Lately, I’ve noticed a pattern in the kind of work that I do and the questions I receive—and maybe you have, too. For sure, Generative AI is a great productivity booster for a range of knowledge work that requires deep thinking and skill. Getting to that first draft within a matter of seconds with the help of AI has become a no-brainer. Why write it yourself? Generate. Skim. Send. Productivity problem: solved.
But when you’re on the receiving end and you’re asked to review drafts (that have seemingly been created with AI) without a diligent review, that mediocrity hits you with its full force.
When Mediocrity Hits You (in the Face)
Imagine the following scenario: Your kitchen stove is broken. You hire a professional who comes to your house to take a look and fix it. Before you can even say ‘hello,’ they are already out the door again, sticking a screwdriver and a bill in your hand that they have haphazardly put together. By their own account, they are extremely efficient because through their approach, they can now see 10x more customers in a workday. The only problem: your stove still isn’t fully operational, and you need to troubleshoot and fix the remaining issue yourself. Any of us would hardly find this acceptable, let alone pay for this kind of service.
Now, imagine the last time a co-worker or team member asked you to review a draft they have created—maybe it was even the “final” version. And maybe they even shared that they have created it with the help of AI within a fraction of the time it would have previously taken them. But once you start reading it, you notice something: It’s not bad. It’s largely correct. But it’s not great, specific, or without errors either. In fact, you notice that with a bit more attention and care, the team member could have spotted and resolved the mistakes themselves—before sending it to you for review.
What has just happened? Their AI-driven time-saving and productivity have become your manually reviewed problem.
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Now, it’s happened to me, too. Actually, I should rather say: I have let it happen before, too. I passed on the shortcut to the result with minimal edits. Maybe you have recently done the same.
I see us entering an era in which good enough becomes the new great. Don’t get me wrong; a lot of times, good enough is indeed good enough. But similar to how (I hope) we have learned in prompting training that “you are still responsible for the AI’s output,” you are not only responsible for its accuracy but also for its quality.
That’s why leaders have an even bigger responsibility when it comes to demanding high-quality work from their teams. As a leader, this means setting and re-setting expectations together with your team as the use of AI increases:
Encourage team members to use AI; they absolutely should
Using AI is not a sign of laziness or incompetence (which 46% of survey respondents mentioned as an inhibitor of AI usage in Slack’s Workforce Index study last fall).
Set clear expectations on when, where, and how to use AI
Team members are responsible for the accuracy and the quality of the results they submit, whether or not AI is involved. For example, use AI tools to generate and refine ideas combined with your own research, validation, and expertise. Review AI-generated output like you would review a junior team member’s work1 before passing it on. Passing on AI-generated results without review or fact-checking is unacceptable.
Retain the right to ask for re-work
If you spot check and notice that team members are not following the mutually agreed guidelines, retain the right to ask them for a revision. Just like before ChatGPT & Co., provide feedback and guidance as to what should be improved and where the bar is.
Even if you don’t currently lead a team, holding yourself to a higher standard will help you stand out and leverage the best of what humans and AI can create together. In addition, you make your recipient’s life a little easier, too, just like you would have before ChatGPT & Co.
Summary
Generative AI is enabling us to rapidly generate first drafts. However, the sender’s newfound productivity gains should not become the receiver’s burden if the quality of the information is subpar. Leaders should set expectations with their teams that team members are still held to a higher quality standard, whether or not AI is involved.
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I am generally not a fan of comparing AI and humans or anthropomorphizing them because AI and humans are not alike. Despite its increasing capabilities, viewing AI as a junior team member might make users pay more attention to detail than viewing AI as a senior team member, more capable than themselves.
