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AI & Technology

What Happens When AI Optimizes Your Workflow

If AI streamlines your tasks, it may also narrow your expertise.

2026-06-181 min read

Most professionals assume that AI optimization of their workflow is an unambiguously good thing, as it saves time and increases efficiency. However, this assumption overlooks a crucial side effect: the loss of peripheral skills. As AI takes over routine tasks, workers may no longer practice and refine the skills that are not directly related to their core tasks. For instance, an accountant who uses AI to automate tax returns may no longer develop their understanding of financial regulations. This specialization can make workers more vulnerable to changes in their industry, as they have a narrower range of skills to fall back on. The temptation to rely on AI for routine tasks is strong, but it's essential to recognize the tradeoff. By focusing solely on high-priority tasks, professionals may inadvertently diminish their ability to adapt to new situations. This narrow specialization can have significant implications for their long-term career prospects.

Key insights
AI optimization can lead to a loss of peripheral skills, making workers more vulnerable to industry changes.
Specialization can diminish a worker's ability to adapt to new situations, limiting their long-term career prospects.
The tradeoff between efficiency and flexibility is a critical consideration when implementing AI in the workplace.
Developing a broad range of skills can provide a safety net for workers as AI continues to advance and automate tasks.
Why it matters

Ignoring this dynamic can lead to a workforce that is highly efficient but inflexible and incapable of responding to unexpected challenges.

Furthermore, as AI continues to advance, the tasks that are automated today may become obsolete tomorrow, leaving workers without a safety net of transferable skills.

Use this tomorrow
1
This week, identify one task that you've automated and make a conscious effort to practice a related skill that is not directly related to your core tasks.
2
Review your workflow and identify areas where AI optimization may be narrowing your expertise, then develop a plan to broaden your skillset.
Go deeper

The concept of skill breadth and its relationship to career resilience has been studied extensively in the field of organizational behavior. Research has shown that workers with a broader range of skills are more likely to adapt to changes in their industry and thrive in uncertain environments. This idea has significant implications for how we approach AI adoption in the workplace.

The dynamics of AI optimization and skill loss are also relevant to the concept of "job crafting," which involves proactively shaping one's job to align with their strengths and interests. By recognizing the potential for AI to narrow their expertise, workers can take steps to craft their jobs in a way that preserves their skill breadth and promotes long-term career resilience.