Why AI Leads to More Work, Not Less

2026-02-11 · Source: The AI Daily Brief: Artificial Intelligence News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, long

Summary

A recent Harvard Business Review study by Aruna Ranathan and Shingchi Maggi, based on an embedded observation of a 200-employee tech company, reveals that AI use is intensifying work rather than reducing it. The research identified three main forms of work intensification: task expansion, where workers take on responsibilities previously belonging to others; blurred boundaries between work and non-work, as AI makes starting tasks easier during breaks; and increased multitasking, with users running multiple AI agents or parallel tasks. While this intensification allows organizations to achieve more and offers intrinsic rewards of mastery, it also introduces new challenges like spillover effects requiring cleanup work from others and reduced downtime due to increased expectations for speed. The study suggests a shift from AI as an efficiency tool to an expansionary opportunity, creating new product lines and markets.

Key takeaway

For CTOs and VPs of Engineering evaluating AI integration, recognize that AI is likely to expand job scopes and intensify work, not merely reduce it. Your strategy should pivot from cost-cutting to leveraging AI for new product lines and market expansion. Be prepared to implement new management strategies, such as intentional pauses and task sequencing, to mitigate burnout and manage increased expectations for speed within your teams.

Key insights

AI use is intensifying work through task expansion, blurred boundaries, and increased multitasking, rather than reducing it.

Principles

• Work expands to accommodate capacity.
• AI shifts focus from efficiency to expansion.

Method

Researchers embedded with a 200-employee technology company from April to December to observe AI's impact on daily work, identifying patterns of intensification.

In practice

• Implement intentional pauses in AI workflows.
• Sequence tasks to manage parallel AI operations.

Topics

• AI Work Intensification
• Agentic AI
• AI Job Displacement
• Organizational AI Strategy

Best for: CTO, VP of Engineering/Data, Executive, AI Product Manager, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI Daily Brief: Artificial Intelligence News.