In my previous post, I described the gap between the AI conversation happening in the market and the AI reality inside most digital teams. The Monster of AI has arrived, but what makes it genuinely unsettling is the distance between ambition and operational readiness.

That gap is now being measured. Anthropic’s March 2026 Economic Index report - “Learning Curves” - finds something that should sharpen the urgency for every digital leader: the organisations benefiting most are not necessarily the ones with the biggest budgets or the boldest AI strategies. They’re the ones whose people have been using AI longest. High-tenure users are 10% more likely to achieve successful outcomes in their AI interactions, attempt more complex, higher-value tasks, and use AI more collaboratively - iterating alongside it rather than just delegating to it. Early adoption, done thoughtfully, is already compounding. The window to build that institutional experience advantage is narrowing.

The Monster needs training. So how do you go about it?

A Framework Built for This Moment

Digital experience transformation is hard. Success has always depended on three things working in harmony: design and usability that customers actually want, technical delivery that ships reliably, and digital operations that scale sustainably. Yet more often than not, teams operate in silos, with different priorities, different budget cycles, and rarely enough time to align. For organisations of scale, that operate across multiple markets, with complex integration and multilingual requirements, and digital teams spread across functions and continents, you can multiply hard by messy!

Now add AI - developing at exponential pace, generating enormous boardroom excitement, and creating an adoption gap between what leaders believe is possible and what is actually being deployed. Strategies are being built on hype and hope rather than evidence and pragmatism. We would usually see it as a normal part of the technology cycle, as Gartner would say, the ‘inflated expectations’ that precede the ‘trough of disillusionment’. But what AI is delivering is far from normal, and we see paralysis in some teams and reckless over-investment in others.

We have developed the AI DXPlaybook to draw a thread between customer experience, platform enablement, and operational readiness, with the intelligent integration of AI throughout - a lens applied consistently across the Digital Experience Lifecycle.

The Six Plays

The AI DXPlaybook is organised around six plays, each examining a distinct dimension of digital capability but together forming the end-to-end Digital Experience Lifecycle.

1. Business & Digital Context - the business context and potential IMPACT of AI - the ‘why’ that defines success combined with the possibilties of AI

2. Experience Research & Design - how user needs are understood and translated into compelling and engaging design

3. Experience Development & Delivery - how designs become deliverable digital experiences, reliably and at pace

4. Content Lifecycle & Omnichannel Orchestration - content operations that fuel consistent experiences across every channel

5. Customer Acquisition & Growth - how customers find and engage with digital touchpoints and how to elevate growth

6. Measurement & Optimisation - how performance is measured, iterated, and continuously improved

The Digital Experience Lifecycle - the end-to-end journey from business context and user understanding, through design and delivery, to content operations, growth, and measurement, is a cycle and not a sequence: the measurement of Play 6 feeds back into the business context driving Play 1, to continuously reshape digital strategy and the experiences that result.

A common failure pattern is organisations investing without the shared clarity we designed Play 1, Business & Digital Context to establish. This is why Play 1 matters so much - and why it’s where every engagement (should) start.

Play 1: Business & Digital Context - Start with the Why

Play 1 is the foundation on which everything else sits. It’s the ‘why’ - the clear definition of objectives and alignment on desired outcomes that is critical at the start but can be forgotten as projects gather momentum. Without it, solutions become commercially irrelevant. Every recommendation needs to link to measurable value and a credible business case. It also needs to be widely understood, across all departments and levels of seniority, to act effectively as the foundation for the solutions to be delivered.

Play 1 is structured around four key questions, each building on the last:

1. What is the influence of digital experience? How much value flows through digital channels and how can that be quantified?

2. What is the impact of AI on digital experience? Both externally - how is AI changing what your customers expect - and internally, where could AI transform your operations?

3. What are the opportunities? Uses the IMPACT AI evaluation framework to identify specific AI opportunities and understand how they can be adopted

4. What is the business case for investment? Builds an outline business case for each prioritised opportunity along with related risk factors and assumptions that require validation.

Our Play 1 template - a structured prompt framework that works through these questions systematically - is designed to be run with AI. It marks assumptions for clarification and generates an outline business casefor each opportunity. It can then be used to prepare for workshops to validate assumptions and align on the opportunities that digital experience and AI can generate. Use it to shape your own organisation's strategy, or analyse a competitor or even define a strategy for a business sector.

The IMPACT Lens

Our IMPACT framework is woven into every play as a lens for evaluating and prioritising AI adoption opportunities. Wherever we surface a potential AI use case, IMPACT provides a structure to assess it.

• Intent: What is the desired outcome and its business value?

• Multiples: How often does this occur, and what volume is involved?

• Platforms: Where does the relevant information live?

• Awareness: How can AI access the information it needs?

• Collaboration: How does human involvement improve quality and is oversight essential, useful, or not needed?

• Time: How long does the process take now and what difference can AI make?

Intent frames what success looks like and the potential benefits. Multiples looks at volumes and frequency. Platforms and Awareness map where the data dependencies live and how these will be integrated and accessed. Collaboration considers where human judgement is required and how it enhances outcomes. Time addresses the effect on how long processes take.

How to Get Started

The AI DXPlaybook is designed to be used iteratively, with AI as a working partner throughout. You initiate the process as follows:

1. Gather context: Collect annual reports, analytics, strategy documents, research - any information that will help inform the outputs. Load this into your AI tool of choice, e.g. into a 'Project' in Claude.

2. Run Play 1: Load the Play 1 template and prompt it to run the Business & Digital Context assessment using the template - adding further context or areas of focus should you wish. Assumptions are clearly marked ready for validation.

3. Validate: Use the assessment as a structured foundation for wider stakeholder engagement, replacing assumptions with validated data. Use workshops to build stakeholder consensus around priorities.

4. Build your AI DX Roadmap: Synthesise workshop outputs into a phased roadmap of initiatives supported by business cases and an AI adoption plan. Apply further Plays in accordance with the needs of each initiative.

We’ve designed the process to work for organisations at very different stages of AI maturity - from those still in the experimentation phase (the majority for now at least, as the Section data shows) to those ready to scale proven use cases. The starting point is always the same: honest assessment of where digital experience creates value, before decisions are made about where AI should accelerate it.

Beyond Play 1

AI is of course driving transformation in the methods and tools digital agencies are using to deliver services and interact with clients — from the way we conduct research and design through to how we build, deploy, and optimise digital experiences. In the coming weeks we will address these as we provide further insight through the subsequent Plays in the AI DXPlaybook.

The Window Is Now

Anthropic's research adds important texture to the urgency. The organisations seeing the most value from AI aren’t simply those with the most sophisticated tools - they’re the ones who started earlier and have had more time to develop the habits, prompting strategies, and organisational instincts that make AI genuinely productive. That learning curve is real, and it compounds. Teams that delay are not just behind today; they’re making it harder to catch up with every month that passes.

The Section proficiency data confirms most organisations are still in the experimentation phase. The digital leaders of the next few years will be those who moved from experimentation to structured adoption while others were scared of the Monster.

The Monster is here. It can be trained. We’re here to help.

Interested in an assessment for your organisation?

We run and facilitate structured AI DX opportunity assessments with digital leadership teams - focused working sessions that produce a prioritised opportunity roadmap and outline business case. If you’d like to explore what this would look like for your organisation, or get hold of the Play 1 template, fill out the form below.