Welcome to the AI job fair
A few weeks ago, I published new data showing that AI job posts vary significantly across different tech hubs. No one talks more about responsible AI than Seattle, while SF spikes highest on AI hype language. NYC is enterprise central.
This week, I'm analyzing AI jobs through another lens. We're looking at how AI job posts have changed over the last year, and what that tells us about how businesses are evolving their approach to AI.
AI transformation by any other name
Over the last year, I've gotten an increasing number of calls about exec roles in AI transformation. Companies, especially enterprises, are looking for leaders to help them reinvent their operations with AI.
However, when organizations talk about "AI transformation," they mean a lot of different things. Many orgs just mean they will equip their employees with sandboxed versions of ChatGPT. Most are doing more talking about AI than actually building with it. But a few forward-leaning organizations have a legit appetite for ripping apart existing systems and building new ones. This latter group is out in front and their AI roles are compelling.
I've been pitched several "AI transformation" jobs over the last few months. However, I've seen numerous other exec job titles in AI popping up too: AI enablement, AI integration, AI optimization, and more. "AI transformation" still shows up prominently, but the others are growing fast.
Can we back up my personal recruiting anecdata with slightly better and broader anecdata? Let's find out!
Everyone's favorite: A scrappy data set
I'm all about using scrappy data sets to tell directionally interesting stories, and this week is no exception. About a year ago when the recruiting calls picked up, I began snapping 1,000 AI-related job posts every few months (nothing fancy, just the first 1,000 I found on LinkedIn that contained one of several hand-selected AI-related phrases). I had the notion that there might be an interesting story to tell if I could look back at the language evolution a year or two later.
For the sake of this story, we're going to focus on the relative popularity of five kinds of AI jobs over time:
- "AI transformation"
- "AI integration"
- "AI enablement"
- "AI optimization"
- "AI activation"
I picked these five phrases because 1) I've been recruited for roles containing all of them, and 2) I've seen them all in multiple settings.
The roles in the data set are at many organizations in many locations. They represent a range of seniority. In multiple industries, bigger organizations and smaller ones. Some are technical roles, some are ops roles, and many in between.
AI transformation is dead, long live AI transformation
Just kidding, AI transformation is not dead at all. But "AI transformation" is rapidly losing market share in job titles, while titles focusing on more specific aspects of AI adoption are on the rise.
The charts below show the relative market share of the five AI job titles in our data set at three different points: 12 months ago, 6 months ago, and today.
In September 2024, "AI transformation" titles represented 57% of total share among these five job titles. The other titles were more niche. For instance, "AI optimization" titles had an 8% share, and "AI activation" titles had a 2% share.
By March 2025, this has begun to shift. "AI transformation" titles have lost significant share, down to 44% of the total. As you can see in the chart below, the niche titles are on the rise.
Looking at the data from this past month, these trends have not only continued but accelerated. Today, "AI transformation" titles represent just 30% of total share. "AI activation" titles have 12% share, and "AI optimization" titles have grown to 17% share. This is a big shift!
The trend is easiest to see when we plot the respective market share for all five AI titles together in one chart. We are currently seeing a much greater balance across AI job titles in the market than we saw a year ago.
The bottom line: This data is only directional, but I am excited about this trend. A year ago, companies didn't understand AI well enough to define detailed accountabilities under the large umbrella of AI transformation. Everything was labeled generically as "AI transformation."
But these days, organizations are starting to introduce more specific accountabilities within AI transformation projects. "AI optimization" and "AI enablement" clearly refer to distinct kinds of work. A given company might staff people in both of these roles, because they have invested enough in AI to warrant it.
A couple of weeks ago, I outlined three enterprise roles in AI that will be ubiquitous by 2030. The Chief Optimization Officer was one of them. This job post trend data shows how businesses get there.
Kieran
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