Embrace the generative AI era: Six adoption essentials 2 In fact, independent economic research indicates that companies are significantly underinvesting in helping workers keep up with advances in AI, which require more cognitively complex and judgment-based tasks. 11 Even domain experts who understand how to apply data in the real world (a doctor interpreting health data, for example) will need enough technical knowledge of how these models work to have confidence in using them as a “workmate.” There will also be entirely new roles to recruit, including linguistics experts, AI quality controllers, AI editors, and prompt engineers. In areas where generative AI shows most promise, companies should start by decomposing existing jobs into underlying bundles of tasks. Then assess the extent to which generative AI might affect each task — fully automated, augmented, or unaffected. Figure 5: Reinventing a customer service job, task by task To assess how specific jobs will be reinvented with AI, an Accenture analysis decomposed one customer service job into 13 component tasks . We found: 4 tasks would continue to be performed primarily by humans, with low potential for automation or augmentation. 4 tasks could be fully automated — such as gathering, classifying, and summarizing information on why a customer is contacting the company. 5 tasks could be augmented to help humans work more effectively — such as using an AI summary to provide a rapid solution with a human touch. Importantly, new job tasks might also be needed to ensure the safe, accurate and responsible use of AI in customer service settings, such as providing unbiased information on products and pricing. 16 A new era of generative AI for everyone |