Managers should be careful about how they use generative AI. There are two schools of thought. The first is that it makes people lazy, business leaders lose their creativity and ability to make good decisions when they outsource their wisdom to AI. The second, is that it positively augments peoples\u2019 capabilities, boosting performance, innovation and productivity.\u00a0<\/p>\n\n\n\n
The latest research by Patrick Haack, Professor of Strategy and Responsible Management, at HEC Lausanne, University of Lausanne, and his colleagues1<\/sup> shows that both schools of thought are valid. This has implications for what LLM (large language models) are used for in organisations in the future. <\/p>\n\n\n\n \u201cOur perspective is more nuanced. The use of generative AI chatbots can lead to either deskilling or upskilling, depending on how managers integrate AI into their work practices and how organisations structure and support its use,\u201d explains Professor Haack.<\/p>\n\n\n\n This is because the use of artificial intelligence affects so-called “managerial phronesis<\/em>.” This is the practical wisdom, which managers develop through human interaction, real-world experiences and reflection. This body of knowledge allows managers to make moral and context-specific judgments in complex situations in pursuit of organisational goals.<\/p>\n\n\n\n \u201cIf a lot of decision making is being outsourced and cognitively offloaded to AI, particularly for junior managers, then they will lack an experiential base of learning. When they become senior managers they may then fail to solve problems independently of AI,\u201d says Professor Haack.<\/p>\n\n\n\n The team of researchers from HEC Lausanne, Universities of Bath, Ohio and Cardiff, created a theoretical model.1<\/sup> It identified the organisational and technological conditions under which AI supports thoughtful decision-making, as well as the conditions in which it may lead managers to over-rely on algorithmic recommendations, disengage from critical reflection, and gradually lose important judgement capabilities. \u00a0<\/p>\n\n\n\n This research comes at an important time as many more organisations across the globe embed AI capabilities into their business practices and operations. The increasing use of large language models, trained on internal and external business data, has huge implications on how businesses are designed now and in the future.<\/p>\n\n\n\n \u201cThe main implication of this research is that organisations need to create spaces where managers and employees can continue to experiment and learn from real life experiences. We must create a future generation of managers that are still able to lead an organisation without the use of AI.\u201d<\/p>\n\n\n\n The research also raises another question for organisations. This concerns accountability, since AI can act negatively or positively, managers have to be more proactive rather than passive when it comes to dealing with this technology. \u00a0<\/p>\n\n\n\n \u201cManagers must always be accountable for their decisions with or without the use of AI. They will then tend to reflect more carefully about the wisdom behind their thinking, justifying and explaining their reasons for the decisions they make. AI should be used as a sparring partner and conversational tool allowing me to critically reflect,\u201d details Professor Haack.<\/p>\n\n\n\n He continues: \u201cWe are constantly told that AI is the next big thing and that it will revolutionise business. Many people simply accept this narrative without questioning it. But the future of AI is not predetermined. We have both the opportunity and the responsibility to actively shape how this technology is developed and used, ensuring that it serves our collective interests. We are not merely passive observers of technological change. Each of us has the power to help shape the future we want to see.\u201d Reference:<\/strong><\/p>\n\n\n\nEmphasising practical wisdom<\/strong><\/h3>\n\n\n\n
Making AI accountable<\/strong><\/h3>\n\n\n\n
<\/p>\n\n\n\n