Consider this: in the US, nearly 20% of workers hired today have job titles that did not exist 25 years ago. They will also hold twice as many jobs in their life, or more (the current average is 20, vs. 11 in 2010, per stats from the World Economic Forum).
Mobility is higher, tenure is lower, and the positions are changing fast. And AI is increasingly playing a role in all of this.
I sometimes feel like that chicken from the folk tale, saying the future is coming, the future is coming, upskill or reskill, stay informed, think about the future of work with AI and how you fit into this future now, before it’s too late…
But today I’m not talking about the future.
I want to look at how AI is changing jobs right now: removing positions, creating others, and transforming still more.
We’re all witnessing a significant change to what jobs are, how they’re done, and where they’re done.
The AI Job Disruption: Create and Eliminate
We posted on PTP recently about the Salesforce shift—they are laying off 1,000 employees per Bloomberg while hiring 2,000 more as salespeople for their AI products.
For a company well known for its internal development and mobility, this is noteworthy—even as those facing layoffs are encouraged to apply for other positions (and, as Newsweek notes in its coverage, there are 800 open positions listed on the website as of a week ago).
This is, in one place, an example of what could become a growing trend: AI replacing human jobs in some sectors while triggering demand in others.
In tech, as Victor Janulaitis, chief executive at Janco Associates, tells the Wall Street Journal’s Belle Lin:
“Jobs are being eliminated within the IT function which are routine and mundane, such as reporting, clerical administration.”
And as AI continues to improve, more positions that are repeatable in consistent ways are going first.
There are less programming job listings, for example, than there were a year ago, though the exact impact is harder to measure. Demand for skilled roles remains strong, and much of the need is shifting, a movement from one skillset to another as AI increasingly comes online.
Data engineers, analytics, workers with cloud expertise and cybersecurity experience remain in demand.
And this of course isn’t unique to tech. While the need for talented salespeople isn’t going anywhere soon, customer service is an area where AI use is flourishing. Among CEOs the world over there’s consensus that large call centers, positions often prone to worker burnout (where repetition, consistency, and patience are key), will be entirely replaced by AI automation within years.
In the recruiting industry, again, it’s things that can be repeated consistently—pre-screening, onboarding, scheduling, clerical tasks, confirmation calls—that are being widely automated.
While research is an area of surging development (OpenAI’s Deep Research was released at the start of February), it still requires human interpretation and verification. Soon, however, AI will be playing the role of academic research assistant for all of us.
In marketing, routine copy and initial design drafts can already be created by AI. But the work still requires a human touch, making creatives who are capable of working with AI more important than ever.
In this way, many of layoffs we’re seeing around AI include cases of workers who are struggling to adapt to co-intelligence, rather than cases of people no longer being needed at the organization.
Skills, AI and Offshore Hiring
We ran a piece in The PTP Report recently about how AI benefits are far more significant for workers with less experience, or who are less skilled in certain areas.
A study covered in the Harvard Business Review looked at this in terms of sourcing, where workers from the US and South Africa were given similar tasks and, in a randomized fashion, asked to complete them with and without the assistance of AI.
Unsurprisingly, AI assistance boosted both groups significantly. Studies by MIT, Stanford, Harvard, and various firms all found that AI assistance improved many common consulting tasks by give-or-take 40% in terms of quality. Consistently, those working on computer-based tasks can do some 10% more work, 20% more efficiently than before.
Research also consistently proves that those tested with less skill beforehand gain the most from AI.
Now some of this could be due to reluctance on the part of more experienced workers to trust the AI system, as has been seen with doctors using AI system for diagnosis (where the systems alone actually outperformed them), and also in low-risk areas like sports predictions, where some AI systems (such as Unanimous’s Thinkscape) more accurately predicted not just the Super Bowl winner but also the reasons behind the results. (The Kansas City Chiefs were Vegas favorites to win, as well as being unanimously picked by the ESPN pregame team, for example.)
Obviously this cuts both ways, as workers without experience may be far less likely to catch hallucinations, but the study referenced above found AI assistance improved the test examples from the South African workers to the extent that their value became relatively greater than the Americans also using AI (with a pay rate 50% higher, as per market value for the study).
The AI assistance also made it impossible for human evaluators to consistently tell the work from the two groups apart. (Without AI they could identify sourcing in 6/10 cases.)
Already, we are seeing this impact on workplace sourcing. If you’re already using remote workers onshore, and can pay less and receive comparable quality work with the assistance of AI offshore, what would hold businesses back?
Perhaps time-zones, regulations, data security, and cultural differences, but some of these issues can be also resolved by merging AI and nearshore talent sourcing.
And yes, clearly there are positions that are necessary onshore, and onsite. But my point here is that this equation is being substantially modified by AI.
Being Ready for AI Automation and Workforce Changes
AI experience and comfort is already essential for many tech roles, and workers are picking up on this quickly.
On LinkedIn, for example, 177% more people list AI literacy skills now as they did even in 2023. The World Economic Forum found people twice as ready to pick up the necessary AI skills for the future.
But is that enough?
Ironically, human skills, or so-called soft skills, are also increasing in importance (+20% since 2018 per the WEF). The need for these is on the rise as organizations come to terms with the many things that AI cannot do well.
Skillsets are also broadening, with workers globally having a 40% broader selection of skills than in 2018. Among these, AI proficiency is of course essential, but so is creativity, problem solving, adaptability, communication, and critical thinking.
Problems with the Hire and Fire Approach
As I mentioned above, Salesforce is well respected for their internal development, and even in this case they are allowing those laid off to attempt to move into the open positions. It’s quite possible these layoffs included workers who could not be easily transitioned.
Still, I expect many companies will follow a less forgiving model in the aim of achieving rapid restructuring.
With the speed of change and the growing skills gaps, this hire-and-fire-at-once approach is likely to become far more common.
As Steve Cadigan, LinkedIn’s former head of HR and a workplace consultant, explained to Newsweek’s Aman Kidwai:
“I attribute [this] to the increasing need to change skill sets and companies’ inability to build these skills as fast as they need them.”
“We are going to continue to see more of this… reductions while actively recruiting new or different skills.”
But the drawbacks to this approach are many, starting with the loss of years of specific workplace experience not easily replaced. Often the nuance of what is being lost in such a swap goes unnoticed until later.
It also may generate unnecessarily repeated costs in onboarding and termination, training, and getting up to speed, all with the risks of mishires (and misfires) running in parallel. It can also be harmful to general retention and company morale.
Obviously, layoffs are a part of business, and many implementing new AI solutions will be hiring AI/ML talent out of necessity, but training and smart transitions are often a more productive means of achieving similar ends.
Conclusion: The Future is Arriving Now
At PTP, we provide technical recruiting the world over, and I’m witnessing this transition now from multiple angles.
We’re already seeing widespread AI-driven job transformation, changing what’s getting done, how it’s done, and even where it’s done. And you don’t need me to tell you that this is only going to increase in scale over the years to come.
And regardless of what’s happening in your business, I hope you consider us for your own talent needs, whether it’s short or long term, onshore, offshore, or nearshore.
References
AI is shifting the workplace skillset. But human skills still count, World Economic Forum
Salesforce Laying Off 1,000 Employees in AI-Driven Restructuring, Newsweek
IT Unemployment Rises to 5.7% as AI Hits Tech Jobs, The Wall Street Journal
