How long should you wait? Image by valentinsimon0 from Pixabay

Hiring data says “most firms not building AI-development teams”

With few exceptions, when it comes to significant, strategic AI investments, enterprises are waiting for the “IT bigs” to do it for them by enhancing their portfolios with new, AI-based capabilities. Job posting data speaks volumes. Listen to the data.

IT bigs

This category includes Alphabet (Google), Alibaba, Amazon, IBM, Facebook, Microsoft, Nvidia, Oracle, Salesforce, and SAP. There are more but not many more than a dozen. The “bigs” are investing heavily in Research, Development, Engineering, Infrastructure, Customer Support, and Marketing AI technologies.

Figure 1 was drawn from 93,237,194 internet job postings organized by industry

AI Job Postings By Industry
Disproportionate demand across industries

Source: Artificial Intelligence in Health Care? Evidence from Online Job Postings, Goldfarb, et al. AEA Papers and Proceedings, American Economic Association, vol. 110, pages 400-404, May 2020.  Burning Glass Technologies provided the raw data, which was based on over 40,000 online job boards and company websites. Industry classification via two-digit NAICS code.

Where is the AI hiring demand heaviest?

At the top of the chart, you can see the information industries which include non-Internet publishing; Motion Picture and Sound Recording; non-Internet broadcasting; telecommunications; data processing; hosting and related services; and other information services. In practice, the Internet and IT are eating the information industries, so you might as well assume that the bulk of the first row in the chart is the Internet and IT firms.

Immediately below, there are consulting firms. They are selling, among other things, AI expertise to help enterprises exploit custom AI-based solutions. (This broad services category includes legal services; accounting; architectural and engineering services; specialized design services; computer systems design and related services; management, scientific and technical consulting; scientific R&D; Advertising, PR and similar; and other.)

So, no surprise, the top bar is IT and Internet, and the second bar is services that make a lot of IT and the Internet operate and evolve.

The third heaviest AI-hiring industry is FSI – the financial services industries, which include brokerages, banks of all kinds and insurance. FSI tends to spend more on technology than most other (civilian) industries to differentiate their financial products, maximize their margins, and delight the customers with often momentary advantages over their competition.

That sounds like a significant endorsement for investing in building bespoke AI-based solutions. Not so fast! What about the rest of the chart? There is far less enthusiasm for building an internal army of AI experts or building bespoke AI-based solutions.

If not building, what are most entities doing?

They’re waiting for viable, AI-enhanced solutions from mainstream vendors. Longer-term, they’ll sample solutions based on new application categories enabled by AI and evaluate if they can justify making the leap away from existing suppliers.

AI-enhanced solutions have already emerged from “the bigs” generalists and second and third-tier specialists. The AI-enhancement quotient should continue to rise for the next several years as today’s AI research filters into existing products.

New, AI-enabled application categories lie further out.

What should you do?

There can be tremendous value in solutions that exploit the last three decades’ advances in AI technologies.

However, more often than not, most firms would likely be better served by waiting for viable AI-enhanced solutions from mainstream vendors and, longer-term, solutions based on new application categories enabled by AI.

Monitor how others in your industry and adjacent industries are delivering new business outcomes and transforming their businesses using new business models and new technologies. Learn from their successes and failures. Business transformation doesn’t require, in many cases, the newest technology but it does require novelty in approach and thinking, and a willingness to change how your enterprise operates.

Alternative hypothesis

Underlying demand may be constant across industries, but firms in many industries just cannot afford to compete for this rare talent. They’re forced to wait for AI-enhanced solutions from mainstream vendors.

What with the hype flowing about AI, a ‘buyers’ panic’ most assuredly has taken place. The ‘buyers’ panic’ pursuing the limited available talent has driven up the cost of building out an AI-development team, dissuading all but the richest few from heading in that direction.

In any case, the world is not moving aggressively towards building their own AI solutions.


Continued investment in using AI technologies to improve executive and line decision making — sometimes referred to as AI for BI or AI/Analytics — should be going on and growing now. That’s a separate category that, admittedly, overlaps with AI-enhanced solutions and new AI-enabled applications.

Where do you stand? How much have you invested in building out an AI-development organization? How does that compare to your overall development investment? Are you waiting for others to build solutions for you to buy?


The views and opinions in this analysis are my own and do not represent positions or opinions of The Analyst Syndicate. Read more on the Disclosure Policy.

Leave a Reply