AI Adoption & Governance
Turn AI pilots into governed ways of working
Most organizations have Rovo, Copilot, or both switched on. Fewer have decided where agents fit in delivery, who owns the decisions they touch, and how teams are trained and measured through the change. That is the work we do.
Why this matters now
Agents are already in your tenant
More than 90% of Atlassian enterprise cloud customers use Rovo, and Microsoft’s Copilot Studio ships multi-agent workflows with MCP connectors. Both platforms now provide agent inventories, permissions, and audit logs. Someone has to own them.
Regulators expect controls, not documents
Examiners and auditors in banking, healthcare, and government ask how AI use maps to NIST AI RMF, ISO/IEC 42001, HIPAA, and model-risk policies. A policy PDF is not a control.
Adoption is a change program
Teams do not adopt AI because it is licensed. They adopt it when roles, decision rights, and training change with it. We run that program.
What we deliver
AI readiness assessment and roadmap
Where AI assistants and agents fit in your delivery workflows, what data and permissions they need, and a phased adoption plan with measures.
Agent governance operating model
Agent inventory, ownership, permissions, approval workflows, and audit across Rovo Studio, Copilot Studio, and Agent 365.
Decision-rights and role design
Who approves, who supervises, and who is accountable when an agent acts, documented as RACI and built into the tools.
Guardrails and control mapping
NIST AI RMF and ISO/IEC 42001 aligned controls, mapped to HIPAA, model-risk, and procurement requirements for regulated environments.
Training and enablement
Role-based programs for executives, managers, agents builders, and end users, with adoption metrics reported monthly.
AI orchestration across platforms
One governance model for Rovo and Copilot, so the same rules apply whether the agent lives in Jira or Teams.
How an engagement runs
01
Discover
Interviews, usage data, and a risk-tiering of current AI use.
02
Design
Operating model, decision rights, controls, and roadmap.
03
Enable
Configure inventories and permissions; train roles; launch pilots.
04
Measure
Adoption, quality, and control metrics reported to leadership.
Frequently asked questions
The people-and-operating-model side of AI adoption: defining where assistants and agents fit in workflows, who owns the decisions they touch, and how teams are trained and measured through the transition. It is distinct from configuring the tools.
NIST AI Risk Management Framework and ISO/IEC 42001, mapped to the regulations our clients already answer to, including HIPAA, CMS, FFIEC guidance, and state AI laws.
Yes. As Atlassian specialists and a Microsoft Solution Provider we build one governance model that covers agents on both platforms.
Three to five weeks, ending with a roadmap, a control map, and a pilot plan your leadership can approve.
Ready to talk?
Book a 30-minute discovery call. No forms, no sales deck. We start with your situation and tell you plainly whether we can help.