AI Builder
Extract structured data from invoices, contracts, forms, and emails automatically. Replaces manual re-entry and reduces errors at the intake layer of any process.
White PaperPower Platform
When AI Meets Automation: Making Power Platform Intelligent
AI tools don't replace your business processes — they amplify them. This guide shows how Microsoft Power Platform and AI capabilities work together to eliminate manual work, surface insights faster, and build agents that actually fit how your organization operates.
Prefer to read offline? Download the full PDF version of this guide.
Download PDFThe Shift
Automation Was Step One. AI Is Step Two.
Power Platform gave organizations a way to standardize workflows, connect systems, and move work without waiting on IT. That was a meaningful step — but it still required humans to initiate, monitor, and interpret.
The next layer is intelligent automation: processes that don't just move work forward, but understand it. With Microsoft's AI capabilities now embedded directly into Power Platform — through Copilot in Power Apps, AI Builder, and Copilot Studio agents — the same infrastructure that runs your approvals and dashboards can now read documents, classify requests, generate responses, and surface recommendations.
The barrier isn't the technology. It's knowing which problems are worth solving with it — and which governance foundations need to be in place first.
Where AI Fits
The Four Layers Where AI Augments Power Platform
Not every process benefits from AI — and not every AI capability fits every workflow. Here's how the technology stack maps to practical impact.
Copilot in Power Apps
Users describe what they need in plain language and Power Apps surface the right record, action, or form — reducing training burden and speeding up task completion.
Copilot Studio — Agents that take action
Build AI agents that answer questions, initiate approved workflows, check status, and escalate exceptions — connected to your actual business data and systems.
Power BI + Copilot — Conversational analytics
Business users ask questions of their data in plain language. Insights surface faster, and the right people see them without waiting on a reporting cycle.
Use Cases
What This Looks Like in Practice
The most successful AI + Power Platform implementations start with a concrete, high-friction workflow — not a broad transformation initiative. Here are patterns that work across roles and departments.
Operations — Intelligent intake routing
AI Builder reads incoming requests (email or form), classifies by type and urgency, extracts key fields, and routes to the correct approval queue — without a human triaging the inbox. Pairs naturally with Power Automate flows already in place.
Finance — Invoice and contract processing
Documents are submitted to a Power Automate flow. AI Builder extracts line items and vendor data, flags exceptions, and pre-populates approval records — eliminating manual data entry.
IT & HR — Employee self-service agents
A Copilot Studio agent answers "How do I…?" questions, checks request status, and initiates approved actions like submitting a ticket or requesting access — reducing tier-1 support load.
Leadership — On-demand operational insight
Executives ask natural language questions against Power BI datasets connected to live workflow data. Approval backlogs, cycle times, and exception rates surface in seconds — not after a reporting cycle.
Before You Scale
Governance Comes First — Especially With AI
Power Platform governance matters for standard automation. It becomes non-negotiable when AI agents are in the picture. Agents that can read data, generate content, and initiate actions require tighter controls than a basic approval flow.
The honest reality: Most organizations that deploy AI agents without a governance foundation end up with agents that drift, produce inconsistent results, or access data they shouldn't. The fix is harder than the setup. See how TrellisPoint approaches Power Platform implementation with governance built in from day one.
- Define which data sources agents can access — and which are off-limits
- Establish human-in-the-loop checkpoints for consequential actions
- Set environment boundaries: dev, test, and production for AI workloads
- Monitor agent behavior over time — not just at launch
- Apply DLP policies that account for AI-connected connectors and external model calls
- Document ownership: who is accountable when an agent acts incorrectly
How to Get Started
A Practical Sequence for AI + Power Platform
The organizations that get the most value don't try to deploy AI everywhere at once. They pick one high-friction process, instrument it properly, and expand from a working foundation. Our Microsoft AI practice is built around exactly this approach.
The five-phase pattern below applies whether you're starting with a single Copilot Studio agent or a full Power Platform implementation.
Phase 1 — Identify
Find one high-friction, high-volume process with clear inputs and outputs. Approval workflows, intake routing, and document processing are common starting points.
Phase 2 — Govern
Set data access boundaries, environment strategy, and DLP policies before building. This is the step most organizations skip — and regret.
Phase 3 — Build
Deploy the AI capability with human-in-the-loop checkpoints and monitoring in place from day one, not bolted on afterward.
Phase 4 — Measure & Expand
Track cycle time, error rate, and adoption via Power BI, then repeat the pattern quarterly with a prioritized roadmap.
Why TrellisPoint
The Partner That Bridges Power Platform and AI
Most Power Platform partners know automation. Most AI partners know models. TrellisPoint sits at the intersection — with the Microsoft Solutions Partner designation, hands-on Copilot Studio experience, and a methodology built on making AI investments defensible to finance and operations leadership, not just IT.
- Grounded in real workflow analysis — not demo-ware
- Governance-first approach: agents built to last, not just launch
- Fixed-scope Power Platform implementations with defined outcomes
- Connects AI investment to measurable operational and financial outcomes via the AI Value Engine
- Works with CFO, COO, and CTO stakeholders — not just IT teams
- 17+ years of Microsoft implementation experience across Dynamics 365 and Power Platform
Get Started
Ready to Make Your Power Platform Intelligent?
Schedule a conversation with our team to identify where AI can have the fastest, most defensible impact in your workflows — and what governance foundations need to be in place first. No pitch. No demo. Just a real conversation about where you stand.