AI ADOPTION NOTES
Content isn’t just outputs; it’s an organisational behaviour shaped by ownership, review paths and shared standards that decide how your voice shows up every day.
Content isn’t just outputs; it’s an organisational behaviour shaped by ownership, review paths and shared standards that decide how your voice shows up every day.
Most teams avoid the unglamorous workflow audit, but tracing what people actually do—step by step—before adding AI is the only way to build workflows that survive real‑world exceptions.
workflow-audit-article Read More »
Most teams get stuck in AI pilot mode; this piece shows how to design an AI operating model that turns one‑off wins into reliable, everyday work.
ai-operating-model-article Read More »
Most AI conversations start with “which tool?”, but the real leverage comes from mapping one critical workflow first so you cut tool sprawl and make better product decisions.
AI STRATEGY · ESSAY 02 Read More »
Many teams approach AI adoption as a tooling upgrade rather than a systems redesign. This article breaks down the most common mistakes—from fragmented workflows to lack of governance—and explains how organisations can move from ad hoc experimentation to structured, scalable AI enablement.
What most teams get wrong about AI adoption Read More »
Most AI adoption failures do not stem from weak models, but from broken workflows at the human-AI handoff. This article explores how unclear briefs, missing governance, and unprepared teams cause high-potential AI systems to fail—and how redesigning workflows, prompts, and operating models can turn AI into a reliable operational partner.
The Handoff Problem: Why Most AI Rollouts Fail Before the Model Does Read More »
A case study on building an AI-assisted content system for a professional services firm to scale thought leadership without overloading partners. By introducing structured templates, AI-assisted drafting, and streamlined review workflows, the system enabled faster publishing cycles, consistent quality, and a repeatable content engine aligned with high-trust expertise.
Designing an AI-Assisted Content System That Scales With the Practice Read More »
A case study on designing an AI-assisted Customer Success operating model for a mid-market B2B SaaS company. By consolidating fragmented AI tools into a coherent, human-in-the-loop system, this approach improved response consistency, reduced churn, and embedded governance directly into customer-facing workflows.
Designing an AI-Assisted Customer Success Operating Model Read More »
A practical case study on building a human-led AI content workflow for financial services teams. This framework shows how to balance automation with editorial control, enabling faster content production, stronger governance, and scalable AI adoption without compromising quality or compliance.
Turning a Stalled AI Pilot Into a Working Content Workflow Read More »
AI use case prioritisation for a mid‑size product organisation: moving from scattered AI experiments to a clear 12‑month roadmap with four high‑impact, governed use cases.
AI Readiness Audit: Prioritising Use Cases Across a Product Organisation Read More »