It’ll Take Years for AI to Take Your Job…If it Does at All

by Scott Stransky | Dec 22, 2024

How a medical field phenomenon will impact marketers

It takes an average of 17 years for a clinical research finding to reach clinical practice. That means that something discovered in the lab in 2006 is just now making its way into practice at your doctor’s office or the local hospital.

Back in my neuro training days (Russian kettlebells + functional neurology and kinesiology is awesome) we called this the “Filter Effect”. The filter effect is all the layers of high education, medical, and social communities information must filter through before it reaches everyday practitioners.

What does this have to do with business and marketing? AI.

Right now Facebook’s a-fire, Twitter’s a-twitter (or “X” is… xing?), and LinkedIn’s Liking the fact that people are pontificating about which jobs artificial intelligence is going to replace and when.

Almost universally, people believe that marketing — and specifically a group of workers we lovingly called “content writers” — are the likeliest casualties because AI tools can presumably do their job better, faster, and cheaper than they can. But even if that were completely true, the great replacement won’t happen overnight because the filter effect occurs in tech too.

There’s evidence it’s already begun, with some publications and companies already slashing headcount in favor of machine workers. But considering we’ve also been promised other pie-in-the-sky scenarios (i.e. flying cars and the like), you can be forgiven for skepticism.

Yet, the truth lay somewhere in between.

For a few select roles in the content and marketing space (SEO, social media, and ad copy writers for example), the end of their work as they’ve known it is probably nigh. They’ll need to adapt to thrive in the new landscape or die (not literally, please).

But for everyone else, you’re probably safe for several years because, whether you work for a big company or a little one,  it’s going to take a while — probably a long one — for AI to fully impact you negatively.

Don’t believe me? Let’s think through it. Join me in entertaining a few reasons why I’m not terribly concerned about this:

Big enterprise inertia prevents massive change

Big companies are more likely to have the budget and technical manpower to implement AI solutions throughout the organization to replace “expensive” and inefficient humans. But the bigness of the company will pretty much always get in the way.

If you’re a marketer at a big company, you already know instinctively how slow big companies are to change. The default answer for “When do you need this project completed?” is always some version of “yesterday!” or “ASAP!”

Half the tasks on your to-do list weren’t rush items when you came up with them — but they are now because everything in a big enterprise is. so. freakin’. slow.

Think about how long it takes the average corporation to accomplish something as seemingly routine as finalizing a quarterly budget for each department. Or pushing a contract through procurement and legal.

How difficult and time-consuming is it to get a vendor invoice processed and paid or to recruit and onboard a new hire (even if they’ll eventually be replaced by a machine)?

Now, think about how much time, effort, and money it’ll take to completely overhaul the company’s marketing engine without negatively impacting the sales and customer success teams? And how much planning must be done to avoid a negative impact on  customers themselves, many of whom are high-profile global brands with massive influence over the company’s reputation and ability to do business?

How much slower will things be when Finance has to rework all their P&L models, factoring in new licensing costs for AI platforms? Or redo severance packages for laid-off workers, and other intricacies I don’t pretend to understand.

So.

Does that sound like something likely to happen in the next year? Or the next 3 or 5 years, especially when AI platforms in their current state still demand human intervention to be reasonably valuable? Nah.

Small business budgets mean change has to wait

At the other end of the spectrum, smaller companies are more likely to adopt AI tools if it means they can work faster and more efficiently. That’s especially the case when it comes to generative AI solutions for content creation.

Smaller orgs have to be more agile, adaptive, and take more risks than their deeper-pocketed big enterprise counterparts.

The problem for them is that they usually don’t have the resources to pull the trigger on solutions they need or implement them in an intelligent and strategic way.

If you’re a marketer in a small company, you already experience this daily. You might be a team of one (or maybe two or 3). Think about how difficult it is to get budget for essential tools like a premium CRM, advanced analytics and retargeting platforms, or a buyer intelligence solution.

How hard is it to get budget for additional headcount or even enough funds to get a moderately priced freelancer to help create the content for your big quarterly campaign push? Money in smaller enterprises is unsurprisingly tight. Every team — sales, marketing, HR, CX…whomever — gets limited funds to do their jobs to the best of their ability.

The bosses who’ve eagerly rubber-stamped generative AI purchases in hopes of unburdening their business of oppressive salaries and overhead are already regretting it. Over-hyped AI solutions add a few more zeros to the monthly expense report but little incremental value over their human competitors.

Ultimately, they still require a human to run them and make sure whatever content they do produce doesn’t go wildly off the rails or make up a bunch of nonsense couched as great writing.

A respite and reprieve for everyone

The generative AI tools we have available now are certainly not the ones we’ll have a year from now. Or five years from now. There’s really no way to predict what AI will do or be capable of doing in that time.

But….even if it’s amazing. Even if it stops hallucinating, starts mimicking styles and tones, and can reasonably compile a compelling version of the 5, 10, or 20 asset formats marketers use most, it’s still safe to assume that those innovations won’t become so normative that they replace human workers. There are simply too many levels and layers to filter through first.

You’re safe. For now.