Leveraging Generative AI for Job Augmentation and Workforce Productivity 2024

High trust, current applicability & quality In this scenario, enthusiasm for GenAI workforce adoption is high. Leadership hopes GenAI will contribute to the solving of labour shortages and anticipates it will improve the quality of work. There is a fear of missing out on opportunities as well. Organizations, fearful of disruption, are afraid of jumping on a fast-moving train too late. The majority of the workforce is also enthusiastic, influenced by the buzz on social media. They are experimenting with ChatGPT and other LLMs at home and want to use it at work to handle tedious tasks, such as generating the first draft of a report. The most active and knowledgeable employees encourage their colleagues who are more hesitant to use it. There is room for experimentation and failure, with some organizations encouraging their employees to Bring Your Own AI (BYOAI). In this scenario, organizations invest hugely in GenAI technology, in its application and in training. Over time, however, in this scenario it turns out that GenAI does not live up to the sky-high expectations. Because confidence is so high, employees also use tools that are not validated or without proper knowledge. Without a thorough understanding of how GenAI works, employees are not able to effectively interpret or validate the results it produces. This leads to inaccurate decision-making or reliance on flawed insights. So, high trust does not result in increasing productivity; on the contrary, it leads to work having to be redone (for example, one recent study showed that participants who used an LLM to solve a particular business problem exhibited a 23% lower correctness of the response compared to those who completed the task without GenAI, due to ineffective use of the tool). 40 Examples of GenAI misfires go viral on social media. Data-breach incidents are widely reported in the media, which influences the public and political debate and provides impetus for further regulation. Due to mistakes and scandals, organizations tighten their risk management. Organizations that planned to integrate GenAI into all their products and processes are not doing so: they have become reluctant, while quality and usability are stagnating. GenAI turns out to be excellent at handling administrative tasks, it is a tool that assists people but does not generate short-term breakthroughs. However, the hope that GenAI is a panacea is fading, and organizations are scaling back on their investments in GenAI because the return on investment is disappointing. They are also reserving larger budgets for training on the responsible use of GenAI and risk management. Scenario 1: High Hopes 2.1Scenario 4 Shifting Gears High trust Expanding applicability/quality Scenario 3 Lost Opportunities Low trust Expanding applicability/qualityScenario 1 High Hopes High trust Current applicability/quality Scenario 2 Broken Promises Low trust Current applicability/quality LowHigh Remains at current level Improves Applicability and quality of GenAITrust in outcomesFour scenarios for the near future of GenAI FIGURE 02 Source PwC and World Economic Forum. 12