“Automation may be a good thing, but don’t forget that it began with Frankenstein.” – Anonymous
Does Leadership scale in the world of AI?
The more AI you have the less leadership you need.
This might not be obvious, but it is self-evident. Management is about orchestrating the collection of skills the organization needs to get work out the door. Leadership is about getting people to follow the leader’s lead.
So when it comes to keeping a joint running, management is essential regardless of how little or much automation management brings to bear. Leadership is a management capability that’s only essential in proportion to the number of human beings management brings to bear. It’s irrelevant to automation because no matter how skilled IT becomes at Turning’s “Imitation Game,” none of the “eight tasks of leadership” will improve how well your AIs perform.
Automation doesn’t respond to leadership, on top of which it scales better.
That’s why, in the entertainment industry, the most popular actors and directors are paid so much: the cast and crew of a single movie replace dozens or even hundreds of actors who would otherwise read from the same script and roles but on different stages around the world.
Not that they’d be delivering identical performances, as anyone knows who has watched Joss Whedon’s Much Ado About Nothing.
Even when the task is as familiar as performing Shakespeare, when different human beings take on the tasks of delivering a movie, changing even one performer results in a new and different work.
With the exception of the entertainment industry, though, and perhaps professional athletics, few businesses are built on a model in which each process output and generated product is supposed to be unique.
In a typical business, where uniqueness isn’t a virtue, a single automaton might displace a large number of human beings who have been responsible for executing the same task. Industrial robots and customer service chatbots are examples.
Other times, an automaton displaces a single human performer, as might be the case for a human researcher whose employer decides to place its trust in Copilot or Gemini instead of a human specialist.
Regardless, a little-explored subject as businesses bring in AI technology is its impact on the executive skillset. That’s a risky oversight, because in traditional businesses the best executives are those with exemplary leadership skills, but in AI-enabled enterprises leadership matters little – it’s the managerial skillset that delivers the goods.
Usually, when the subject turns to business processes it centers on the major process design methodologies – lean, six sigma, lean/six sigma, the theory of constraints, and re-engineering. And to be sure, these methodologies provide useful tools for designing efficient processes.
What sometimes gets lost in the shuffle is process management – the day-to-day slog of making sure management’s elegant new processes are doing what they’re supposed to do.
This will entail more than defining metrics and crafting the systems needed to collect, compute, and review them.
But that will be a good start.