Administrative Services Managers

In admin work today, AI mostly helps rather than completely replaces people. For example, Google’s recent report found that simple AI tools can save office workers about 122 hours per year on routine tasks like reports and scheduling ^[1]. Big companies also use AI to speed up supply duties – Starbucks now uses an AI-based scanner to count store inventory much faster ^[1].

In other words, computers can do a lot of the boring paperwork (and even warn about low stock) so managers have more time to focus on bigger decisions. Government data supports this: the U.S. Bureau of Labor Statistics notes that AI can take over some paperwork, but managers will then spend more time on planning and people skills rather than lose their jobs ^[2]. In practice, things like setting goals or designing office space still need human judgment.

And tasks like hiring or firing people are handled very carefully – AI can screen resumes or suggest candidates, but humans make the final call (and must watch out for bias) ^{[3] [3]}. In short, AI tools are already automating bits of admin work (reports, schedules, inventory checks) and helping managers be more efficient, but they work alongside people, not instead of them.

Whether companies adopt these AI tools quickly depends on many factors. On the plus side, the tools are now widely available and can save money – a little software training can save hundreds of work hours ^{[1] [1]}. In fact, a study showed that just teaching workers to use AI made older, non-tech staff jump from 17% to 56% daily AI use within months ^[1].

Also, many managers want to keep people in charge of real decisions. One survey found over half of managers see AI as a helper and do not want to replace employees ^[3]. On the “slow” side, hiring rules and fairness concerns make companies cautious about using AI for people decisions ^{[3] [3]}.

Plus, implementing AI can have upfront costs and requires training. Overall, experts note managers’ jobs are fairly safe: their complex, people-oriented skills are hard to automate fully ^{[2] [3]}. So companies tend to use AI where it makes sense (like automating routine reports or scheduling) and keep humans in charge of the tricky parts.

The result is a mix of AI-augmented tools and human leadership, which can help workers do their jobs better without being replaced.