Platform
Make Microsoft 365, Power Platform and Azure AI pay back
Assistants people actually use, agents that work across Teams, Outlook and line-of-business systems, and data controls that stop oversharing.
Last reviewed: 29 September 2026
90 days
to a measurable lift in weekly active use
Before rollout
oversharing risks identified and addressed
2–3
role-based workflows redesigned around AI
Typical target ranges, agreed at baseline.
Licences switched on. Habits unchanged.
Many organisations have rolled out Microsoft’s AI assistants to some or all staff and are now looking at usage reports with concern. Weekly use is uneven, a few enthusiasts drive most of the activity, and leaders cannot link the spend to any business result. At the same time, assistants surface documents that were never meant to be widely shared, and Power Platform apps and flows have spread without clear ownership.
- AI seats with low or uneven weekly use
- Sensitive files exposed to assistants through broad permissions
- Power Platform sprawl without environment strategy or ownership
Where AI pays back in Microsoft
| Use case | Business KPI | Maturity |
|---|---|---|
| Role-based assistant adoption (finance, sales, HR, operations) | Weekly active use, hours saved | Proven |
| Meeting-to-action workflows in Teams and Outlook | Follow-up time, missed actions | Proven |
| Process automation with AI document handling in Power Automate | Manual steps removed, cycle time | Proven |
| Custom AI applications on Azure | Task-specific KPIs | Proven |
| Internal service desk agents built in Copilot Studio | Ticket deflection, resolution time | Emerging |
| Agents connected to ERP and CRM through connectors | End-to-end cycle time | Emerging |
How we work in Microsoft environments
1
Assess
Usage telemetry, licence inventory, permissions and data exposure review.
2
Redesign & build
Role-based workflows, automations and agents, with controls configured.
3
Adopt & run
Enablement by role, adoption tracking and a quarterly improvement plan.
Controls in place before you scale
- Sensitivity labels and data-loss prevention configured before assistants are widened (Microsoft Purview)
- Identity and conditional access for users and agents (Microsoft Entra)
- Environment strategy, ownership and lifecycle rules for Power Platform
- Usage and adoption telemetry reported by role and team
Paying for AI seats nobody uses? Estimate your idle spend in two minutes.
See it in practice
Blueprint
Governed HR operations automation
Onboarding and compliance workflows automated across HR systems with Power Platform, with audit-ready records.
View the blueprint
Programs that start here
Platform ROI Recovery
Recover value from Microsoft 365 and AI licences you already own.
Cost Takeout & Productivity
Automate high-volume processes across Microsoft 365 and your ERP.
AI Risk & Governance
Configure the data and identity controls AI needs.
Questions about AI in Microsoft environments
How do we raise assistant adoption?
Link it to specific tasks in specific roles. We identify two or three high-frequency tasks per role, redesign them around the assistant, train people on those tasks, and track weekly use. Generic training produces a short spike; task-based redesign produces lasting habits.
How do we prevent oversharing through AI assistants?
Assistants respect existing permissions, so the fix is in permissions and labelling. Before wider rollout we review broadly shared sites and files, apply sensitivity labels and data-loss prevention, and tighten access where needed.
When should we build agents instead of using the standard assistant?
Build agents when a task is repeated, well defined and needs data or actions from specific systems — for example, answering policy questions or handling routine service requests. Use the standard assistant for open-ended personal productivity.
Can this reduce our licence spend?
Often. A usage baseline shows where seats are idle or where a different licence would serve a role. You go into renewal with evidence and a plan.
Make your Microsoft AI investment count
- 30 minutes with a senior lead
- No sales script — a working conversation
- A clear view of where AI can pay back first