Governed AI Automation for Dynamics 365
Buyers do not need an AI strategy. They need contained, auditable automations connected to throughput, accuracy, and cycle time. Every automation Kendra deploys is anchored to a measurable operating metric, carries a risk classification and a human-approval threshold, and is recorded in an automation register you can hand to an auditor.
Indicative planning range: $1,500–$5,000 / month as an add-on or bundled with managed support. Final pricing is confirmed after discovery.
Automation is applied where controls, approvals, logging, and operating boundaries are clear — inside the Microsoft stack the business already runs on.
Productized automations tied to a measurable operating metric.
Each pack is a defined scope with a defined control model, not an open-ended AI engagement. The metric ranges below are the indicative planning ranges published for each pack; actual results depend on volume, data quality, and current process maturity.
01 · AP invoice automation
Automated invoice capture, coding, and approval routing inside Business Central or Finance & Operations, with exception queues and human sign-off for high-value items. Indicative: 20–30% reduction in AP processing effort.
02 · Collections intelligence
AI-prioritized collections queue, automated dunning sequences, and aging exception alerts — so the team works the right accounts, not just the oldest. Indicative: 15–25% improvement in DSO.
03 · Sales and demand forecasting
ML-assisted pipeline and demand forecasts surfaced in Dynamics or Power BI, calibrated to your historical data and seasonality. Faster planning cycles, fewer inventory surprises.
04 · Service case triage
Intelligent case routing and sentiment classification for Field Service and Customer Service, with automated assignment, priority scoring, and SLA alert management. Faster first response, reduced manual triage.
05 · Month-end close acceleration
Automated reconciliation checks, journal entry validation, and close-status dashboards — so the team spends time analyzing rather than chasing open items. Indicative: 25–35% faster month-end close.
06 · Inventory exception management
Real-time alerts for stock-out risk, excess inventory, and slow-moving SKUs, with automated reorder suggestions in Business Central or Supply Chain. Reduced carrying cost, better stock availability.
Governance is part of the offer, not a policy document written afterwards.
Every automation deployed by Kendra carries a risk classification, defined human-approval thresholds, an audit trail, and a quarterly tuning review. We maintain an automation register for your records, so you always know what is running, who owns it, and what the exception handling looks like.
What every automation carries
- A risk classification agreed before deployment.
- A defined human-approval threshold for higher-risk actions.
- A complete audit trail of every action taken.
- Documented exception handling, including what happens when it fails.
- A named owner on the client side and on the Kendra side.
- A quarterly tuning review against its stated operating metric.
Where the line sits
- AI accelerates workflow, extraction, and prioritization.
- AI does not replace financial control logic.
- Core accounting rules, approvals, and system-of-record integrity stay anchored in the ERP.
- Human approval stays in the loop for higher-risk accounting actions.
- Privileged financial, configuration, and security changes remain under formal change control.
- Data grounding and role design come before deployment, not after.
Automation without uncontrolled production risk.
Approved actions only. Allowlisted remediation. Rollback rules. Validation before closure. An audit trail for every action. Being explicit about the ceiling is what makes the floor defensible.
Grounded answers, structured diagnosis, and recommendations. No production action is taken.
Approved scenarios only, executed through controlled actions with validation before closure. This is the immediate target.
Production remediation through approved runbooks and APIs, for tightly scoped use cases with rollback rules in place.
Explicitly not the operating model. Unrestricted production change is not something Kendra deploys.
Lead the AI conversation before the business asks.
For many CIOs the pressure has shifted from keeping systems running to showing where AI can improve the business. Boards and CEOs often know AI matters before they know what should actually be done. The readiness assessment turns that into a governed, prioritized answer.
What the assessment establishes
- D365 readiness: whether systems, data, integrations, and controls can support practical AI.
- Workflow friction: where teams lose time to manual work, repeated errors, and avoidable handoffs.
- An AI opportunity pipeline translated from support patterns and business pain.
- Executive priorities: a clear, governed set of next moves for the CEO, CFO, COO, or board.
- Data grounding gaps: identifiers, master data, and business context AI would need.
- A first-wave list separated from later-wave opportunities.
What it deliberately avoids
- Chasing every AI request that arrives from leadership.
- Broad transformation decks with no execution path.
- Automation on top of data the business does not trust.
- Unbounded production autonomy.
- Automations with no named owner and no tuning cadence.
- Claims that cannot be measured against an operating metric.
What CIOs and CFOs ask about AI in the ERP.
Is this Copilot, or something else?
How do you stop AI from touching financial controls?
What is an automation register and why does it matter?
Which use case should we start with?
Are the percentage improvements guaranteed?
What happens if an automation starts producing bad output?
Want AI automation that will survive an audit?
Start with a readiness assessment: whether your systems, data, integrations, and controls can support practical AI, where workflow friction actually sits, and which use cases are worth doing first.