One of the things that makes an agent more than a glorified macro is that it can prioritise - deciding what to tackle first when faced with several tasks. That autonomy is genuinely useful and genuinely worth watching, because how an agent ranks its work directly shapes the outcomes you get.
How agents decide
An agent prioritises based on the goals and rules you give it. Tell it to "resolve support tickets, urgent ones first," and it will judge urgency from the signals available - keywords, customer type, wait time - and order its work accordingly. The quality of that judgement depends heavily on how clearly you defined "important" in the first place.
Why this is powerful
Good prioritisation means the agent works on what matters, not just what arrived first - clearing the urgent invoice before the routine one, escalating the angry customer ahead of the calm query. Done well, this is where agents feel less like automation and more like a capable assistant, and it is central to what makes something agentic AI.
Why it needs oversight
The risk is that the agent's idea of "important" quietly diverges from yours. If your instructions are vague, it will optimise for the wrong thing - efficiently. Watch its choices early, especially on anything with money or customers attached, and refine the rules until its priorities match yours. This is the tuning work described in how much maintenance AI agents need.
Getting prioritisation right
- Define "important" explicitly - do not assume the agent shares your instincts
- Review its ordering early - check what it chose to do first, and why
- Keep humans over high-stakes calls - approval gates on the priorities that really matter
The bottom line
An agent's ability to prioritise is a real strength - but it optimises for whatever you told it to value, so define that carefully and watch it early. Learning to direct agent behaviour deliberately is part of the Strategic Application of AI in Business course at London School of Business UK. Enquire today.