Artificial intelligence has brought a wave of new vocabulary into the workplace, and much of it sounds more technical than it actually is. Employers don’t need a computer science degree to keep up, but you do need to understand what these terms mean in practice, because HR policies, vendor contracts, and even performance reviews are increasingly built around this language. Below are 10 terms making the rounds right now, explained simply, along with a quick note on why each one matters to your organization.
1. Tokenmaxxing
This is a way of measuring AI use. It’s the practice of maximizing how many AI “tokens” (units of text an AI model processes) an employee or team runs through a system. These are sometimes tracked on internal leaderboards at tech companies where heavy AI use is encouraged. (The opposite trend, “tokenminimizing,” is also emerging: some companies are now capping AI use altogether after realizing usage-based rewards are counterproductive.)
| Why it matters at work: Some organizations have started mimicking tech companies by rewarding heavy AI usage as a proxy for productivity. But that can backfire when your employees pad their prompts or run unnecessary AI tasks just to boost their numbers, not to mention the fact that constant AI-heavy work can also drive burnout. If you want to mirror Silicon Valley and track AI usage, track outcomes alongside it, not volume alone. |
2. AI washing
When a company overstates, exaggerates, or falsely advertises the AI...
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