Microsoft is pushing AI hard right now, and it’s easy to see why. There are plenty of ways it can slot into day-to-day work, taking pressure off routine tasks and helping people move through their day with more confidence.
But of course, it’s not the answer to everything.
The conversation around AI can feel overhyped, hard to follow, and wrapped in jargon. It’s often presented as if simply switching it on will transform the way people work. The reality is much less magical. AI absolutely has its place in Microsoft 365, but the real value comes from knowing where it helps, and where it still needs careful handling.
Where AI helps
AI tends to work best when it’s supporting repeatable, predictable, low-risk tasks that already follow a clear process. These can include:
1. Communication
Drafting emails, tightening up wording, and pulling together internal comms are all useful areas. AI can work well when someone needs to turn rough notes or bullet points into something clear, quickly.
2. Meetings
Summaries, action points and follow-up notes are one of the clearest use cases. AI can reduce the admin that follows calls and meetings, making it easier for teams to focus on decision-making.
3. Document handling
Reviewing long files, extracting key points, and surfacing important information with AI can save time, particularly when teams are working across large documents or shared knowledge.
4. Productivity support
The strongest use of AI is often as an assistant rather than a replacement. It helps people complete tasks faster and organise information easily, removing small bottlenecks from the day.
Where AI struggles
Perhaps the most useful skill in using today’s AI is knowing where it starts to fall short. That’s where poor outputs, wasted time, and avoidable risk come in. Currently, AI typically struggles in the following ways:
- Understanding context: AI still depends on clear input. Without enough direction, it can misread intent, miss nuance, or produce something that sounds right but misses the point entirely.
- Reliability: It’s important to remember that outputs still need to be checked. AI can present incorrect information with complete confidence, creating obvious risks when people rely on it too heavily.
- Process following: While a human may be able to follow a workflow that’s slightly unclear, inconsistent, or poorly structured, AI can’t. It often amplifies the problem rather than attempting to solve the issue.
- Setup: AI still needs proper setup, the right permissions, and clear governance. Without that, outputs can become unreliable, and teams may start using it inconsistently or in ways that make work less clear.
There are risks to using AI, particularly when it’s introduced without sufficient controls. Poor permissions can expose information too widely, and it doesn’t take long for people to start trusting outputs without properly checking them. Bad information then feeds into real decisions.
A balancing act
A lot of Microsoft’s AI messaging can feel overwhelming at times, especially with so much jargon in use. But now that businesses are increasingly adopting AI, the conversation needs to be more accessible to the people who use it.
The core message is that the value is not in having AI switched on. It’s in knowing where it helps – and where it can create more friction than value.