Perhaps the only thing outpacing AI spending is the volume of commentary dedicated to the technologyâs disruption. And while business leaders arenât lacking for insights, they are discovering that AI is evolving faster than any coherent playbook can keep up with. The result is that companies are making high-stakes decisions without clear returns, stable organizational structures or even agreement over whoâs in charge. In a conversation with Ken Brown, The Informationâs senior finance editor, Kathryn Kaminsky, U.S. chief commercial officer at PwC, described how that uncertainty is reshaping everything from investment decisions to workforce planning, and is pushing leaders to rethink not just how they deploy AI but how they define success. Not Your Parentsâ Tech Cycle Unlike previous tech cycles where innovations primarily impacted one business function, Kaminsky observed that AI is touching every inch of the C-suite. âThe CEO obviously cares about AI because theyâre investing so much. Human capital cares because they donât know what workforce planning is going to look like. The back office cares because theyâve been the guinea pigs,â she said. âWhen I think about change in the world of AI, the biggest difference is how itâs impacting multiple people in the C-suite.â From chief information officers to chief human resources officers, corporate leaders are trying to factor AI into their planning, a task the technologyâs rapid evolution is making difficult. This puts pressure on traditional change management processes that werenât designed for this pace. By way of example, Kaminsky noted the quandary CIOs are finding themselves in as they attempt to pick which models to embed in the enterprise. In the past, the decision would have been at their discretion. Today, thatâs less frequently the case. âIs the business telling the CIO what they need or is the CIO telling the business? Thereâs a question now of who should own the transformation,â said Kaminsky. In practice, that uncertainty is playing out in how companies adopt AI. Rather than testing a single provider, many are testing multiple frontier models at once as capabilities evolve quickly and different tools excel at different tasks. âCIOs normally have a process for things like what hyperscaler to use and how to use it. But what weâre seeing is that they may have to bring on more than they normally would, which in a way is very anti-ROI. How do you manage operating expenses for something like that?â Redefining ROI Kaminsky said that when it comes to AI, business leaders risk using an outdated lens to measure return on investment. For companies where AI poses an existential threat, delaying decisions because of ROI may be a death knell. âThe ROI of AI isnât the issue. The ROI of doing nothing is the real issue,â she said. With this in mind, she said, many business leaders at public companies are changing how they talk to their boards about ROI and reconsidering how they categorize those investmentsâblurring the line between operating expense and long-term investment. âTaking a bet on where things are going is better than not doing anything at all,â she said. âThe people who do it best are those that make assumptions as to what could happen and plan around those changes.â A New Talent Model AI has undeniably altered the hiring landscape, triggering companies like PwC to add new job titlesâengineer, data scientistâto the accountants that traditionally made up the bulk of their workforce. âWe donât just hire accountants anymore, because the worldâs changing. We have evolved quickly in this time, and so weâre really refocusing,â she said. More human-led skills that machines canât easily replicateâlike relatability and critical thinkingâare also becoming increasingly important. âWe need people that can talk to a client with empathy and understand what theyâre doing and where theyâre going,â she said. The days of the âyes-man,â it seems, are also numbered, as she stresses the importance of people who can ask questions and challenge human and machine alike. âA U.K. regulator we work with just said, âYou canât blame the AI.â You still need a human lens. We really need people that will challenge us and look at the output to review it and have a dialogue around the review process,â she said. âWe like to be challengedâthose are the type of people weâre looking for.â
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