In organisations, many good ideas never go anywhere.
The technology works. The idea makes sense. The potential value is clear.
Yet the initiative quietly stalls.
This pattern appears everywhere: graduates entering the workplace, startups entering the market, new technologies entering organisations, consultants trying to turn expertise into clients.
The problem is rarely capability alone. The real challenge is whether that capability becomes legible, supported, and adopted by the surrounding system.
To understand this transition stage, I use a framework called SCRIPT.
SCRIPT describes the conditions that determine whether an initiative moves from potential to traction.
The Transition Problem
Many frameworks explain whether something should work.
For example, the Foundation Three examines data availability, strategic alignment, and economic value. These foundations determine whether an AI initiative makes sense in principle.
But even when the foundations are strong, initiatives can still fail.
Why?
Because organisations are social systems. Ideas do not spread automatically simply because they are logical or technically sound. Research on the diffusion of innovations shows that adoption follows a predictable social process — moving through awareness, interest, evaluation, trial, and only then adoption — and that this process can be accelerated or stalled at every stage depending on conditions within the social system, not the quality of the idea itself.
Ideas must become understandable, supported, trusted, visible, timely, and compatible with people’s identities and roles.
SCRIPT describes these transition conditions.
The SCRIPT Framework
SCRIPT stands for:
Sponsorship
Confidence
Repeated Proof (Proof Loops)
Identity Fit
Presentation (Legibility)
Timing
Each factor influences whether an idea gains traction within a system. Together they explain why some initiatives spread while others quietly fade away.
S — Sponsorship
Ideas rarely spread on their own.
In most organisations, new initiatives require someone with influence to support them. This support can take many forms: a senior leader championing the project, a manager allocating resources, or a respected colleague advocating for the idea.
Without sponsorship, even strong ideas struggle to survive.
Why Sponsorship Matters
Research on innovation champions — the people who actively promote new ideas inside organisations — consistently shows that their personal advocacy is one of the strongest predictors of whether an initiative survives early resistance. Effective champions do more than endorse an idea. They analyse key stakeholders’ interests, tailor their approach to each audience, and work to build support across the organisation rather than relying on a single point of authority.
At the executive level, sponsorship provides something even more concrete: the authority to allocate resources, remove obstacles, and align the initiative with organisational strategy. Without this, promising ideas are frequently displaced by competing priorities that have a named sponsor behind them.
The Sponsorship Question
A useful question is: Who inside the organisation is personally invested in this succeeding?
If the answer is unclear, the initiative may struggle to gain momentum regardless of its technical merit.
C — Confidence
For a new idea to spread, people must believe it actually works.
This belief rarely comes from theoretical explanations. Confidence usually develops through experience and observation — seeing the system produce reliable outputs, solve real problems, and improve actual work.
The Confidence Barrier
New technologies often face scepticism. People may worry about reliability, accuracy, unintended consequences, or job displacement. These concerns can slow adoption even when the technology performs well.
Albert Bandura’s research on self-efficacy — the belief in one’s ability to act effectively in a given situation — demonstrates that people need not certainty but sufficient belief to take action. Confidence matters not because it eliminates doubt but because it provides enough forward momentum to generate the first experiences that build real trust. Research on innovation champions also identifies self-efficacy as a key predictor of champion performance: the more confident the person advocating for the idea, the more likely they are to sustain effort through early setbacks.
Building Confidence
Confidence grows through small demonstrations, early successes, and transparent results. The key is allowing people to see the system working in practice — in their context, with their problems.
R — Repeated Proof (Proof Loops)
One successful experiment is rarely enough to create momentum.
Adoption usually requires repeated evidence that the initiative delivers value. These reinforcing demonstrations are known as proof loops.
What Proof Loops Look Like
A pilot project that saves time
A workflow that reduces manual effort
A chatbot that successfully answers customer questions
When these successes are visible and repeatable, they reinforce the belief that the initiative is worthwhile.
Why Proof Loops Matter
Diffusion research shows that adoption follows an S-shaped curve: it begins slowly, accelerates as evidence accumulates, and stabilises once the idea reaches critical mass within the organisation. The inflection point — where momentum shifts from fragile to self-sustaining — is driven largely by informal opinion leaders observing and talking about early successes. This means proof loops do not only convert sceptics. They generate the visible social proof that enables others to adopt without feeling like they are taking a personal risk.
Without these loops, initiatives remain theoretical. With them, a narrative forms: “This actually works here.”
I — Identity Fit
One of the most overlooked factors in organisational change is identity.
People adopt ideas more readily when those ideas align with how they see their role in the organisation. When an initiative conflicts with that identity, resistance can appear — even among people who intellectually support the idea.
Identity Conflicts
Research on professional identity threats and AI resistance identifies two distinct mechanisms at work. Threats to professional recognition — the feeling that expertise and status are being devalued — affect people’s sense of self. Threats to professional capabilities — the feeling that hard-won skills are becoming unnecessary — directly produce resistance to adoption. Both operate regardless of whether the technology is objectively beneficial.
Studies of digital transformation confirm the pattern more broadly. When new technologies change what people do each day, they can erode the professional identities that employees have built their sense of competence and meaning around. People who defined themselves as creative thinkers or skilled practitioners find that the technology does not reinforce that identity — it quietly replaces the activities that expressed it.
Identity Alignment
Adoption becomes easier when the initiative reinforces existing identities. Framing AI as an assistant rather than a replacement, or positioning automation as removing routine work rather than removing expertise, reduces the perceived threat to professional recognition. Research also shows that perceived identity enhancement through AI — the sense that the technology amplifies rather than diminishes professional capability — directly reduces resistance.
Identity fit determines whether people see the initiative as supporting their role or undermining it.
P — Presentation (Legibility)
Ideas must be understandable before they can spread.
In complex organisations, initiatives often fail because they are not clearly explained. This problem is known as legibility: how easily others can understand what the initiative is, what problem it solves, how it works, and why it matters.
The Legibility Problem
Technical explanations often create confusion rather than clarity. Terms such as AI models, machine learning pipelines, and prompt engineering make sense to specialists but remain opaque to most employees. In diffusion research, an innovation’s complexity — the degree to which it is difficult to understand or use — is consistently identified as one of the factors that slows adoption. The harder something is to explain to a colleague, the harder it is to adopt.
Improving Legibility
Clear presentation focuses on outcomes rather than mechanisms. Instead of explaining the technology, explain what changes in daily work, what tasks become easier, and what problems are solved.
When the idea becomes legible, others can evaluate it, talk about it, and support it. The ability to communicate an idea peer-to-peer is often what converts early adoption into broader momentum.
T — Timing
Even the best ideas can fail if introduced at the wrong moment.
Organisations move through periods of stability, change, and crisis. Timing determines whether people are ready to engage with a new initiative.
When Timing Is Wrong
Adoption becomes difficult when employees are already overwhelmed, when major organisational changes are underway, or when leadership attention is focused elsewhere. Dissemination research describes these conditions as closed windows: moments when even well-designed interventions fail to gain traction because the environment is not receptive.
When Timing Is Right
Conversely, timing can accelerate adoption when existing systems are failing, inefficiencies are widely recognised, or leadership is actively seeking solutions. Rogers’ diffusion framework identifies a related condition: when the pain of the current situation becomes sufficiently visible, organisations become far more motivated to adopt innovations that would have been ignored in a period of relative comfort.
Timing creates windows of opportunity. The skill lies in recognising when a window is open — and acting before it closes.
How SCRIPT Works as a System
The six elements of SCRIPT interact with one another.
An initiative gains momentum when several of these conditions are present simultaneously.
Sponsorship provides support and removes obstacles
Confidence builds willingness to act
Proof loops demonstrate and reinforce value
Identity fit reduces resistance
Presentation makes the idea understandable and referrable
Timing determines whether the environment is ready
When multiple elements align, the initiative can move from concept to adoption. When several are missing, momentum fades — not because the idea was weak, but because the transition conditions were incomplete.
SCRIPT and Technology Adoption
SCRIPT is particularly useful when examining how new technologies spread within organisations.
Technologies such as artificial intelligence often succeed technically but fail organisationally. The reasons frequently lie within the SCRIPT factors: no senior sponsor, employees who lack confidence in outputs, early experiments that remain invisible, AI framing that conflicts with professional identity, explanations focused on technology rather than outcomes, or an organisation not yet ready to change.
Understanding these dynamics helps explain why adoption can be uneven even when the underlying technology works — and why the same technology can flourish in one team and stall in another.
From Potential to Traction
SCRIPT does not determine whether an idea is technically viable.
Instead, it determines whether the idea becomes embedded in organisational practice. It describes the moment when capability must transform into momentum.
In this sense, SCRIPT addresses a universal question: Why do some ideas spread while others stall?
By examining sponsorship, confidence, proof loops, identity fit, presentation, and timing, organisations can better understand the forces that shape adoption. Only when these conditions align can new initiatives move from possibility to traction.