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Why AI learning needs a place in the workday
If your calendar is already full, “study after work” does not solve the scheduling problem; it moves the cost onto your personal time. Ask for learning time to be treated as work, with agreement about what should move or take priority while you use it.
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There is a practical reason to make that request explicit. Microsoft and LinkedIn’s 2024 Work Trend Index, based on a survey of 31,000 people across 31 markets alongside other labor and workplace signals, reported that 75% of surveyed knowledge workers used AI at work. In a separate finding, 39% of surveyed AI users said their company had provided AI training. These are survey results, not a census of employers, but they show why workers may be expected to use AI before they have received formal training. Microsoft and LinkedIn’s 2024 Work Trend Index and Microsoft WorkLab’s related survey findings.
Find a realistic block before you ask
Look at one ordinary workweek rather than promising yourself time that does not exist. Identify a recurring gap you can protect, or the meeting, task, or lower-priority work that would need to move. If nothing can move without putting a deadline at risk, that is useful information to bring into the conversation—not a reason to silently add training hours to your day.
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LinkedIn’s workplace-learning guidance suggests calendar blocking and gives one hour a month or one hour a quarter as examples. Those are possible starting points, not a tested prescription or a guarantee that either cadence is enough for your role. Agree on a frequency that fits your responsibilities, then put the block on the calendar with a clear label such as “AI practice: summarize approved internal updates.” LinkedIn’s guidance on making time for learning at work.
Make a specific, bounded request to your manager
A useful request explains the time, the work it supports, and the boundaries for practice. For example:
“Could I reserve a recurring block during work hours to learn how to use an approved AI tool for first-draft summaries of material we are allowed to share with it? I’ll bring back one example for review. Which tool and data rules should I follow, and what should I deprioritize during that block?”
Adapt the task and cadence to your role. LinkedIn’s 2025 Workplace Learning Report recommends development that reflects job needs: introductory AI fluency may be relevant for an administrative assistant, while an engineer building and deploying AI systems may need more technical skills. The report also advises employers to provide dedicated time to learn and experiment with approved generative AI tools. That is organizational guidance, not evidence that a particular allocation is optimal. LinkedIn Workplace Learning Report 2025.
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Choose one work task and one learning outcome
Keep the first learning block narrow enough to apply and review. Pick a task you already understand, then decide what you want to learn about doing it with AI. Depending on your employer’s policy, examples might include exploring a first draft, summarizing non-sensitive material, or getting help with a spreadsheet. These are examples, not blanket approval to put workplace content into an AI system.
- Task: Name the specific, recurring step in your work.
- Learning outcome: State what you will practice—for example, writing a useful prompt or checking an AI-generated summary against its source.
- Review: Decide what a colleague, manager, or existing quality check should verify before the result is used.
Before entering any work information, check your employer’s current AI policy and approved-tool list. Confirm what information may be used, whether outputs can be retained or shared, and whether human review is required. This matters because workers have reported using AI without official employer tools or training, while the OECD identifies data collection and use as workplace concerns. Microsoft and LinkedIn’s 2024 Work Trend Index; OECD, “Using AI in the Workplace” (2024).
Protect deadlines while you practice
Learning should not quietly displace urgent work. Agree with your manager on what takes priority during the block and what to do if a deadline or customer need conflicts with it. Use a low-risk, bounded exercise, and do not rely on an AI output in live work until it has been checked under your team’s normal standards.
- Before the block: Confirm the time is still protected and choose the task and approved tool.
- During the block: Practice one skill on permitted material. Note where the AI result needs correction or human judgment.
- After the block: Review the work with the relevant person or quality process. Record whether the practice was completed and what, if anything, should change next time.
Do not count a faster-looking draft as a productivity gain by itself. OECD surveys found that four in five surveyed workers said AI improved their performance at work and three in five said it increased their enjoyment of work. Those are self-reported survey findings, not a promise about any individual’s results. The same OECD publication notes concerns including increased work intensity as well as data collection and use. OECD, “Using AI in the Workplace” (2024).
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Choose learning that fits the job, not just the trend
When comparing a course, internal workshop, or hands-on practice, use the same practical checks. A suitable option should match your role, respect employer tool and data rules, fit within protected work time, and give you a way to apply and review what you learn. A broad introduction may be useful for one employee; a technical path may better serve another. The available evidence does not identify one universally best course or provider.
LinkedIn’s 2025 report says career development champions were 32% more likely than non-champions to deploy generative AI training programs. That is an association in the report, not proof that those programs caused greater AI adoption. It supports treating AI skills as part of a wider development plan rather than as an isolated trend. As Naphtali Bryant, an executive coach and leadership development consultant at RAC Leadership, put it in the report, “Think of it as a unified strategy for agility,” referring to generative AI adoption and career development. LinkedIn Workplace Learning Report 2025.
If your workload leaves no room for training
If your manager cannot approve a learning block, ask which current responsibility should take priority and whether the learning and development team can help find an alternative. Keep the conversation focused on workload and trade-offs: learning time cannot be protected if every existing task remains equally urgent.
The OECD Skills Outlook 2025 characterizes the evidence it reviews as associating negotiated AI adoption—with worker consultation and training provision, including dedicated training time—with better worker outcomes. It says these practices can help steer AI toward augmenting workers rather than displacing them. This is the report’s account of the evidence, not a guarantee that any particular consultation or training arrangement will produce a specific outcome. OECD Skills Outlook 2025.
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