Administrative Services Managers

Administrative services managers do a lot of routine tasks like ordering supplies and making reports. Many companies now use smart inventory systems to help with supplies. For example, one company used an AI forecasting tool and cut its warehouse stock by 43% ^[1].

Researchers note that office work often involves routine data tasks, scheduling, and managing supplies ^[2]. Tools like spreadsheets, calendar software, and AI reporting programs can gather data and even help write reports, saving managers time. By contrast, tasks needing judgment or creative thinking – like setting department goals or deciding to hire/fire someone – remain mostly human.

In fact, studies find that while up to 44% of routine admin tasks could be automated ^[3], no full-time administrative role is entirely replaced by technology ^[3]. We also found little about AI disposing of surplus office property; that usually needs human decisions about reuse or recycling. Overall, routine tracking and scheduling tasks are increasingly automated, but strategic decisions remain in human hands.

AI tools for admin work are widely available, so some offices adopt them quickly. Many talent-management and scheduling products now include AI features – for example, AI chatbots (like Paradox’s “Olivia”) can even handle parts of a hiring process, scheduling interviews and chatting with candidates ^[4]. Large organizations see big potential savings: one UK analysis estimated automating routine work could save around £36 billion per year ^[5].

Surveys also show most companies plan to ramp up AI use (92% say they will invest more), though only a few feel they’re “AI ready” yet ^[6]. However, adoption is slower for tasks that need trust and nuance. AI errors or biases are concerns (for example, AI-driven hiring can accidentally enable fake resumes ^[4]).

Managers often hesitate when immediate benefits aren’t clear ^[6]. Still, many workers already use AI tools and want more training. In short, tasks that are highly structured (inventory, data analysis) are easier to automate and see new tools quickly, while people-driven tasks (motivation, judgement) stay largely under human control ^{[6] [4]}.

Even as AI grows, human skills like leadership and problem-solving remain essential.