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Could AI replace your chief executive officer?

Certainly it could easily figure out arguments to justify high remuneration for doing the work. And some of the chief responsibilities of a CEO – looking into the future, synthesis, calculating odds for making decisions – are not beyond AI’s scope.

Consultant Dan Schawbel’s recent Workplace Intelligence survey of more than 500 CEOs found nearly nine out of 10 say at least “a little” of their job could be automated by AI. McKinsey & Co. research six years ago, before the current AI frenzy, estimated that around 25 per cent of a CEO’s time is spent on tasks that AI could replicate.

Replacing CEOs with machines is, of course, provocative. The real issue is support. Mr. Schawbel’s survey found 91 per cent of executives would like AI to support them and they are already moving in that direction. The same applies, of course, throughout the organization. And that support’s impact can be powerful.

A group of social scientists worked with Boston Consulting Group to test AI in its offices. “For 18 different tasks selected to be realistic samples of the kinds of work done at an elite consulting company, consultants using ChatGPT-4 outperformed those who did not, by a lot. On every dimension. Every way we measured performance,” Ethan Mollick, a professor at the Wharton School, reports on his blog.

Consultants using AI finished 12.2 per cent more tasks on average, completed tasks 25.1 per cent more quickly, and produced 40 per cent higher quality results than those without. They were consulting for a fictional shoe company, the work involving creative tasks, analytical challenges, writing and marketing, and persuasiveness.

Mr. Mollick notes the researchers confirmed an effect that is increasingly apparent in other studies of AI: It works as a skill leveller. The consultants who scored the worst when assessed at the start of the experiment had the biggest jump in their performance, 43 per cent, when they used AI. The top consultants also got a boost, but less prominent.

“I do not think enough people are considering what it means when a technology raises all workers to the top tiers of performance. It may be like how it used to matter whether miners were good or bad at digging through rock … until the steam shovel was invented and now differences in digging ability do not matter any more. AI is not quite at that level of change, but skill levelling is going to have a big impact,” he writes.

A recent Bain & Co. report looked at various organizational tasks AI can supercharge. It can minimize the time to formulate new products, while increasing the quality of what is conceived. It can transform worker productivity, democratizing knowledge and technical skills, automating, improving workflow and creating more innovative solutions. Bain suggests it will also boost customer service, through hyperpersonalization, reimagining service experiences and moving to a “pro-active, streamlined agent-led chat,” which to my mind may be fanciful given what we’ve seen so far from big companies.

Mr. Mollick stresses that no one actually knows the full range of capabilities of the most advanced Large Language Models, like GPT-4. “No one really knows the best ways to use them, or the conditions under which they fail. There is no instruction manual. On some tasks AI is immensely powerful and on others it fails completely or subtly. And, unless you use AI a lot, you won’t know which is which,” he writes.

He mentions an important downside: People can go on autopilot when using AI, falling asleep at the wheel and failing to notice AI mistakes. Managers will need to be alert to this possibility.

A team from the analytical firm GAI Insights recommends leaders look at AI through bifocal lenses. Using the top lens you can focus on the long view of big, looming issues, such as accuracy, privacy and bias – as well as impact on knowledge workers and even economywide job losses and societal risks. The bottom lens illuminates the immediate opportunities and threats from AI that firms face today.

Usually that lower lens has been focusing on knowledge work. But their case studies, with more than 3,000 AI practitioners, point to a new category of work, more precise and actionable than knowledge work.

“We call it WINS Work: The places where tasks, functions, possibly your entire company or industry are dependent on the manipulation and interpretation of Words, Images, Numbers, and Sounds (WINS). Heart surgeons and chefs are knowledge workers but not WINS workers. Software programmers, accountants and marketing professionals are WINS workers,” Paul Baier, Jimmy Hexter and John J. Sviokla write in Harvard Business Review.

Leaders must then ask: How much of our cost base is made up of such words, images, numbers and sounds work and how digitized are the inputs for such efforts today? Companies with low digitization and limited such work can stay in the balcony for a while. Industries with a high percentage of costs in such work and that are highly digitized must understand and embrace GenAI immediately.

There is indeed no manual. It’s all discovery. But some of those clues help.


  • Sometimes it’s the constant desire to fix things that keeps breaking them in the first place, observes author Mark Manson.
  • Consultant Diana Peterson-More recommends hiring panels to ensure all candidates are treated fairly: Rather than successive interviews with a variety of those who will work with the new employee, each candidate appears in front of the same hiring panel and is asked the same question in the same rotation. At the conclusion of each interview, the panel rates the candidates.
  • Advertising consultant Roy H. Williams says there are three types of wordplay: Useful, which communicates clearly; ornamental wordplay, where writers splash splendid colours in the mind to produce vivid visions (he tips his hat here to Canadian novelist Robertson Davies); and adspeak, for which there is no place, no purpose and no need. His sample is from Weird Al Yankovic’s song, Mission Statement, which begins: “We must all efficiently operationalize our strategies, invest in world-class technology and leverage our core competencies in order to holistically administrate exceptional synergy.”

Harvey Schachter is a Kingston-based writer specializing in management issues. He, along with Sheelagh Whittaker, former CEO of both EDS Canada and Cancom, are the authors of When Harvey Didn’t Meet Sheelagh: Emails on Leadership.

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