CEO Briefing: Could employees in larger companies be more susceptible to AI related job displacement?
The rapid advancement of artificial intelligence technologies is transforming workplaces across New Zealand, raising questions about job displacement and restructuring.
This report evaluates the assertion that employees in smaller businesses (under 100 employees) are less susceptible to AI-driven job displacement, while larger enterprises (1000+ employees) face significant restructuring pressures.
Through examination of New Zealand-specific data, research, and case examples, this report provides a nuanced analysis of how business size correlates with AI's workforce impact.
Current State of AI Adoption in New Zealand
New Zealand businesses across all size categories have been increasingly experimenting with and implementing AI technologies. According to recent surveys, 82% of New Zealand small and medium-sized businesses (SMBs) are at minimum experimenting with AI technologies—significantly higher than both the global average of 75% and the Asia-Pacific regional average of 63%[3].
However, adoption remains uneven, with another survey indicating approximately half of Australian and New Zealand small businesses have yet to incorporate AI into their operations[8].
The pace of AI capability development presents an urgent timeline for adaptation. Research from Model Evaluation & Threat Research (METR) indicates AI capabilities are doubling approximately every seven months, creating an accelerating trajectory toward potential job displacement that many New Zealand organizations may be unprepared to address[1]. By 2028-2031, AI systems are projected to reliably complete projects requiring an entire month of human labor[1].
AI Impact on Small Businesses (<100 Employees)
Adoption Patterns and Revenue Effects
Smaller New Zealand businesses implementing AI technologies report overwhelmingly positive outcomes. A striking 95% of New Zealand SMBs utilizing AI report enhanced earnings—a figure that exceeds most global counterparts[3][11]. These businesses primarily apply AI in three key areas: optimizing marketing campaigns, deploying automated customer service chatbots, and providing automated recommendations for customers[3].
The adoption approach tends to be more targeted in smaller organizations. Rather than implementing comprehensive AI transformation strategies, these businesses typically identify specific operational pain points where AI can deliver immediate value. This focused implementation may explain why smaller businesses report minimal job displacement resulting from AI adoption.
Task Augmentation vs. Displacement
For smaller businesses, AI appears to function more as a productivity multiplier than a job replacement technology. With limited staff resources, these organizations value AI's ability to augment existing roles rather than eliminate positions. The concentrated expertise within small businesses often means employees perform diverse functions that are less susceptible to complete automation.
New technologies like Small Language Models (SLMs) are particularly well-suited for smaller organizations, offering several practical advantages:
Focused performance: SLMs learn from smaller, targeted datasets directly relevant to specific business tasks[6]
Cost-efficiency: More budget-friendly to deploy and maintain than larger systems[6]
Customisation: Can be tailored to specialized organisational needs[6]
Easier updates: More adaptable to changing business requirements[6]
This alignment between small business needs and focused AI technologies suggests smaller organizations may experience less disruptive workforce impacts while still capturing productivity gains.
AI Impact on Large Businesses (>1000 Employees)
Strategic Implementation and Restructuring
Larger New Zealand enterprises typically approach AI implementation as part of comprehensive digital transformation strategies. These organizations often have specialized departments, standardized processes, and higher volumes of routine tasks—creating conditions where AI can potentially replace entire job functions rather than simply augmenting them.
Evidence of restructuring in larger New Zealand organizations is emerging. For example, Spark (a major New Zealand telecommunications company) recently announced staff restructuring with AI explicitly mentioned as a contributing factor in their efficiency drive[10]. This example aligns with the research indicating that AI's most immediate impact will target knowledge workers in professional services—roles commonly concentrated in larger organizations[1].
The Microsoft-commissioned report "New Zealand's Generative AI Opportunity" projects that AI adoption is expected to add $76 billion to New Zealand's economy by 2038, representing 15% of GDP[5]. This economic transformation will inevitably drive workforce restructuring, with the analysis revealing:
24% of tasks could be augmented by using generative AI as a copilot
14% of tasks could be automated entirely
The average worker could free up 275 hours annually[12]
Scale Advantages and Disadvantages
Larger organizations possess certain advantages in navigating AI transition:
1. Resource capacity: Better positioned to invest in comprehensive AI training and implementation
2. Data advantages: Have larger proprietary datasets essential for effective AI implementation
3. Specialised roles: Can create dedicated AI governance and development teams
However, these same organizations face greater restructuring pressures:
1. Process standardisation: Standardised workflows are more easily automated
2. Volume efficiency: AI cost-effectiveness increases with scale
3. Reporting pressure: Public and shareholder accountability may drive aggressive efficiency initiatives
Evaluating the Central Assertion: Size as a Factor in AI Impact
The available New Zealand evidence provides limited support for the central assertion that small businesses will experience less job displacement than large enterprises. While there are indications of differential impacts, the relationship appears more nuanced than the binary statement suggests.
Supporting Evidence
Several factors support aspects of the assertion:
1. The AI Forum of New Zealand reports that "AI-driven job displacement will account for only 10 percent of normal job" turnover across the economy—suggesting moderate rather than drastic impacts in both small and large businesses[7].
2. Smaller businesses report overwhelmingly positive revenue impacts from AI adoption without significant corresponding layoffs, suggesting implementation is primarily augmenting rather than replacing staff[3][11].
3. Job cuts explicitly linked to AI implementation have thus far been more visible in larger New Zealand enterprises like Spark[10].
4. The technology adoption curve suggests larger organizations typically implement transformative technologies earlier, potentially facing restructuring pressures sooner.
Contradicting Evidence
Other findings challenge or complicate the central assertion:
1. The Treasury's prediction that New Zealand's concentration of knowledge-based jobs makes its labor market particularly vulnerable to AI transformation applies to organizations of all sizes[9].
2. Research shows that "AI's immediate impact on employment is felt in how it has streamlined tasks, but it has not yet eliminated entire jobs"—a pattern consistent across business sizes[9].
3. Only 8% of New Zealand businesses (regardless of size) report significant changes in tasks traditionally performed by humans thus far[9].
4. The PwC AI Jobs Barometer shows generalized growth in AI-related positions across the New Zealand economy without clear size-based differentiation[4].
Industry-Specific Considerations
The impact of AI appears more strongly correlated with industry sector than business size alone:
1. Financial Services: Both small and large financial firms face significant task automation potential, with Treasury data suggesting substantial vulnerability[1][9].
2. Healthcare: Organisations of all sizes benefit from AI augmentation rather than replacement, with hybrid AI-human workflows showing reduced turnover[15].
3. Customer Service: While automation of service functions is widespread, the 14% productivity gains are observed across business sizes[15].
Recommendations for New Zealand Organisations
Based on the available evidence, several recommendations emerge for New Zealand businesses navigating AI implementation:
For Small Businesses (<100 Employees)
1. Prioritise augmentation over replacement: Focus AI implementation on enhancing employee capabilities rather than eliminating positions. This approach aligns with New Zealand SMBs reporting success with marketing optimisation, customer service, and recommendation engines[3].
2. Explore purpose-built AI solutions: Investigate Small Language Models (SLMs) and other specialised AI tools designed for specific organisational needs, which are often more cost-effective and implementation-friendly for smaller businesses[6].
3. Develop AI readiness plans: While immediate job displacement appears limited, the accelerating capability trajectory suggests proactive planning is essential. The five-year timeline identified in research provides a window for strategic preparation[1].
4. Participate in industry collaborations: Partner with industry associations, technology providers, and government initiatives to access AI resources that might otherwise be unavailable to smaller organizations.
For Large Businesses (>1000 Employees)
1. Implement ethical restructuring frameworks: Develop transparent approaches to AI-driven organisational change that prioritise reskilling and redeployment over elimination. New Zealand research shows 44% of businesses identify worker displacement as an ethical challenge[19].
2. Address the skills gap: With 47% of employees lacking confidence in using AI tools, develop structured upskilling programs that maintain workforce viability as tasks evolve[15].
3. Create AI governance structures: Establish clear ethics guidelines and governance frameworks, which research indicates can improve talent retention by up to a 28% compared to organizations without such frameworks[15].
4. Focus on human-AI collaboration: Target the 24% of tasks that research suggests can be augmented rather than eliminated, creating productivity multipliers rather than direct replacements[12].
For Policymakers
1. Enhance monitoring of AI workforce impacts: Expand data collection on AI-related job transitions across different business sizes to inform evidence-based policy development.
2. Develop targeted transition support: Create programs specifically designed to support worker transitions in heavily affected sectors, regardless of organization size.
3. Consider New Zealand's AI sovereignty: Explore potential for homegrown AI-based services via targeted investment or even government-initiated enterprises to retain economic benefits domestically[18].
Conclusion: A More Nuanced Reality
The available New Zealand evidence suggests a more complex relationship between business size and AI-driven job displacement than the original assertion proposes. While some patterns align with the hypothesis that smaller businesses may experience less dramatic workforce disruption, the distinction appears less pronounced than suggested.
Current data indicates that approximately 8-10% of New Zealand jobs face potential AI-driven displacement in the near term[7][9], with minimal observed difference based on organization size thus far. However, the accelerating trajectory of AI capabilities—doubling every seven months—suggests the next three years may bring more significant disruption as systems become capable of handling increasingly complex, month-long projects[1].
Rather than business size alone, the more determinative factors appear to be:
1. Implementation approach: Organisations prioritising augmentation over replacement report less displacement regardless of size
2. Industry sector: Knowledge-intensive sectors face greater potential disruption across all business sizes
3. AI readiness: Only 9% of New Zealand organizations report being fully prepared for AI integration[15]
As New Zealand navigates this transition, the focus should shift from size-based predictions to developing responsible AI implementation strategies that maximize economic benefits while supporting workforce adaptation across the full spectrum of New Zealand businesses.
Sources
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