If it hasn’t happened to you yet, it will soon: you’re going to get a memo or briefing from someone on your team that is suspiciously well-written, but also just a little bit off. It’s going to have impeccable grammar and spelling, and it’s going to come with the boilerplate format and impersonal, formal voice and tone that business managers love to conflate with professionalism. It’s going to be persuasive but not memorable, and if it comes with any citations, you may have trouble finding those sources.
Congratulations—you’ve just had your first brush with the output of a Large Language Model (LLM), or what is popularly referred to today as Artificial Intelligence… AI.
It’s early days yet for machines that think they can think, and opinions are mixed on whether this is a good or a bad thing. In May of 2023, more than 350 experts who are actively involved in the development of the technology signed a letter warning that it could lead to extinction level events for humanity.
On the other hand, they are all continuing to work on it, so apparently they feel it’s worth that enormous risk.
Still others warn of less dramatic, yet more insidious dangers emerging from the technology, such as the risk of codifying systemic discrimination, environmental damage, and widespread and hard-to-detect disinformation.
One thing everyone can agree on is that with the new technology will come new disruption. And it is going to fall to leaders to manage that disruption, avoid the pitfalls, and, yes, even lead their new robot teams to greatness.
AI is a Somewhat Generous Term for Describing the LLM Breakthrough That’s Getting So Much Attention Lately
First, it’s important to note that the term AI (Artificial Intelligence), like the term Cloud Computing before it, has essentially become a marketing term of art rather than any specific scientific description of the technologies involved.
And nothing that has come to light in recent months, despite all the fuss, comes close to approaching the science fiction versions of intelligent machines that most people imagine when they hear the term. The technologies that are creating the biggest waves right now are basically glorified versions of auto-complete… a technology famous for how ducking inaccurate it can be.
But that’s not to say they aren’t marvels of a sort in their own right. For an algorithm to be able to effectively predict long sequences of words that a human might write out is an impressive accomplishment. And both LLMs and less well-known AI technologies are certainly going to have profound impacts in every sector in the coming years, well maybe months.
The Biggest Changes from AI Will Be Ones You Don’t See Coming
The specific technology behind the most talked-about kinds of AI today is called machine learning. It’s essentially a process of throwing a huge volume of data at an algorithm, which then optimizes itself based on nudges from the programmers to accomplish some goal: recognizing a dog or pedestrian in a mess of pixels, predicting the most likely next words in a sentence, forecasting seasonal sales based on historic data.
But there are other technologies and larger goals on the horizon. While most AI tools today are very specific in function and ability—dealing only with certain types of data and limited output—the holy grail of the field is Artificial General Intelligence (AGI). That’s a machine intelligence that displays the full range of reasoning, analytic, and developmental capability that a human can.
Should that goal be realized—and it’s a big if, you might actually have to start thinking about the reality of leading a team of bots.
Until then, leaders will have to deal with more prosaic but still important challenges rising from AI.
The Full Range of Impacts from AI in Business and Society Will Be Both Profound and Mundane
What sort of impacts will industry leaders have to deal with? In some ways, that’s the million-dollar question right now. Imaginations are active, but there have been few practical changes in most businesses.
Perhaps the greatest risks in AI technologies at this stage will come from misunderstanding them. A lawyer who relied on ChatGPT to pen a brief for him in a recent personal injury case found out the hard way that autocomplete doesn’t mean autocorrect when opposing counsel discovered that none of the case citations in the piece actually existed. They just sounded good.
Ultimately, however, AI of various flavors will work its way into the daily activities of your organization. And it’s going to change the nature of organizational leadership at the most fundamental levels.
Machine Learning Hits Leaders Where It Hurts, Right in the Analytics
That’s because the strengths of many forms of AI overlap extensively with some of the traditional domains of leadership:
Any leader who is used to being the smartest, most authoritative person in the room is about to become second fiddle to an algorithm.
Of course, someone still needs to point that algorithm in the right direction and feed it the right data. Much of the work of a leader is in communicating their intent and instructions to their staff accurately. This is hard enough with human beings. With the current iteration of AI, it’s literally impossible.
That’s because, as effective as their output can be at mimicking human comprehension, there’s really no mechanism for an AI to understand you. They don’t think in any recognizable sense. Your instructions are a kind of code, except unlike conventional computer code, the model has options for interpreting it statistically.
That’s not going to be a recipe for clarity or consistency. Instead, you and your staff will have to become machine whisperers, figuring out how to massage and manipulate AI inputs to tune-in their function.
Managing Your Human Staff Will Become Even More Difficult
Speaking of staff, you’re probably going to have fewer of them than you do today. And the rapid evolution of AI may put many organizations into something like a perpetual restructuring mode.
Many of your leadership challenges stemming from AI in the near-term won’t just stem from shifts in your own position that come with it. They will also emerge in how your staff relate to and make use of it.
Which comes back to that memo that landed on your desk. Your first big leadership test with AI will be determining when and where it should be used in your organization.
This will often come down to the classic leadership challenge of aligning the individual goals and aspirations of your staff with those of the organization as a whole. The team-member who used AI to write that memo probably used it because they perceived an easier way to do their job. But for you, the question will be how to reward their initiative and insight while ensuring that you are getting accurate data on your desk… while finding ways to reassure them that the algorithm itself won’t be interviewing for their job.
How Strong Organizational Leaders Benefit from AI and Address the Challenges
If you have been following and embracing the tenets of organizational leadership in your career, you have already spotted the gap in AI capabilities. While the technology may be tailored to the management role of absorbing large amounts of data and quickly distilling salient points from it, it’s a complete dud when it comes to the soft skills of leadership.
Organizational leadership itself has emerged as a high-priority discipline in the past few decades exactly because research has revealed that it’s those soft skills that make the biggest difference in effective leadership. Meta-analysis of leadership studies conducted over the past decades has shown that raw intelligence, the kind of cognitive stuff that AI excels at, is far less important in leadership than interpersonal skills and relationship building.
So, while AI may well take over significant parts of leadership roles as an impartial, all-seeing decision-making machine, it’s nowhere close to filling the shoes of an organizational leader.
Using Education as the Big Ticket to Develop Leadership Skills for an AI-Infused World
Still, you will have to shift your own skills to increasingly emphasize the gaps left by AI. And there’s no better way to do that than through an organizational leadership degree program.
Although the basic nature of OL ensures you will graduate with a good set of tools for handling any challenge, including AI, there are a few specific areas that managers of the future will want to work on as they pursue a degree:
Breadth of Knowledge
Some ML algorithms are very good at drawing in data from disparate sources and coming up with innovative conclusions. But in general, AI today is effectively a one-note instrument, incapable of playing tunes outside its area of expertise. Good organizational leaders will focus less on depth of knowledge in their industry and cultivate a broad range of knowledge to complement AI competencies.
High conceptual level of AI operation and limitations
A major limitation in AI use today stems from misconceptions of how it operates. Leaders will have to be the people in any institution with the ability to draw lines around what advantages AI offers and what stumbling blocks it introduces.
We’ve seen how quickly AI can train itself to perform new tasks. Since that capability will only accelerate, leaders will have to become more adaptable than ever to both take advantage of AI abilities and protect their organization against new AI threats.
Finally, doubling or tripling down on the human factor is the only sensible response to introducing AI to the workforce. What they are missing in empathy, care, and attention, leaders must make up for.
While these points are likely to become increasingly emphasized in all kinds of organizational leadership programs in the coming years, there are a few areas that are likely to dive into them already. An organizational leadership degree with a focus in virtual organization leadership skills is one.
But almost any degree in the field of organizational leadership will put you ahead of most executives today. And when the real robots come around, you’ll be ready to manage them, too.