Commercial Real Estate has spent the last decade "digitizing" relationships: capturing contacts, logging calls, tracking deals, storing notes. That's what traditional CRM is designed for: a system you update.
But if I'm honest, that model is hitting its ceiling in CRE.
Not because CRMs are bad: because the work pattern is wrong for modern operations. CRE teams don't wake up excited to update fields. They wake up to a flood of signals: tenant emails, broker chatter, lease events, tours, expiring options, credit changes, pipeline slippage, commission questions, and internal approvals. The real cost isn't "missing data." The cost is latency: the time between something happening and the business responding.
AI-first, agentic systems flip the direction of value:
- Traditional CRM: the user updates the system so the system can report.
- Agentic operations: the system watches the work, updates the record, routes the decision, and updates the user.
That's the shift I care about: not "add a chatbot," but rebuild the operating rhythm so Dynamics 365 becomes a place where the business is kept current: proactively: without begging busy teams for admin.
The real transition: from "AI as a feature" to "AI as an operator"
Most teams start with what I call AI garnish: email summaries, meeting notes, "draft this response," or "summarize this lease abstract." Those are useful. They save time. But they don't change the system. They don't change throughput. And they definitely don't create an operating advantage.
Operator-level agents do something different: they don't just help a user write. They help the business run.
From the outset, we noticed that organizations achieving 41% higher revenue per sales representative weren't just using AI for content: they were using it to remove the administrative burden entirely. Agents were saving 15+ hours per week, not by typing faster, but by letting the system handle what used to be manual overhead.
Operator agents follow a clear pattern:
- Observe: They listen to signals across Outlook, Teams, SharePoint, and Dynamics activities.
- Interpret: They classify intent: leasing request, tenant issue, commission dispute, renewal signal.
- Act: They create or update records, trigger workflows, request approvals, and schedule follow-ups.
- Escalate: They hand off to a human when risk or ambiguity is high.
- Learn: They improve through feedback loops and outcome measurement.
That's the point where the system starts updating you.
The Microsoft stack is finally ready for this
When people talk about "agents," I see two mistakes immediately: treating agents like magic, or treating agents like chat.
In the Microsoft ecosystem, the winning path is almost always: agents + workflows + data discipline.
A practical agentic foundation in CRE uses:
- Dynamics 365 as system of record for deals, contacts, properties, tours, tenant requests, commissions
- Dataverse as the data backbone for consistent schema, security roles, and auditing
- Power Automate for deterministic workflow orchestration: routing, approvals, SLAs, notifications
- Copilot Studio to define the conversational layer, tool calling, and guardrails
- Azure OpenAI for LLM capabilities with enterprise controls
- Microsoft Graph to securely access M365 context where the work actually lives
If you only add AI on top of messy data, the agent becomes a confident liar. If you add AI with good orchestration and governance, it becomes a scalable operator.
Three agent patterns that change the game in CRE
1) The Operator Agent: Running the Playbook
CRE workflows are full of repeatable playbooks: new inquiry → qualify → schedule tour → send materials → follow-up → update pipeline. The problem is teams execute those playbooks inconsistently because they happen across inboxes, calls, spreadsheets, and tribal knowledge.
An Operator Agent isn't just answering questions. It's running the workflow.
Example: Leasing Intake Operator Agent
A prospect emails: "We're looking for 12k sq ft, need Q3 occupancy, parking requirements…"
The agent:
- Creates a Lead in Dynamics 365
- Extracts requirements into structured fields (sq ft, occupancy date, use case, budget)
- Finds matching properties from Dataverse
- Drafts a tailored response with options and suggested tour slots
- Assigns to the right leasing rep based on territory rules
- Sets follow-up tasks automatically
The difference isn't the AI-written email. The difference is the deal is now tracked without manual entry, the next steps are enforced, and ops leaders can measure conversion and cycle time.
We've seen this pattern handle 5x more leads daily compared to manual qualification, while reducing response times by over 50%. That's operator-level.
2) The Commission Agent: Payout Clarity
Commissions are where CRE operations goes to die.
Not because the math is impossible: because the data is fragmented: deal terms in one place, amendments in email threads, broker agreements as PDFs, payout schedules in spreadsheets, approvals scattered across Teams messages.
So what happens? At the worst possible time: when a deal is closing: people ask: "What's the commission on this?" "Who's the broker of record?" "Which split applies?" "Has it been approved?"
And then you get a week of chaos.
What a Commission Agent actually is
A Commission Agent is an explainable commission operator embedded in the workflow: not a calculator.
It provides:
- Instant answers ("what will I get paid and when?")
- Transparent reasoning ("based on term X and split Y and approval Z")
- Exception detection ("this amendment changes the basis; needs approval")
- Workflow execution (create commission record, route approvals, push to finance)
How it works in the Microsoft stack:
- Dynamics 365 holds the deal record and related parties
- Commission rules live as configuration tables in Dataverse or logic in Power Automate
- Documents (LOI, lease, amendments) are stored in SharePoint
- AI extracts the relevant fields: rate, term, triggers, caps, splits
- Agent produces a commission summary with citations back to source docs
- Approval workflow routes to the right manager or finance controller
- Final output integrates with the accounting layer
Outcome you can measure:
Fewer commission disputes. Faster close-to-cash. Less time spent reconciling "what changed." Reduced dependency on a handful of commission experts.
In CRE, "commission clarity" isn't a nice-to-have: it's a trust and velocity driver.
3) Micro-targeted Outreach Agents: Operational Assistants
"Outreach" in CRE often gets misunderstood as "send more emails."
That's not the goal. The goal is: make the right follow-up happen at the right time with the right context, without turning reps into admins or spammers.
A micro-targeted Outreach Agent is closer to an ops coordinator than a marketing tool.
What it does:
Instead of a generic sequence tool, it:
- Detects a trigger (tour completed, proposal sent, lease expiration window, tenant complaint resolved)
- Builds a micro-list of 5–20 highly relevant contacts
- Drafts messages tailored to context (asset, requirement, previous conversation, stage)
- Proposes next steps (schedule, send deck, request call)
- Logs and updates Dynamics automatically
- Stops outreach when signals indicate "not now"
CRE-specific triggers that matter:
- Tour happened, no follow-up in 24 hours
- Proposal sent, no reply in 3 business days
- Lease expiration 180/120/90 days with no renewal workflow started
- Tenant NPS dips or service tickets spike (risk of churn)
- A space becomes available that matches previously lost demand
The key is that outreach becomes a controlled operational process, not an individual habit.
Governance: avoiding agent chaos
Agentic systems scare leadership for good reasons: hallucinations, unauthorized actions, data leakage, audit gaps, inconsistent behavior across teams.
The fix isn't "no agents." The fix is explicit governance.
Here's the minimum viable governance I recommend:
1) Tool boundaries
What can the agent do vs. what must be human-approved? Example: agent can draft, classify, suggest; human must approve sending external comms or posting commissions.
2) Grounding + citations
Agents should cite the source: Dynamics record, SharePoint doc, email thread. If it can't cite, it should flag uncertainty.
3) Role-based access
Use Dataverse security roles and M365 permissions. Agents should not have "god mode."
4) Audit and telemetry
Every action logged: what changed, who approved, what inputs were used. This becomes your change control system.
5) Fallback paths
If confidence is low, route to a queue. "Safe failure" beats "silent wrong."
The bottom line: CRE leaders should demand systems that update them
If your Dynamics 365 environment still depends on humans to remember to log the call, update the stage, capture the requirements, chase the approval, and set the follow-up… then the business is operating on hope, not a system.
Agentic operations is how you turn Dynamics from a database into an operator:
- Fewer missed follow-ups
- Faster cycle times
- Cleaner data without "data entry initiatives"
- Fewer commission disputes
- More consistent execution across regions and teams
That's the promise: systems that update you, not systems you update.
About Dynamica Labs
At Dynamica Labs, we help teams already running Dynamics 365 and Power Platform get a "second wind": especially when adoption is lagging, processes are inconsistent, and the business wants to modernize without a full reimplementation.
Our sweet spot is AI automation and verticalization: taking real CRE workflows: intake, routing, approvals, extraction, follow-ups, commission clarity: and automating them end-to-end, securely, inside the Microsoft ecosystem.
If you want to explore what an Operator Agent, Commission Agent, or Micro-targeted Outreach Agent could look like in your environment, let's talk.
