The AI workforce reset is already underway
The AI workforce reset is already underway
Over the past year, a pattern has been emerging across global businesses: teams are getting smaller, but the pile of work isn’t.
Artificial intelligence is changing how organisations operate, and companies are beginning to redesign their workforces around it.
For the past two years, conversations about AI and jobs have sounded the same. Some argue artificial intelligence will replace workers at scale, other insist the fears are overblown and AI is “simply another productivity tool”.
A third perspective is now emerging: Some employers are using AI as a catalyst to trim the fat and restructure their workforce.
Our view? None of these explanations are mutually exclusive. What we’re seeing across industries is likely a combination of all three.
The result is something more structural than a wave of mass layoffs. Instead, we’re at the beginning of a workforce reset shaped by human-AI collaboration.
The signals are already appearing
The last 12 months saw a growing number of companies linking major restructures directly to AI adoption.
Australian logistics software giant, WiseTech Global, recently announced plans to cut 2,000 staff from its global workforce as it integrates AI across its operations and software platforms.
Atlassian also announced approximately 1,600 layoffs in early March as part of an ongoing restructuring tied to AI and operational efficiency.
Globally, similar patterns are emerging. Amazon has cut tens of thousands of roles across multiple rounds of layoffs, while simultaneously investing heavily in AI-driven products and infrastructure.
Other organisations, including Citi, eBay and Meta, have also announced workforce reductions while reallocating investment towards AI and automation.
Individually, these can be seen as cost-cutting decisions but viewed together, they suggest something else:
Organisations are rebalancing their workforces around a new operating model.
As Thomas Mackenzie, Director of Client Services at Scale by Avec, puts it:
“AI isn’t stealing jobs, but it is reshaping them. We’re seeing smarter, leaner teams and a new operating model defined by human and machine collaboration.”
This is simply capital reallocation
Most coverage and public discussion have framed these recent layoffs as a reaction to AI disruption but, in many cases, organisations are making deliberate investment decisions.
When new technologies dramatically increase productivity, companies often rebalance resources to reduce effort in some areas while increase investment elsewhere.
Thomas draws a parallel with financial markets:
“When investors anticipate structural change, they liquidate certain assets and redeploy capital into areas with greater potential. We’re seeing something similar with human capital as organisations adapt to AI.”
In other words, the workforce changes happening today are signs of reallocation.
Capital freed up from traditional workflows is being reinvested into areas such as:
- AI infrastructure
- Data platforms
- Product innovation
- AI-enabled services
And many organisations making cuts today are simultaneously hiring in completely different capability areas.
Where AI is changing work fastest
The early impact of AI on work isn’t evenly distributed, and the roles most affected tend to share similar characteristics:
- High repetition
- Structured workflows
- Process-heavy tasks
- Large operational scale
These are all areas where AI can quickly deliver productivity gains.
Take software engineering.
Historically, large development teams spent significant time writing routine code, testing functionality and maintain systems. Today, generative AI tools can produce and review code at a dramatically faster speed.
This capability is what led WiseTech’s chief executive to state:
“The era of manually writing code as a core act of engineering is over.”
Importantly, this doesn’t wipe the need for engineers but instead changes the nature of their work as productivity tools improve.
Instead of spending most of their time writing code, developers will increasingly focus on:
- System design
- Architecture
- Problem solving
- AI oversight
Another emerging impact is being felt earlier in the talent pipeline.
Early-career roles, particularly graduate and junior positions, are among the first to be affected as AI reduces the need for large numbers of entry-level workers performing repetitive or structured tasks.
Based on Talent placement data, entry-level hiring has declined by 19% in the last two years.
Over time, this creates a structural risk for organisations. If fewer early-career professionals are entering the workforce and developing experience, the pipeline of mid-level and senior talent available in five to ten years may be significantly smaller.
Put simply: if organisations shrink the base of the talent pyramid today, they may struggle to fill the top of it tomorrow.
The new workforce will favour AI-native talent
Organisations are rebuilding around different capabilities and employees who understand how to work effectively with AI systems are becoming significantly more valuable.
Thomas summarises the shift:
“AI may not take your job, but someone who knows how to use it effectively will.”
While this doesn’t mean every worker needs to become an AI engineer, AI literacy is quickly becoming a core professional capability like how digital literacy became essential two decades ago.
People who can design workflows around AI, interpret outputs and combine machine insights with human discernment will increasingly sit at the centre of modern organisations.
Some companies will inevitably overcorrect
Periods of technological change rarely happen smoothly, and history shows that productivity breakthroughs often trigger cycles of over-correction and adjustment.
Some organisations cut too deeply, and others move too slowly but eventually, capability gaps become clear and hiring will rebound.
One emerging example of this dynamic is what some observers are calling the “AI layoff boomerang.”
Swedish fintech Klarna provides one example. After aggressively promoting AI-driven efficiency and reducing headcount, the company later acknowledged it needed to rebuild human capability in key areas after the cuts went too far.
And this pattern may be more common than many assume. A Careerminds survey from February 2026 found that 32.7% of organisations that conducted AI-led layoffs had already rehired between 25-50% of the roles they initially eliminated.
Another 35.6% reported they had already rehired more than half of the roles that were cut.
In other words, the labour market may already be seeing the early stages of an AI layoff boomerang.
Thomas believes the same pattern may emerge during the current transition:
“AI is a powerful tool, but it won’t replace people entirely. Some organisations will realise they’ve cut the capability they still need and will find themselves needing to rebuild it.”
If history is any guide, the current wave of restructures may eventually be followed by new hiring cycles focused on different skills.
What this means for organisations
The important question for leaders is: How do you design work in an AI-enabled world?
Three priorities are becoming increasingly clear.
1. Redesign work, not just roles
AI changes tasks first before changing entire jobs. Instead of asking ‘which roles can AI replace?’, organisations should ask:
How should work be structured so humans and AI each contribute their strength?
2. Invest in AI-native capability
Future teams will rely on a blend of technical and human capabilities:
- AI literacy
- Critical thinking
- Systems thinking
- Leadership and collaboration
- Resilience
- Adaptability
And the organisations that invest in these capabilities early will move faster than their competitors who are still adapting.
3. Think more strategically about workforce design
AI adoption also creates an opportunity to rethink how teams are structured.
Not every requirement needs to be filled through a permanent hire. In some cases, the work may be better delivered through specialist contractors or project-based expertise.
Blended workforce models can combine the stability of permanent teams with the flexibility of external specialists. This approach can help organisations scale skills up or down as demand changes, while still maintaining control of intellectual property and reducing operational risk.
The conversation moving forward
It isn’t enough to keep focusing on the single question, ‘Will AI replace workers?’
The bigger shift already underway is the redesign of the workforce itself.
Future organisations are likely to operate with fundamentally different workforce models, combining permanent employees, project-based contractors and AI-augmented teams working together to deliver outcomes.
These blended teams will allow organisations to scale capability and productivity more fluidly as demand changes, reducing the need for the large-scale redundancies that often follow rigid workforce structures.
However, this evolution also places greater responsibility on leaders to think more carefully about workforce design before building out their teams.
Organisations that can plan for flexibility by building contingency and adaptability into their workforce strategies will be better positioned to navigate technological change without repeatedly cycling through major layoffs when market conditions shift.
The question is no longer whether AI will reshape work. It’s whether organisations are designing their workforce to adapt to that reality.