About
Quaie is a role-based predictive intelligence company focused on how AI adoption decisions form inside enterprises
We capture how organisations decide to adopt AI before outcomes are visible, and examine what those early decisions reveal about direction, timing, and organisational alignment. The work is structured and longitudinal. It is tied directly to executive decisions on investment, capability, and timing rather than vendor claims or lagging metrics.
We exist to answer six executive-grade questions:
Where is AI already creating repeatable economic value?
Which roles lead adoption and which reliably follow?
Where will internal misalignment slow or block progress?
When does organisational consensus make action rational?
How aligned is the leadership system on AI strategy?
Which leadership roles most strongly influence adoption decisions?
These are leadership decisions that ultimately determine capital allocation.
They shape when organisations invest, how they deploy resources, and whether artificial intelligence becomes a source of durable advantage or fragmented experimentation.
The Blind Spot
The trillion-dollar AI industry built an ecosystem where every participant is incentivised to sell into organisations without measuring whether those organisations can absorb what they’re being sold.
Venture capitalists need adoption to accelerate. Vendors need deployments to scale. Consultancies need engagements to close. Analyst firms need enterprise-level snapshots to renew. Each produces genuinely useful insight within its own frame. None is structured to measure the organisational coordination dynamics that determine whether AI investment succeeds or fails.
Quaie exists to build that measurement layer. The bigger AI spending becomes, the more valuable it becomes, because the larger the investment, the higher the cost of getting the coordination wrong.
The Time Scale
AI is the fastest-adopted consumer technology in history. But organisational AI adoption, the kind that requires cross-functional alignment on value, risk, and timing, follows a fundamentally different pattern. Ninety-five per cent of enterprise AI pilots fail to reach production. Nearly two-thirds of organisations remain stuck in experimentation. The binding constraint is not the technology. It is the organisation itself.
This pattern mirrors every comparable transformation of the past century. Electricity, telecommunications, digitalisation, each took decades to move from available technology to embedded organisational capability. AI is following the same trajectory, not because leaders are failing, but because the coordination required across roles, functions, and decision-making structures is irreducibly complex and cannot be compressed on demand.
Quaie is built for this timescale. Every element of its methodology, from role-based measurement to longitudinal repetition to quarterly compounding, is designed to produce intelligence that becomes more valuable over time, not less. The dataset that begins in Q1 2026 is the first wave of a system intended to track, explain, and ultimately predict how organisations navigate AI adoption over the years and decades ahead.
How It Works
We continuously collect structured responses on adoption, budget, readiness, governance, and conviction from senior decision-makers across ten C-suite functions at mid-to-large enterprises. Those role-level signals are analysed through six proprietary instruments: the Role Shift Index, Role Lead-Lag Ranking, Organisational Adoption Gradient, Consensus Formation Time, Role Alignment Map and the Role Influence Index. The output is The Role Layer Intelligence Quarterly, Quaie's quarterly predictive intelligence report.
Our intelligence is:
First-party and human-sourced
Role-focused and longitudinal
Decision-oriented, not descriptive
This methodology distinguishes Quaie from trend newsletters, vendor benchmarks, and generic research. We measure how decisions form and when rational action becomes visible.
A detailed explanation of our approach is available on our Methodology page.
Authorship
Quaie’s founding editor is accountable for the design, analysis, interpretation, and editorial direction of all research and published work.
Quaie is intentionally small at launch. Its first phase is focused on establishing a rigorous longitudinal dataset and an independent analytical framework before expanding research and editorial capacity.
About the Founding Editor
Simon MacTaggart is the Founding Editor of Quaie and the creator of the Role Layer Intelligence System.
He has worked across strategy, brand, and creative execution for global organisations including Nike and Honda, developing a career-long fascination with a question that most strategy frameworks avoid: why do organisations with equivalent resources and intent reach fundamentally different outcomes when absorbing new ideas and technologies?
That question produced a thesis. Enterprise technology adoption does not fail at the organisational level. It fails at the role level, in the gap between the function that has reached conviction and the function that has not yet seen the evidence that makes commitment rational. That gap is the Role Layer. Quaie exists to measure it.
Simon is based in the United Kingdom. The Role Layer, his first book, publishes in 2026.
How Quaie Is Built
Quaie's research methodology, analytical frameworks, and editorial judgement are entirely human. The Role Layer Intelligence System, comprising the Role Layer Analytical Framework, the Role Layer Dataset, and the Role Layer Executive Survey, represents original intellectual work by the founding editor. The six constructs of the Role Layer Analytical Framework, the role-layer thesis, and the case study analysis that grounds it are proprietary to Quaie. The framework is described in full on the Methodology page.
All fieldwork is human. The survey is designed and analysed by the founding editor. Every response is collected directly from senior decision-makers through Quaie's own always-on research programme. No panel providers. No incentivised completions. No third-party aggregation. Most intelligence on enterprise AI adoption is derived from commissioned panels or periodic sweeps of externally sourced respondents. Quaie's dataset is proprietary, continuously built, and compounds in analytical value with every quarter of responses added. The C-suite executives in this dataset chose to contribute. That distinction is the foundation of everything the Role Layer Intelligence System produces.
Written materials are authored by the founding editor with AI used as an editorial and production tool. Not as a source of ideas, analysis, or judgement. Audio briefings are produced using AI-generated narration, editorially controlled by the founding editor.
Every claim is independently sourced and endnoted.
We believe this approach will become standard across the intelligence industry. It allows Quaie to operate as a lean, focused research operation, directing resources toward what matters most: the quality of the dataset and the signals it produces.
Quaie believes this represents responsible use of the technology it studies.
Intellectual Foundations
Quaie’s work builds on the research and thinking of those who mapped the territory before the role layer became visible.
Tom Davenport’s decades of work on how organisations compete on analytics established that technology adoption is an organisational challenge long before AI made it urgent. Erik Brynjolfsson and Andrew McAfee’s research on why some organisations capture value from technology and others don’t is the question Quaie attempts to answer at the role level.
Rita McGrath’s writing on strategic inflection points shaped how the founding editor thinks about timing and conviction. Ethan Mollick’s work on how AI reshapes organisations gave the field both rigour and accessibility.
Amy Webb’s methodology for identifying signals before they become trends influenced how Quaie’s instruments were designed. Gary Hamel’s argument that organisational structures are the binding constraint on human capability is one this work extends to technological capability.
Their work made ours possible.
Standards & Governance
Quaie publishes its research under a defined set of methodological, ethical, and editorial standards.
Methodology: how data is collected, analysed, and interpreted
Research Ethics: how contributors and organisations are protected
Editorial & Commercial Independence: how editorial judgement is insulated from commercial influence
Name & Mark
The name Quaie reflects the field the company is built to study: the quantitative understanding of artificial intelligence in enterprises. The mark encodes the same idea: judgement guiding organisations through stages of AI adoption, without prescribing outcomes or fixed frameworks.
A fuller explanation of the name, mark, and their relation to Quaie’s methodology is available in Mark & Meaning.
Who It’s For
Quaie is designed for senior decision-makers responsible for direction, investment, and organisational alignment, including:
Chief Executive Officer (CEO), Managing Directors, and Founders
Chief Technology Officer (CTO) / Chief Information Officer (CIO), IT Directors, and senior technology leaders
Chief Operating Officer (COO), Operations Directors, and operations leaders
Chief Financial Officer (CFO), Finance Directors, and senior finance leaders
Chief Marketing Officer (CMO), Marketing Directors, and senior marketing leaders
Chief Revenue Officer (CRO) / Chief Sales Officer (CSO), Sales Directors, and commercial leaders
Chief Data Officer (CDO), Data Directors, and senior data leaders
Chief Information Security Officer (CISO), Security Directors, and senior security leaders
Chief Human Resources Officer (CHRO) / Chief People Officer, HR Directors, and senior HR leaders
Chief Legal Officer (CLO), Legal Directors, and senior legal and compliance leaders
The work is also read by:
Investors and analysts seeking signal over noise in AI adoption
Journalists and editors looking for credible, first-party organisational insight
Mid-career operators and emerging leaders seeking to understand how senior decisions form over time
If you are responsible for direction, budgets, or execution, Quaie examines when AI adoption becomes organisationally rational rather than merely fashionable.
Platform & Distribution
Quaie operates as an independent predictive intelligence company. In its early stages, its work is published using Substack’s distribution and access infrastructure.
Substack is used to provide globally recognised payments via Stripe, secure access control, and a consistent user experience across regions, while allowing Quaie to focus on building its underlying dataset and maintaining research quality.
The choice of platform reflects a practical focus on research integrity and reach, rather than a statement about the long-term technology platform of the company.
Subscription Plans
Quaie publishes role-based predictive intelligence on how enterprises adopt AI, produced from live survey data and structured for senior decision-makers.
Free subscribers receive:
Essays and selected analysis drawn from ongoing research into role-based AI adoption in the enterprise
The Executive Summary of The Role Layer Intelligence Quarterly upon eligible survey participation
Paid subscribers receive:
The Role Layer Intelligence Quarterly. Four in-depth, board-ready reports per year grounded in live, role-based data from senior decision-makers across ten C-suite functions
The Role Layer Audio Briefings. Role-specific audio summaries of quarterly findings, tailored to your C-suite function
The Role Layer Annual Synthesis. A year-end synthesis consolidating four quarterly editions into a single, executive-level view of how AI adoption dynamics evolved across the year
Full access to the growing intelligence archive from day one, enabling longitudinal comparison and early visibility into emerging patterns and risks as they form
Together, these outputs provide early visibility into emerging patterns, risks, and opportunities, and a clear view of when AI investment becomes rational rather than premature.
Contact & Company Details
Quaie is published by Quaie Ltd, a company incorporated and based in the United Kingdom. Quaie Ltd operates as an independent predictive intelligence company.
Registered address:
128 City Road
London
EC1V 2NX
United Kingdom
General enquiries:
contact@quaie.io
How to Contribute
Your participation makes the intelligence possible.
Contribute your senior, role-level perspective through our structured survey and help shape the dataset that powers predictive insight.
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Subscribe to Quaie to receive role-based predictive intelligence on how enterprises adopt AI, capturing where real value is forming, where alignment breaks down, and when investment decisions become rational.
