A structured 8-session training program designed to move organisations from curiosity to confident, governed, measurable adoption across Microsoft 365.
Designed for enterprise reality — cross-functional teams, complex information estates, governed data environments, and executives accountable for measurable AI performance.
Deploying Copilot across departments with consistency and structure.
Needing clarity around data boundaries, risk, and responsible AI.
Demanding measurable ROI and visible adoption signals.
Embedding Copilot into real daily workflows — not experiments.
Measurable enterprise outcomes — aligned to governance, productivity, and executive accountability.
Each session is designed to produce a capability uplift and a reusable asset: standards, workflows, templates, and patterns your teams keep using after the series ends.
Establish how Copilot works in enterprise: grounding, permissions, Microsoft Graph context, and practical Responsible AI guardrails.
Build a repeatable prompting standard that scales across departments, with validation patterns for quality outputs.
Operationalise meetings and collaboration into trackable decisions, actions and follow-ups — consistently.
Reduce inbox friction with structured patterns for summarisation, drafting, tone alignment and follow-ups.
Produce better first drafts faster — with structure, audience alignment, and review techniques that reduce rework.
Use Copilot to accelerate analysis while maintaining trust: interpretation, validation and narrative framing.
Convert docs into executive-ready slides with narrative flow, summary precision, and speaker notes that land.
Move from training to operations: define champions, workflows, measurement, and a 30-60-90 day adoption plan.
Five-time Microsoft Most Valuable Professional (MVP) in Copilot and Azure AI, and founder of Archon Gnosis. Daniel advises enterprise and government organisations across Australia on secure, governed, and scalable AI adoption within Microsoft 365.
His work spans Copilot enablement, Azure OpenAI architecture, AI governance frameworks, information architecture optimisation, and enterprise AI operating model design — aligning AI capability to measurable executive outcomes.
This is not generic feature training. It is architected enterprise AI enablement — designed for governance, scale, and accountable adoption.
Enterprise Copilot adoption is not about switching features on. It is about designing structured, governed, measurable enablement aligned to executive strategy.
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