% A new era of generative AI for everyone | 15