AI Strategy and Delivery Lead

Role Overview

AI is easy to pilot and hard to embed. This role exists to close that gap. We’re looking for an individual who can walk into a room of senior stakeholders, gain alignment on what AI should and shouldn’t do, then make sure the resulting tools are adopted, governed, and trusted by the people using them every day.

1. Sets the direction. Works with leadership to figure out where AI creates real value across the organization, then turns that into a prioritized, realistic roadmap, weighing impact against risk, complexity, and whether teams are actually ready to change how they work.

2. Gets the org to move. Many organizations are complex, global, and matrixed, which means this role can’t rely on top‑down authority. Success looks like building genuine agreement across business units, IT, HR, and other internal departments. Running the workshops, doing the translation between technical and business language, and designing the training and change management that makes adoption stick.

3. Deploys and governs. Owns the backlog, facilitates user story development, manages the pilots‑to‑scale pipeline, all while making sure everything that goes live meets the bar on ethics, privacy, legal, and security. This includes staying ahead of the risks that come with the territory: bias, deepfakes, data leakage, and third‑party exposure.

Underneath these layers lies a constant thread of measurement. This role is accountable for proving AI is working, not just that it’s deployed. That means real KPIs, usage data, and regular reporting to leadership and governance forums, not vanity metrics.

• Rolling out enterprise copilots and AI assistants
• Making knowledge easier to find (enterprise search, knowledge management)
• Automating workflows, including agentic AI where it fits
• Multilingual/translation support
• Meeting summarization and action‑item tracking
• AI‑assisted review of policy and documents
• Service desk automation
• Augmenting cyber security and threat intelligence work

You’ve done this before, in some form. You’ve been a Lead or Product Owner who has actually deployed enterprise technology, not just written specs for it.

You know AI well enough to be useful, not just conversant. Generative AI, copilots, agents, automation, LLMs: you understand what they’re good at and where they break down.

You’ve operated in messy organizations. Global, multi‑stakeholder, competing priorities: you know how to build consensus when you don’t have authority to just mandate a decision.

You can run agile delivery without needing someone else to manage the process.

You can hold your own on governance
. Data privacy, security principles, and the practical realities of managing AI risk in a regulated or reputation‑sensitive environment.

Temperamentally. This role rewards people who are pragmatic over perfectionist, genuinely comfortable in ambiguity, build relationships, and able to simplify without dumbing down. You’ll need the judgment to know when to push and when to listen, and the confidence to challenge leadership when the data says something different than what they expect.

• There’s an agreed to roadmap that leadership actually refers back to, and that gets updated as priorities dynamically change
• At least a handful of use cases are live, adopted, and demonstrably valuable
• A governance model and adoption framework exist and are actually being used, not just documented
• AI literacy across teams has visibly improved
• Manual, duplicated work has measurably decreased
  
  Leadership has clear, ongoing visibility into value, risk, and adoption

Flexible work from home options available.