Everything we know, written down.
Practical guides on getting AI adopted - readiness, governance, change management, and how to measure whether any of it worked. Written for the people who have to make it land, not for the people who buy the licences.
Work out who does what, before you brief anyone.
Top AI partners for marketing and creative teams →
Five firms working with marketing and creative leaders on AI, what each one is best at, and how to choose.
AI change management tools and frameworks →
Prosci, Kotter, 7-S, and the adoption platforms - what each one is for, and the order to use them in.
AI change management software, compared →
WalkMe, Whatfix, Pendo, Prosci Hub, Bridge, Copilot adoption, AI spend trackers - what each platform is for, where it falls short, and the order to buy them in.
AI readiness assessment →
The six dimensions worth measuring, what good and bad look like in each, and how to turn a read into a 90-day plan your team will act on.
AI adoption strategy →
An eight-step guide to building an AI adoption strategy that actually changes how work gets done - and stays alive past the launch deck.
Generative AI adoption →
The three metrics worth measuring, the four most common stall points in marketing and creative teams, and a 90-day pattern that works.
AI transformation consulting →
An honest guide to the four kinds of firm, what each one is actually good at, realistic price bands, and how to brief the work.
AI change management framework →
The seven-layer loop - diagnose, decide, redesign, enable, govern, measure, re-read - and how it maps onto ADKAR and Kotter.
AI change management frameworks, compared →
ADKAR, Kotter, Lewin, and McKinsey's 7-S side by side - what each is built for, where each strains under AI, and how to choose.
AI implementation benefits and case studies →
The benefits that actually hold up, how to measure ROI, and the case-study patterns behind AI programs that moved an outcome.
The work itself: adoption, governance, measurement.
Robotic Process Automation Software →
RPA software automates repetitive tasks. But most deployments stall because adoption breaks around people. What to choose and how to design around it.
SMB AI adoption barriers: lack of experience →
Why lack of AI experience stalls adoption in Dutch SMBs, what really blocks momentum, and how to design change around real capability gaps.
AI governance business context and strategic visibility →
Why AI governance fails when leadership cannot see it. Build strategic visibility into how AI is adopted, used, and governed across the organization.
AI Governance News: What Leaders Need to Track →
AI governance news moves fast. This guide helps executives filter signal from noise and focus on changes that affect adoption, trust, and accountability.
AI transformation is a problem of governance →
Why AI stalls in most companies: weak governance, not weak technology. How to design decision rights, accountability, and operating rhythm around AI.
Make America AI Ready →
A guide for senior leaders on making organizations AI-ready through workforce capability, not just technology deployment. People before Process before Plat
AI governance that respects your business context and delivers accuracy where it matters →
How to build AI governance that respects your business context and delivers accuracy where it matters. Ground truth, not generic frameworks.
AI ROI Framework: How to Measure Real Value, Not Activity →
A practical framework for measuring AI ROI through alignment and value creation, not logins and licenses. Built for leaders accountable for results.
AI Transformation Roadmap →
A practical AI transformation roadmap that sequences people before process before platform - not a platform launch plan.
How to measure AI adoption in a large organization →
A practical guide for senior leaders to measure AI adoption in large organizations, from ground truth to behavior change, without vanity metrics.
How to measure AI adoption success →
A clear-eyed guide to measuring AI adoption for leaders who need honest ground truth, not vanity metrics. Written for accountability.
AI Operating Model: Redesigning Work When Machines Draft and Humans Decide →
How to redesign roles, decisions, and workflows when AI drafts and humans decide. A guide for senior leaders building a working AI operating model.
AI governance framework that enables adoption instead of blocking it →
Build an AI governance framework grounded in ground truth, designed around how people adopt, and focused on enabling work instead of controlling technology
AI governance quick wins: policy intake, risk tiering, and registry →
Build effective AI governance fast. Policy intake, risk tiering, and a working registry deliver clarity and control without paralyzing the business.
AI governance theater: what it is and how to avoid it →
AI governance theater creates the appearance of control without changing behavior. How to spot it in your organization and what real AI governance looks like.
AI governance tools: what they do and what they miss →
A plain guide to AI governance tools for leaders managing adoption. What they do, what they miss, and how to choose when technology is not the bottleneck.
AI Implementation Plan: Why Most Fail Before They Start →
Most AI implementation plans solve the wrong problem. Learn why ground truth comes before the launch - and how to build a plan that works.