AI

Don’t Tell People to “Be AI-Ready.” Look at the Work First.

There is a familiar pattern playing out in nearly every organization right now. Leadership buys the AI tools, announces the AI strategy, and then issues the directive: everyone needs to be AI-ready. I liken this to handing out a box full of hammers and just telling everyone to pound on anything that might be a nail. It is the same move I have complained about before with innovation — telling people to “be more innovative” without giving them a process, or, as I once put it, refusing to invest in accounting while telling employees to be more accountable. We are doing it again, only the stakes are higher and the anxiety is louder.

Here is the uncomfortable truth: the risk to your workforce is not AI. The risk is reacting to AI without ever understanding the actual work your people do. When organizations skip that step, the predictable results follow — skill obsolescence, quiet resistance to the very tools you just paid for, fear-based disengagement, a dip in productivity right when you need it least, attrition of the people you most wanted to keep, and a disappointing return on a very expensive investment. None of those are AI problems. They are omission problems; they are leadership problems.

So before we hand out the box of AI hammers and start telling everyone to start “banging” on everything they see, let’s do the thing almost no one wants to do. Let’s look at the work.

Start With Tasks, Not Tools

A “job” is a convenient label, but it is not the unit of analysis that matters. Jobs are bundles of tasks, and AI does not consume jobs whole—it acts on tasks. That distinction changes everything about how you plan.

The honest starting point is an old, unglamorous discipline: job-task analysis. Have the people who actually do the work inventory their tasks and estimate where their time goes. Then interrogate each task along a couple of dimensions that turn out to matter enormously in an AI context:

If you spend any time researching the best tools to classify tasks in relation to AI incursion you will generally see two dimensions: “Routine” versus “Non-Routine”; and “Operational” versus “Cognitive” or some similar construct that breaks down into:

  • How scripted is it? Some tasks follow a procedure that rarely varies. Others require judgment, adaptation, and reasoning in the moment; versus,
  • How human is it? Does the task need human oversight before anything goes out the door? Does it depend on empathy, trust, or persuasion? What are the consequences if it goes wrong?

What you may not see often is adding another dimension of what we frequently call “criticality”; i.e., how important is it that the task be done correctly the first time, every time? Maybe, one day, we will have the confidence level that AI solutions are infallible and 100% trustworthy; until then, it is a good idea to use criticality as a way to classify risk.

When you graph the results you get a fair idea of which tasks are best suited for AI (Operational and Routine), which tasks may be less suited (Cognitive and Non-Routine), and which tasks fall somewhere between. When you add criticality, and time studies, you have a clear view of the tasks that exist today as well as the potential ROI and risks of automating these tasks.

Notice that none of this requires you to predict the future of AI. It requires you to understand the present of the work. That is a far more tractable problem, and it is the foundation everything else sits on.

Every Task Has One of Four Futures

Once you can see the work at the task level, you can ask the question everyone is actually afraid of — but ask it precisely. For each task, what is AI most likely to do?

  1. Automate it. The task largely goes away or runs with minimal human involvement.
  2. Augment it. A human still owns the task, but does it faster, better, or at greater scale with AI assistance.
  3. Leave it human-owned. Judgment, trust, accountability, and consequence keep the task firmly with a person.
  4. Make it more important. This is the category people forget, and it may be the most strategically interesting. AI raises the value of certain human work — the oversight, the relationship, the critical judgment — precisely because so much else around it is being automated.

That fourth category is the antidote to fear, because it re-frames the whole conversation. AI is not just subtracting from the role; it is reshaping it, and parts of it are about to matter more. People can move toward that future. They cannot move toward a vague mandate to “be ready.” Involving the people who do these tasks to understand where they fall, and sharing the results with them can go a long way to overcoming fear and resistance.

Three Dimensions of “Ready”

When you aggregate those task ratings back up, capability sorts itself into three buckets worth developing deliberately:

  • Hard skills — the technical capabilities that come out of the operational, more scripted tasks.
  • Soft skills — the interpersonal and cognitive capabilities that cluster around the non-routine, human-owned work.
  • AI literacy — the emerging baseline, drawn from wherever AI tooling is already showing up in the work.

This is where most “AI training” goes wrong. It treats AI literacy as the only skill that matters and bolts a tool tutorial onto everyone’s calendar. But if the susceptibility analysis tells you a role’s future value is concentrated in human-owned judgment and the relationships around it, then the highest-leverage up-skilling might be in the soft-skill column, not the prompt-engineering one.

Readiness Is a Human State, Not a Technical One

Here is the part the technologists tend to miss, and the part my own work on expertise keeps dragging me back to: you cannot up-skill a workforce that is frightened, demoralized, or quietly convinced you are training their replacement for them.

So before any intervention, take a baseline of the human reality, not just the skill gap. What is people’s actual confidence? Their learning agility? Their sense of preparedness? Where are the human-premium skills already strong? And — say it plainly — where are the resistance and fear indicators? Measure that the way you would measure anything you intend to manage. Pair the self-assessment with open-ended questions and a few real conversations, because the numbers will tell you what and the words will tell you why.

If that sounds like an assessment problem, it is — and I would argue it should be treated with the same seriousness as any psychometric instrument. Done casually, you get vibes. Done with attention to what you are actually measuring, you get a defensible map of where your people are and what they need. That is the difference between a program and a slideshow.

Final Thoughts

The reflex of the moment is to treat AI as something that happens to a workforce. The better framing is that AI is something you can lead a workforce into — but only if you do the work of understanding the work. Analyze the tasks. Sort their futures honestly, including the ones that are about to matter more. Develop the right mix of hard skill, soft skill, and literacy. And take the human temperature before you prescribe anything.

AI does not reduce the need to understand how work gets done and how people develop capability. It raises it. The organizations that figure this out will not be the ones with the most tools, they will be the ones who continue to thrive.

If this resonated, I write regularly about strategy, innovation, assessment, and the future of work at The Versatilist Perspective.

Fear Not the AI Overlords! Humans Have Intrinsic Value.

There is significant hype about Artificial Intelligence (AI) and its potential to take over many jobs thought safe from Automation.  It has been suggested AI could replace accountants, lawyers, doctors, and even general management activities.  While it is true that advances in AI will certainly change many jobs, as so often happens, the fear is exaggerated.  First, there is no evidence to support the notion automation has ever eliminated more jobs than it has created.  Second, and more importantly, humans have intrinsic value that is unlikely to ever be replicated or replaced.

The Fear of Losing Jobs

Before anyone gets too excited, a recent Wall Street Journal article highlights the facts of mass automation in the past.  Technology from the cotton gin through AI has always eliminated some jobs, but historically it has also created far more and better paying jobs as a result.  Sure surrey drivers were put out of work with the advent of the automobile, but the auto industry created millions of jobs supporting the US GDP for decades.  AI is simply the latest in a long-line of technological advances feared to lead to the end of our society.  It has never happened before and is unlikely to happen anytime soon.  It is true that some jobs may cease to exist, but this will be accompanied by a growth of new jobs supporting the AI industry.  Even more remarkable will be the new jobs that don’t even exist today.

A recent report from the Institute for the Future estimates 85% of the jobs today’s students will perform by the year 2030 haven’t yet been invented.  This is a difficult prospect for today’s workers to imagine, but it is not without precedent.  Student’s graduating high school in the 1990’s could not have imagined careers working in web design, social media, or – for that matter — artificial intelligence, machine learning, and big data.  Another recent article from MIT Sloan Management Review hints at some of the new jobs AI technology may create.

On top of all of that, it is unlikely many of the jobs being predicted to succumb to AI will actually go away.  It is much more likely they will be augmented and changed than disappear entirely.  And the reason is simple: humans have innate value in performing jobs in a human society.

Humans Have Intrinsic Value

Although AI is redefining what is considered automata by allowing more variation in performance, it is still not human.  Human beings are defined by the irrational and emotional more than they are by cold, calculated precision.  While this may seem to be a negative aspect of humans, it is also the source of the innovation, creativity, and passion that simply cannot be replicated.  Just for sake of argument, let’s examine just one of the jobs proposed to be replaced in the future by AI: management.

Business management is an oft misunderstood discipline, which does not benefit from the HR moniker “people manager”.  You manage objects, but you lead people.  Objects are managed to gain efficiency, but they have finite limitations. You cannot encourage a robot to be more productive.  You cannot ignite passion in your inventory tracking software to go above and beyond.  Yet human beings have nearly limitless capability to “reach for a goal”, “put in extra effort”, or “embrace shared visions”.  While this can also work to reduce human performance (as discussed in this article from MIT Sloan Management Review), this is critical distinction when looking at the effects of AI in particular.

Management, in its truest sense, is absolutely ripe for AI replacement.  Eliminating the idiosyncracies of human performance can have significant value to organizations.  AI is simply better able to gather, process, and act on vast amounts of data where human input is less vital (although not necessarily irrelevant).  By offloading these tedious and taxing responsibilities, while also improving their performance, humans can spend more time doing the things where they have intrinsic, and irreplaceable value (See article from Swiss Cognitive).

Leadership, on the other hand, will no longer need to take backseat to management.  By focusing on leadership, organizations will not only gain the advantages of AI-based management efficiency, but also from the benefits of stronger human performance.  In essence, organizational leaders will be able to offload the tasks they don’t do very well anyway, and focus on the actions that lead to truly superior performance.

Fear Not!!

While the example above focuses on my area of expertise, the same can be said for many other jobs ripe for AI augmentation.  AI, like the cotton gin and automobile before it, are tools that will augment and improve the way we work.  Yes, some jobs may be significantly reduced or eliminated; however, they will be replaced by newer and better jobs.  The jobs getting augmented by AI will simply change, putting more focus on the human aspect.  It is not the end of the world.