Case Studies.

A PiAI Case Study

From Experimentation to Enterprise AI

A comprehensive case study describing how PiAI supported an international media organisation to adopt AI safely, ethically, and pragmatically at scale combining strategy, governance, and hands‑on delivery.

The Client

This international media and entertainment organisation operates across scripted drama, unscripted, documentaries, and entertainment formats. With teams distributed globally, it works across multiple languages, cultures, and production models, balancing creative freedom with commercial, legal, and reputational considerations.

As AI tools became more accessible across the organisation, leadership recognised the need for a coordinated, ethical, and operationally effective approach to AI adoption one that could scale globally while still delivering tangible value to teams on the ground.

The Challenge

AI adoption had begun organically across teams, driven by immediate needs and local experimentation rather than a shared enterprise strategy. While Microsoft Copilot licences were already in place, there was limited organisational readiness to use them safely, consistently, or to their full potential.

Key challenges included:

No global AI strategy defining when to use AI, automation, or traditional approaches.
Inconsistent use of generative AI tools, often without appropriate safeguards.
Copilot licences available, but no structured readiness, rollout, or enablement plan.
Growing concern around ethical use, data protection, and reputational risk in a creative industry.
Fragmented experimentation across teams, with no central visibility, prioritisation, or shared learning.
Internal teams under pressure, with limited capacity to design, build, and iterate AI solutions alongside day‑to‑day delivery.

The organisation needed to move from ad‑hoc AI usage to a controlled, enterprise‑grade operating model, while still delivering real outcomes and momentum.

Our Solution

PiAI partnered with the organisation to design and actively embed a global Ethical AI and Governance model combining strategy, governance, change, and direct delivery support.

Rather than stopping at frameworks and policies, PiAI operated as an extension of the internal team, helping to progress real use cases, unblock delivery, and accelerate value where internal capacity or specialist expertise was constrained.

Key elements included:

AI Strategy and Decision Framework: Defined clear principles for when AI, automation, or non‑AI solutions were appropriate, enabling teams to make consistent, auditable, and defensible decisions.

Copilot Readiness Assessment: Assessed technical, security, data, and organisational readiness to ensure Copilot could be deployed safely and effectively translating findings into practical actions, not just recommendations.

Governance & AI Register: Established a formal AI register capturing use cases, approvals, risk assessments, ownership, and delivery status, providing global visibility of both experimentation and live solutions.

Policy & Guardrails: Developed pragmatic AI usage policies aligned to the organisation’s creative culture and group‑level governance requirements, ensuring guidance was usable in practice, not theoretical.

Request Intake, Backlog & Delivery Management: Introduced a structured intake and prioritised backlog for AI and automation requests, replacing ad‑hoc experimentation with controlled progression.

Hands‑On Delivery & Development Support:

Shaping and refining use cases into deliverable solutions
Feasibility assessments of off the shelf solutions and products
Designing and building shared Copilot prompts, agentic workflows, automations and AI point solutions
Developing proof-of-concepts and production-ready solutions
Progressing backlog items during gaps in internal availability

Targeted Tooling & Point Solutions: Supported the use of Copilot, automation, and targeted point solutions where appropriate, rather than enforcing a one‑size‑fits‑all approach.

Global Knowledge Enablement: Delivered multilingual solutions enabling global drama and documentary teams to share knowledge safely and consistently.

“PiAI helped us move from fragmented experimentation to a coherent, responsible AI operating model and crucially, helped us turn ideas into real outcomes. Their combination of governance, strategy, and hands‑on delivery gave us confidence and momentum to move, pace and stay competitive.”

– Head of Innovation and Product

The Process

PiAI introduced a structured but flexible operating model that allowed AI adoption to scale without losing control or delivery pace:

Strategy Alignment: Agreed global principles for ethical AI use, creative protection, and acceptable risk.

Use Case Intake & Backlog: AI and automation ideas captured through a formal request process, assessed, prioritised, and actively progressed, not left idle.

Governance Review: Each use case assessed, approved, and logged within the AI register, aligned to risk, impact, and delivery complexity.

Design & Build: PiAI supported solution design and development directly where needed, ensuring ideas translated into working outcomes.

Tool Selection: Decisions made on whether to use Copilot, automation, or targeted point solutions based on suitability, not convenience.

Controlled Rollout Plans: Rollout agreed per team and region, avoiding blanket enablement and ensuring readiness before adoption.

Forums, Surgeries & Delivery Support: Regular forums and drop‑in surgeries enabled teams to raise concerns, test ideas, and receive hands‑on support to move work forward.

Feedback & Iteration: Ongoing refinement of guidance, tools, and solutions based on real usage, delivery experience, and feedback.

AI Governance & Ethical Oversight

Operating within a wider group structure, governance alignment was essential. PiAI worked closely with legal, technology, and business stakeholders to:

Align the operating company’s AI approach with group‑level governance and ethical standards.
Define clear ownership and accountability for AI use cases.
Provide audit‑ready visibility of AI adoption and delivery progress across global teams.
Embed risk‑appropriate controls without stifling innovation or delivery speed.

Change Management & Adoption

Rather than a single rollout, PiAI supported phased, confidence‑based adoption, reinforced by practical delivery. This approach built trust, reduced resistance, and prevented unmanaged “shadow AI” usage.

Phase 1

Leadership Alignment: Ensured senior stakeholders shared a clear understanding of strategy, risk posture, and delivery priorities.

Phase 2

Team-Level Enablement: Provided practical guidance, examples, and working solutions to demonstrate safe and effective AI use.

Phase 3

Surgeries & Open Forums: Created space for teams to ask questions, surface concerns, and receive real‑time support.

Phase 4

Incremental Capability Build: Internal teams progressively took ownership as confidence and capability increased, supported by PiAi during transition.

Outcomes & Impact

The transformation delivered both immediate and long-term enterprise value.

Immediate Outcomes

Reduced risk associated with unmanaged AI experimentation.
Clear, shared understanding of acceptable AI and automation use.
Tangible progress across prioritised AI and automation use cases.
Maintained delivery momentum despite internal capacity constraints.

Long-Term Outcomes

A scalable, ethical AI operating model embedded across global teams.
Improved decision‑making on when to apply AI, automation, or alternative solutions.
Increased internal capability, supported by real delivery experience.
A sustainable foundation for future AI initiatives.

Why PiAI?

The organisation selected PiAI for its ability to bridge AI strategy, governance, and hands‑on delivery within a complex, global, creative environment.

PiAI provided structure without rigidity — and crucially, did not stop at frameworks. By supporting real delivery, unblocking backlogs, and accelerating progress where needed, PiAI enabled the organisation to unlock AI value safely, credibly, and at pace.

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