When the Australian technology company Atlassian recently announced layoffs (1600 jobs, 10% of global workforce) as part of a broader restructuring, many employees were reportedly taken by surprise.

The company explained that the changes were linked to a strategic shift toward platform efficiency, automation and increased use of artificial intelligence tools. Public statements emphasised productivity improvements and organisational focus. But inside the organisation some employees were left confused about what the changes meant for the future of work inside the company.

For many staff the issue was not simply the loss of roles. It was the absence of a clear narrative explaining how technology—particularly artificial intelligence—was expected to reshape work.

Questions quickly surfaced:

• Which tasks were being automated?
• Which roles were expected to evolve?
• Would new AI-related roles emerge internally?
• Was this a temporary restructuring or the beginning of a deeper technological shift?

Without this context, the restructuring risked appearing less like a planned workforce transition and more like a sudden efficiency exercise. The episode highlights a broader leadership challenge now confronting organisations around the world. When technological transformation occurs faster than workforce communication and planning, employees are left uncertain about what lies ahead.

A growing pattern across industries

Over the past two years, large technology companies have collectively announced hundreds of thousands of job reductions while simultaneously increasing investment in artificial intelligence and automation. Industry trackers estimate that more than 260,000 technology-sector jobs were cut globally in 2024 alone, with restructuring continuing into 2025 and 2026 as companies reorganise around AI capabilities.

In some cases the connection between layoffs and AI adoption is explicit. In others, companies refer instead to “productivity gains”, “technology transformation” or “operational efficiency”. Moreover where layoffs occur that may not be simply because AI has replaced a worker but may be the consequence of multiple motives [Forbes: “Why Today’s AI-driven Layoffs are becoming Tomorrow’s Hiring Crisis” ]

Across sectors the sequence often looks similar:

• Investment in AI infrastructure
• Emphasis on productivity gains
• Workforce reductions in adjacent roles
• Communication of workforce transition strategies only afterwards

This pattern has appeared not only in technology companies but also in professional services, media, publishing and other knowledge-intensive sectors. For employees, the result is understandable anxiety. When layoffs occur alongside technology investments, it is easy to assume that machines are simply replacing people.

Yet the reality is often more complex.

The reality: work is changing, not disappearing

Artificial intelligence systems are already performing tasks that were previously carried out by humans. These include activities such as document analysis, customer service responses, data processing, software coding assistance and elements of financial analysis.

However, most jobs are not disappearing entirely.

Instead, AI is changing the task composition of work.

Routine tasks are increasingly automated, while human work is shifting toward areas where judgement, creativity, complex decision-making and relationship management remain essential.

Historically, technological change rarely eliminates work altogether. Instead it reshapes the kinds of skills that are valuable.

The real challenge lies in managing the transition.

When organisations introduce new technologies without clear workforce planning, employees are left uncertain about their future. That uncertainty can quickly erode trust.

The debate about artificial intelligence and employment is often framed as a contest between two perspectives.

Pessimists argue that AI represents a new form of automation capable of replacing both routine and cognitive work.

MIT economist Daron Acemoglu has warned that if artificial intelligence is primarily used to automate existing tasks rather than augment human work, it could reduce labour demand and push workers into lower-productivity roles.

Economist David Autor has similarly suggested that the greater risk may not be mass unemployment but the erosion of the economic value of certain skills as automation reshapes the labour market.

Optimists, however, take a different view.

Research by Erik Brynjolfsson and colleagues indicates that artificial intelligence can significantly improve productivity by helping workers perform tasks more effectively and by spreading expertise across organisations.

Australian AI researcher Professor Toby Walsh has taken a more balanced position. While acknowledging that AI will disrupt many occupations, he argues that technological change historically reshapes jobs rather than eliminating them altogether.

What responsible organisations should do

The long-term impact of AI on employment will in all probability depend less on the technology itself and more on how organisations choose to deploy it
If artificial intelligence is to improve productivity without damaging trust, organisations must treat technological transformation as a workforce strategy.

This requires several key steps.

1. Conduct workforce impact assessments

Before deploying AI systems at scale, organisations should analyse:

• which tasks will change
• which roles will evolve
• which roles may disappear
• which new roles may emerge

This analysis allows organisations to prepare the workforce before disruption occurs.

2. Communicate early and clearly

Employees should not first learn about technological transformation at the moment restructuring begins.

Responsible and caring organisations explain:

• why AI is being introduced
• what benefits it will deliver
• how the workforce will be supported during the transition

Early communication reduces uncertainty and builds trust.

3. Invest in reskilling and redeployment

Many roles that appear vulnerable to automation can evolve into higher-value work if employees are given the opportunity to develop new capabilities.

Skills increasingly in demand include:

• human-AI collaboration
• data interpretation
• advisory and relationship management
• complex problem-solving

Where roles genuinely disappear, redeployment into adjacent functions should be prioritised wherever possible.

4. Treat layoffs as a last resort

If redundancies become unavoidable, organisations should approach them with transparency and fairness.

This includes clear explanations of the business rationale, consultation where required and meaningful career transition support.

Legal compliance is necessary, but responsible organisations go further by recognising the human impact of technological change.

Leadership perspective: managing the human transition

Organisations often approach artificial intelligence primarily as a technology investment. In practice, its success depends just as much on leadership.

Workforce transitions succeed when employees understand how their roles may evolve and believe they will be supported in adapting to change. Without that confidence, technological transformation can generate uncertainty, resistance and disengagement.

Leaders therefore face an important question when introducing AI: not simply how the technology will improve productivity, but how the workforce will be included in the transition.

This involves creating psychological safety around change, investing in skill development and communicating openly about the future of work inside the organisation.

When organisations treat AI transformation as a shared journey rather than a top-down efficiency programme, employees are far more likely to engage constructively with new technologies.

AI-driven workforce transformation also raises significant legal and governance risks. Employment law in most jurisdictions requires organisations to follow fair redundancy procedures and consult employees appropriately.

At the same time, the increasing use of algorithmic systems in recruitment, performance management and workforce planning introduces new risks. Algorithms trained on historical data may unintentionally reproduce existing biases, creating potential exposure under discrimination and equal opportunity laws.

Beyond legal compliance, organisations also face cultural risks. Sudden layoffs linked to technological change can create widespread anxiety among remaining employees, reducing engagement at precisely the moment organisations need their workforce to adapt and innovate.

Responsible leadership therefore requires organisations to treat AI transformation not simply as a technology project, but as a people strategy.

A moment of transition

Artificial intelligence will undoubtedly reshape the labour market. Some jobs will disappear. Many more will change. At the same time, entirely new roles and industries are emerging.

That transformation in our workplaces by AI is already well underway. The real question is how organisations choose to manage it. Companies that treat AI purely as a cost-reduction tool risk creating fear, distrust and cultural disruption.

Organisations responding to the challenge with a profound understanding that a workforce transition strategy is essential have the opportunity to strengthen trust, develop new capabilities and unlock long-term productivity.

Employees do not expect certainty about the future. In other words, the long-term impact of AI on employment will depend less on the technology itself and more on how organisations choose to deploy it.

But they do expect honesty. They want to know whether their roles will change, whether they will have opportunities to develop new skills and whether their organisations are prepared to support them through the transition.

Artificial intelligence will transform work. But the organisations that succeed in the AI era will not be those that adopt the technology fastest. They will be the ones that manage the human transition best.

Before implementing artificial intelligence systems that may reshape work, leaders should consider three critical questions:

*Have we clearly explained how work will change?
Employees need to understand which tasks may be automated, which roles will evolve and where new opportunities may emerge.

*Are we investing in people as well as technology?
Reskilling, redeployment pathways and capability development are essential to ensuring that technological progress benefits both organisations and employees.

*Are we building trust during the transition?
Leading with transparency, early communication and fairness in decision-making are critical to maintaining engagement during periods of organisational change.