From Experimentation to Enterprise AI

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.