How ready are we to harness AI, be it in the cloud or elsewhere? Pluralsight, the technology workforce development company, has released new research on the topic, the Pluralsight AI Skills Report: The Gap Between AI Investments and Worker Readiness, where we can find some answers.
Full disclosure: I have many personal friends at Pluralsight, but that did not drive me to write this post, and they were not informed I was doing so. I don’t work for or with Pluralsight, in case you are wondering.
Workers are not prepared to leverage AI
The research covers the AI landscape and its impact on talent based on a survey of 1,200 decision-makers and practitioners in technology, IT, cloud, cybersecurity, and related fields.
Pluralsight found a gap between the pace of AI investments occurring now and the readiness of the workforce to implement and use AI. According to the study, 90% of executives admit to not completely understanding their teams’ AI skills and proficiencies. This means they have not done a skills gap analysis. That translates into a fundamental disconnect between organizational AI strategies and the skill sets in-house.
Companies need to start prioritizing a few things:
- Take a more proactive role in developing the skills. Although this study focuses on AI, you can replace AI with cloud or cloud-based AI. The principle is the same.
- Bridge the gap between AI investments, money already budgeted for 2024, and the readiness of employees to leverage these technologies.
Pluralsight is not as pessimistic as I am. I predict that failure will likely occur, including growing technical debt when enterprises are bathing in technical debt already. Too many organizations are hiring so-called AI experts who make a good number of poor decisions. By the time companies discover this, it’s too late.
We saw something similar happen with initial cloud efforts. However, AI issues will come quicker and be 10 times as harmful to the business. Again, as I stated in my 2024 predictions, we need to focus on fixing this, and we need to do so through innovative approaches and an understanding of the talent supply chain.
AI investments at risk
Of course, some overlook this as just another challenge that can be overcome. Perhaps. The core difference is that we’re not implementing a technology transformation that will save the business 20% in operational costs and shift from capex to opex. Generative AI systems could make or break many businesses, and getting this right the first time is imperative.
The Pluralsight report outlines the broader implications for organizational success with AI and other digital transformation technologies. Failure to close the AI skills gap could impede companies’ ability to achieve returns on their AI investments and lose the opportunity to capitalize on the competitive advantages offered by AI-driven innovations.
This could kill your business. That’s bad.
The talent supply chain
This is not one of those things you wait for the market to fix. Many hiring managers are sitting with their arms folded, complaining about how bad the colleges and universities are at turning out graduates with AI skills. They might as well give up now. Educational institutions move far too slowly and aren’t the best way of learning these days.
It’s up to you to fix the talent supply chain. Work with existing employees to find out who is willing and able to become an AI expert. Figure out what courses and on-the-job training they will need. This does not mean sending people back to college, but providing innovative and dynamic training that is laser-focused on the what, whys, and how of AI and the cloud—especially the how, which is largely missing today.
I don’t want people who can explain generative AI to me. I want someone who understands how it can be applied to the specific business to ensure its ultimate success. Not much to ask for.
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