AI is supposed to lighten the load. So why does it still feel like more work?
AI is supposed to take the work off our hands. Automate routine tasks. Free up time for strategy. That’s the promise.
In practice, 77% of employees report that GenAI increases their workload—not reduces it. (Upwork)
Not because AI doesn’t work. But because it delivers speed, not a system. Drafts are generated in seconds. Communication becomes cheap. And suddenly there’s just more of it—plus the task of reviewing everything.
And this applies to a daily routine that’s already fragmented: According to Microsoft, you’re interrupted on average every two minutes by a meeting, email, or notification. (Microsoft WorkLab)
AI isn't just adding to the noise—it makes the existing noise more cost-effective.
This article shows you what typically goes wrong —and how to use AI in a way that truly lightens your workload (not just speeds things up). It outlines three simple rules that strike a balance between speed and quality—clearly explained in this Harvard Business Review article.
How AI Makes Work More Intense (and Why You Don't Realize It Until It's Too Late)
Before we get to the rules, you need to understand the pattern. Otherwise, you’ll just be treating the symptoms—and wonder why things are still getting worse.
The latest HBR article highlights a pattern that many teams are currently experiencing firsthand: AI doesn’t automatically reduce the amount of work—it makes more tasks easier to handle. The result: a faster pace, a broader range of tasks, and work that is spread out over more hours in the day.
The article describes three typical dynamics. Important: They rarely occur in isolation. They reinforce one another.
1) Task Expansion: “I can do that now, too”
AI fills in knowledge gaps. Suddenly, product managers are coding. Designers are “quickly” putting together a script. Research teams are taking on engineering tasks. It feels empowering.
The price comes later: Seniors review, coach, and save pull requests. Unplanned, but real.
And that’s exactly when it clicked for us. The topic came up with one of our clients when a senior engineer said, “I now spend 30% of my time fixing AI code written by people who’ve never coded before.” That was the moment it became clear: AI hasn’t reduced the workload. It’s just redistributed it.
2) Ambient Work: Work becomes something done “on the side”
Because it’s so easy to start, work creeps into your breaks: during coffee, between meetings, “just before the end of the workday.” Prompt feels like chatting—and that’s exactly why you often only realize the toll it takes in hindsight: less real rest, more constant connectivity. (Harvard Business Review)
3) Multitasking: more threads, greater cognitive load
AI sets a new pace: You keep working while the next version is already taking shape in the background. It sounds efficient. But it often amounts to constant context switching: check, tweak, compare, check again. (Harvard Business Review)
The insidious thing is that each of these dynamics feels harmless at first. Together, they lead to workload creep: a faster pace, more side tasks, more “just a quick prompt”—until focus, quality, and breaks start to fall by the wayside.
5 Questions: Are you already seeing workload creep?
Here are 5 simple questions to help you figure out if you (or your team) are already in this situation. If you answer “yes” to two of them: welcome to the club.
- Are results expected sooner “just because AI is here”?
- Do people take on tasks outside their job description because AI makes it easy to get started?
- Are pauses filled with "just a quick reply"?
- Do seniors participate more often in informal review sessions (Slack, calls, DMs)?
- Is the number of concurrent tasks increasing—without anything being officially prioritized?
That's not a tool problem. It's a leadership issue.
In many teams, AI acts like an amplifier: tasks that were already stressful become faster; issues that were already unclear become more pronounced; and things that “weren’t really a priority” suddenly become feasible—and so they get done.
We need competent leadership to ensure that we all use AI effectively. This starts with self-management and then extends to the wider environment.
That is precisely why it is not enough to simply “let AI run its course.” Conscious rules are needed. The Harvard Business Review article refers to these rules as “AI practices.” (Harvard Business Review)
The solution: “AI Practice” – few rules, big impact
You’ve seen it: AI makes output cheaper—and without team guidelines, the workload doesn’t decrease; it actually intensifies. The HBR article calls the solution “AI Practice”: small, repeatable routines that define how AI is used—and where to consciously draw the line so that work doesn’t quietly pile up (task expansion) or become more concentrated through reviews and context switching (multitasking).
Three components of the AI Practice that you can test as a team:
1) Intentional Pause (slows down task expansion)
When everyone suddenly starts taking on tasks “just for a moment” that fall outside their job description, there’s often no time to ask: Should we even be doing this?
Example: AI generates landing page variations for you in minutes. Instead of publishing them right away, take a 60-second pause:
- 1 Counterargument: “Why not record that live today?”
- 1. Priorities check: “If we go live with this today, what are we consciously putting on hold this week?”
Effect: You’re not stopping the AI; you’re stopping the reflex to think, “That’ll be quick.” The priority check forces you to weigh every AI shortcut against your actual capacity.
2) Sequencing (reduces multitasking and review chaos)
When options become “cheap,” feedback turns into a never-ending cycle: constantly new versions, constantly new questions, constantly new minor decisions. Sequencing turns this back into a process with distinct phases: Create → Evaluate → Decide → Complete.
Example: Five AI-generated options in Slack: “Which one should we go with?” With sequencing:
- Review window: 2 set times per day (e.g., 11:30 a.m. & 4:00 p.m.)
- In between: Focus time without review notifications (“we collect feedback, but we don’t respond immediately”)
- Decision at the breakpoint: “At 4:00 p.m., we’ll choose A or B—and that’s it.”
Result: fewer context switches, less endless iteration, clearer decisions.
3) Human Grounding (ensures quality, prevents AI silos)
AI speeds up solo work—but context comes from the system: customers, sales, support, real objections, real side effects. Without staying grounded, you’ll quickly end up optimizing in a way that misses the mark—just faster. Routine: 10 minutes of human interaction before things get “important.”
Example: Strategy design using AI on screen:
- 10-Minute Check-In: “What’s the main point? What would be the strongest objection?”
- 1 Reality Check from Sales/Support: “What customer question immediately exposes the problem?”
Important: This isn't about "let's set up a meeting." Often, a quick message to the right person is all it takes.
Result: AI sets the pace; humans provide context.
Conclusion
AI rarely increases the workload through deliberate design—mostly because it makes initiating tasks so easy that speed becomes the norm. Standards help. But it only becomes sustainable when someone builds AI-driven work as a system: with ownership, clear prioritization, and automation that truly removes work from the process (rather than just generating new tasks more quickly). This is precisely where “we use AI” differs from “we scale with AI.”
If you want to take this step in a structured way: In our Master Business with AI (MBAI) , you’ll learn how to build an AI team, implement automation effectively, and integrate AI leadership into your daily routine. And if you’d rather start with small steps: Subscribe to our newsletter.
AI doesn't save you work. It reduces friction. And friction was often your only protection against overload.
Sources
- Harvard Business Review (2026): AI Doesn’t Reduce Work—It Intensifies It
- Upwork Investors: “Upwork Study Finds Employee Workloads Rising…”
- Microsoft WorkLab: “Breaking Down the Infinite Workday”
