Workforce planning has always involved predicting the unpredictable. What capabilities will we need in three years? Five years? How should we balance building versus buying talent? Where are the critical skill gaps? Jobs and Skills Australia provides valuable data on emerging skill needs, but translating national trends into organisational strategy requires careful analysis.

AI makes these questions harder to answer and more important to get right. The capabilities we need are shifting. The roles we’ve always hired for may not exist in their current form. And the planning horizons that used to feel adequate now seem uncomfortably long.

Here’s how I advise HR and workforce planning teams to think about AI’s implications.

The Forecasting Challenge

Traditional workforce planning extrapolates from historical patterns. We look at past headcount changes, turnover rates, and capability needs to project future requirements.

This approach assumes relative stability—that the future will resemble the past closely enough for extrapolation to work.

AI disrupts that assumption. The work people do will change in ways that historical patterns can’t predict. Some tasks will be automated. Others will be augmented. New tasks will emerge. The pace of change makes multi-year projections especially uncertain.

This doesn’t mean abandoning planning. It means planning differently:

• Shorter planning cycles with more frequent revision
• Scenario-based approaches rather than single-point forecasts
• Greater emphasis on adaptability over specific skills
• More investment in capability building relative to external hiring

Identifying Roles at Risk

Not all roles face equal AI exposure. Useful frameworks for analysis:

Task-Based Assessment

Rather than evaluating entire roles, assess component tasks:

• Which tasks in this role involve routine cognitive work that AI handles well?
• Which tasks require creativity, judgment, relationship, or physical presence?
• What percentage of role time goes to each category?

Roles heavy in routine cognitive work face more disruption than roles heavy in human judgment and interaction.

Augmentation vs. Automation

Distinguish between:

• Automation potential: Tasks AI could do entirely
• Augmentation potential: Tasks AI could enhance while humans remain essential

Many roles will be augmented rather than automated. The human role changes but doesn’t disappear. Planning should account for this nuance.

Time Horizon Considerations

AI capabilities are advancing, but not uniformly. Some capabilities are mature today. Others remain limited. Consider:

• What can current AI actually do? (Be realistic, not hype-driven)
• What capabilities are likely within two years?
• What remains further out or more uncertain?

This temporal analysis helps prioritise planning efforts.

Building Adaptive Workforce Capability

Given uncertainty, the most resilient approach is building a workforce that can adapt to multiple futures.

Foundational Capabilities

Invest in capabilities that remain valuable across scenarios:

• Learning agility and growth mindset
• Critical thinking and judgment
• Complex problem-solving
• Communication and collaboration
• Relationship and influence skills

These aren’t AI-proof because nothing is AI-proof. But they’re more durable than specific technical skills.

AI Fluency Across the Workforce

If AI will touch most roles, basic AI fluency becomes a universal requirement. This includes:

• Understanding what AI can and can’t do
• Ability to work productively with AI tools
• Judgment about appropriate AI application
• Critical evaluation of AI outputs

Building this baseline capability is a workforce planning priority.

Specialised AI Capability Where Needed

Some roles require deeper AI expertise:

• AI system development and maintenance
• AI ethics and governance
• AI training and change management
• AI-enabled process design

Identify these specialised needs and plan for capability acquisition through hiring, development, or external partnerships.

Scenario Planning Approaches

Rather than single-point forecasts, develop multiple scenarios:

Scenario 1: Gradual Augmentation

AI capabilities improve steadily but adoption is measured. Most roles evolve gradually. Workforce changes are incremental and manageable through normal attrition and development.

Scenario 2: Rapid Transformation

AI capabilities advance faster than expected. Competitive pressure forces rapid adoption. Significant workforce restructuring becomes necessary. Some roles disappear. New roles emerge quickly.

Scenario 3: Uneven Disruption

AI transforms some functions dramatically while leaving others largely unchanged. Different parts of the organisation face very different planning challenges.

For each scenario, consider:

• What workforce changes would be required?
• What capabilities would become critical?
• How would we need to adjust planning processes?
• What early indicators would signal this scenario emerging?

Planning for multiple scenarios builds resilience that single-point forecasts can’t provide.

Ethical and Social Considerations

Workforce planning in the AI era involves more than optimising headcount. There are ethical dimensions:

Responsibility to Current Employees

People who have contributed to the organisation deserve thoughtful treatment even if their roles evolve. Options include:

• Reskilling and internal mobility opportunities
• Transition support if roles are eliminated
• Transparent communication about changes
• Adequate time to adapt

The cheap approach—sudden layoffs with minimal support—damages trust, employer brand, and morale among remaining staff.

Equity Considerations

AI’s impact won’t be evenly distributed. Entry-level and administrative roles may face more disruption than senior positions. Workers with less educational background may have fewer adaptation options.

Workforce planning should consider:

• Who is most affected by changes?
• How can we support those most at risk?
• Are we inadvertently widening inequality?

Broader Social Impact

Organisations don’t operate in isolation. If every company pursues AI-enabled workforce reduction simultaneously, societal effects accumulate. Industry collaboration, policy engagement, and responsible corporate citizenship matter.

HR’s Evolving Role

HR’s role in organisations is being reshaped by the same AI forces affecting everyone else. Some HR tasks will be automated. Others will be augmented. But strategic workforce planning becomes more important, not less.

HR professionals should:

• Develop their own AI fluency
• Build analytical capabilities for workforce scenario planning
• Strengthen change management expertise
• Deepen understanding of emerging skill requirements
• Position as strategic partners in AI-related decisions

The transactional parts of HR may shrink. The strategic parts should grow.

Practical Next Steps

For workforce planning teams beginning to address AI implications:

Short Term (0-6 months)

• Assess current workforce AI exposure using task-based analysis
• Inventory existing AI capabilities and gaps
• Begin AI fluency building across HR function
• Establish baseline metrics for tracking

Medium Term (6-18 months)

• Develop scenario-based workforce plans
• Launch broad-based AI capability development
• Adjust hiring profiles to emphasise adaptability
• Strengthen internal mobility processes

Longer Term (18+ months)

• Integrate AI considerations into ongoing planning cycles
• Refine scenarios based on emerging evidence
• Build sustainable capability development infrastructure
• Contribute to organisational AI governance

The Uncertainty Paradox

Here’s the uncomfortable truth: we can’t predict with confidence how AI will reshape work. The honest answer to many workforce planning questions is “we don’t know.”

But “we don’t know” doesn’t mean “do nothing.” It means:

• Build adaptable capabilities rather than betting on specific predictions
• Plan for multiple scenarios rather than single forecasts
• Revise frequently as evidence emerges
• Invest in the ability to respond to change

The organisations that navigate AI workforce transitions well won’t be those with the most accurate predictions. They’ll be those with the greatest adaptive capacity.

That’s what workforce planning in the AI era really means: building organisations that can thrive across multiple possible futures, rather than optimising for one prediction that may prove wrong.