Summarize this content to 2000 words in 6 paragraphs in Arabic Unlock the Editor\u2019s Digest for freeRoula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.The \u201cbusiness hospice\u201d is how some companies are describing the final destination for corporate operations at risk of being wiped out by artificial intelligence.Orchestrating a soft landing for people working in such activities is just one of the new challenges facing managers, according to AI ethicist, Lollie Mancey, who introduced me to the term this month.Her point is that nobody goes into business hoping their legacy will be an enterprise that consists of a handful of executives and some large language models: \u201cOur organisations are made of people; we have organisational culture and we need to protect that.\u201dThe need to \u201ckeep humans in the loop\u201d is becoming almost as much of a clich\u00e9 as the claim that AI is about better jobs, not fewer jobs. But that loop needs managing, often in novel and unfamiliar ways. I\u2019ve added palliative care nurse to the growing list of roles managers will have to acquire, as AI spawns new, improbable-sounding managerial jargon. Here are six more.Possibility catalyser. We have to \u201ceducate our workforce en masse about what is possible\u201d with AI, says Jacky Wright, McKinsey\u2019s chief technology and platform officer, whose job includes rolling out AI tools to the consulting firm. Being a manager is now also about \u201cbeing a catalyst and a champion\u201d of what could be done differently with the new technology, adds Nitin Mittal, Deloitte\u2019s global AI leader.Uncertainty mapper. Nobody should underestimate employees\u2019 \u201cfear of being obsolete\u201d. FOBO squats at the other end of the uncertainty spectrum from FOMO (fear of missing out). PwC\u2019s commercial technology and innovation officer Matt Wood, formerly Amazon Web Services AI vice-president, says the constant quest for efficiency \u201cdrives a lot of mistrust inside organisations\u201d. It falls to managers to try to soothe both forms of AI-driven panic.Organisational designer. Teams need to apply the power of AI tools correctly and in the right place. Their managers need first to work out what parts of any task can be automated, \u201cwhat can be augmented and what do the new processes look like\u201d, says Aditya Bhasin, chief technology and information officer at Bank of America. Next, they need to redesign the work to ensure staff \u201cdo a lot more of the \u2018why\u2019 and the \u2018what\u2019, and let the machine do a lot more of the \u2018how\u2019\u201d, according to Harrick Vin, Bhasin\u2019s counterpart at Tata Consultancy Services.Growth amplifier. Managers need to ask themselves \u201cwhat skills can [they] accelerate and amplify using this technology today?\u201d says PwC\u2019s Wood. Yet they will sometimes also need to act as ambition moderators.\u00a0I heard one executive last year describe the effect of applying generative AI as an instant promotion for all 2,000 of his staff. But in the words of Deloitte\u2019s Mittal, for a consultant to be able to sit down with an important client and \u201cmake sure he\u2019s comfortable and feels that you\u2019re credible \u2014 that\u2019s years and years of learnt experience and you can\u2019t \u2018prompt\u2019 yourself to it\u201d. Managers need to mentor their team members carefully so they develop those skills and do not immediately assume they can do it all because they have the help of a machine.Ideas evaluator. If the output of the AI-augmented worker is less likely to be lines of code or quantity of PowerPoint slides, the manager\u2019s role becomes more one of \u201cencouraging peer review or quality assurance, than of checking the individual\u2019s work or making sure they have the technical competency\u201d, says BofA\u2019s Bhasin.\u00a0Managers may need to re-examine even the basics of workers\u2019 terms and conditions in light of AI. \u201cIf you are doing a job in two hours because you\u2019re using AI, are you going to be paid for the same seven hours you would normally be paid for. How are we going to work that out?\u201d asks Mancey.This forecast reimagining of managerial work comes with some important caveats. Workplace technology expert Danielle Li, a professor at MIT Sloan School of Management, points out that \u201ceverybody knows how to talk about culture and change management\u201d, which is why leaders inevitably frame AI in those terms. But she says they need to put in place the foundations for effective use of AI, notably properly organised, high-quality data.The potential benefits of AI are many. It could be used, for instance, to disseminate expert teachers\u2019 and managers\u2019 insights, helping to meet the challenge of educating the workforce about the opportunities offered.First, though, managers need to work out how, in Li\u2019s words, \u201cto incentivise, to compensate, to excite people\u2009.\u2009.\u2009.\u2009that the nugget of an idea that lives inside you\u201d will be shared with a machine. And, I might add, how to explain that the same machine may be about to send you, your job and the organisation where you work, on a one-way trip to the business hospice.andrew.hill@ft.com<\/p>\n","protected":false},"excerpt":{"rendered":"
Summarize this content to 2000 words in 6 paragraphs in Arabic Unlock the Editor\u2019s Digest for freeRoula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.The \u201cbusiness hospice\u201d is how some companies are describing the final destination for corporate operations at risk of being wiped out by artificial intelligence.Orchestrating a soft<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[63],"tags":[],"class_list":{"0":"post-247584","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-tech"},"_links":{"self":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/247584","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/comments?post=247584"}],"version-history":[{"count":0,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/247584\/revisions"}],"wp:attachment":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/media?parent=247584"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/categories?post=247584"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/tags?post=247584"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}