From Training Completion to Readiness Evidence
A practical evidence model for moving beyond participation and completion toward application, system support and durable readiness.
Read Field Note 02 →Evidence before assertion
Research that sharpens the readiness question.
Translate IDEAS™ uses external research to understand the problem landscape, develops original readiness thinking in response, and identifies what evidence should be captured when readiness is applied in the field.
Published by Translate IDEAS™
From framework language to a body of practice.
These publications make our assumptions, model logic and research questions visible. They are designed to be read, challenged, used and improved through future field evidence.
AI Adoption Readiness
A five-dimensional approach to moving from AI access and experimentation toward responsible, confident and productive use.
Download the brief →Readiness Conversation Canvas
A structured conversation tool for defining the future state, surfacing friction and agreeing what evidence of movement matters.
Download the canvas →Readiness Framework™ Brief
A concise explanation of the five dimensions, the Discover–Diagnose–Design–Demonstrate journey, and the evidence discipline behind readiness work.
Download the brief →Culture OS™ Brief
Purpose, People and Standards; six behavioural levers; and a practical way to observe whether the operating system supports the culture being asked for.
Download the brief →The Readiness Gap
A research-led field note on the gap between individual capability and organisational readiness, with particular relevance to AI-enabled transformation.
Read Field Note 01 →Evidence standard
Three kinds of evidence. Never one blurred claim.
Credibility depends on knowing what a source actually supports. External studies inform the context. Translate IDEAS™ frameworks are our intellectual property. Field evidence must come from observable application, not invented outcomes.
Published research
Studies and reports that illuminate AI adoption, workforce readiness, leadership, culture, change and digital transformation.
Translate IDEAS™ research
Founder notes, framework briefs, field questions and hypotheses developed through the Readiness Framework™ and Culture OS™ lenses.
Observed movement
Signals, behaviours, decisions and outcomes captured when readiness work is used in real contexts. These become case evidence only when verified.
External evidence we are learning from
The readiness problem is bigger than training.
The sources below do not “validate” Translate IDEAS™ frameworks. They strengthen the case that AI and transformation outcomes depend on leadership, human capability, culture, organisational learning and readiness — not technology alone.
AI in the workplace: empowering people to unlock AI’s potential
The report examines technology and business readiness for AI adoption and argues that leadership is a major barrier even when employees are ready to use AI.
Read the source ↗AI at Work: Momentum Builds, but Gaps Remain
BCG reports that leadership support, access to the right tools and meaningful training are strongly associated with employee confidence and regular AI use.
Read the source ↗The State of AI in HR 2026
SHRM’s research provides a current benchmark for how HR functions and organisations are using AI, giving leaders a people-system lens on implementation and workforce implications.
Read the source ↗Organizational Digital Transformation Readiness
This peer-reviewed work explores how organisational readiness for digital transformation can be conceptualised, assessed and improved — reinforcing the value of treating readiness as a multidimensional organisational condition.
Read the source ↗Founder perspective
Why training completion is not readiness.
A point of view on the difference between learning activity and the conditions required for capability to become usable in real work.
Founder Perspective 01 · August 2026
Completion is evidence of participation. Readiness requires something more.
What changes when learning teams define the future behaviour, the application environment and the evidence before choosing the intervention?
Read the perspective →Translate IDEAS™ research agenda
Questions we intend to investigate.
These are research directions, not completed findings. Publishing them makes the intellectual agenda visible and creates a disciplined path from ideas to evidence.
Why do trained people still hesitate at the moment of action?
Exploring the gap between knowledge acquisition, confidence, environmental support and execution.
What makes AI capability usable rather than merely available?
Investigating the interaction between mindset, skill, trust, workflow design, leadership and governance.
Which system signals make desired behaviour become normal?
Examining purpose, leadership cues, standards, rituals, reinforcement and evidence through the Culture OS™ lens.
What changes when leaders are responsible for readiness, not just communication?
Studying how leaders create clarity, permission, practice and accountability during uncertainty.
How should employability readiness be evidenced beyond course completion?
Looking at confidence, work behaviours, decision quality, communication and applied performance.
What does readiness look like when access, context and opportunity are unequal?
Exploring how capability-building can translate into practical agency and sustainable participation.
Research should lead to better questions — and better decisions.
Explore the intellectual property behind our readiness work or see how readiness can be applied and evidenced in practical contexts.