Director, Enterprise AI Transformation in London

Where the Role Sits

You will report to the Chief People & AI Transformation Officer and lead the enterprise AI transformation agenda across Cint. You will lead a small, high‑impact ATO team and work closely with:

• AI Workflow Transformation Lead – workflow redesign, co‑build sprint delivery and practical delivery coordination.
• AI Enablement & Adoption Lead – AI literacy, manager capability, adoption, playbooks and behaviour change.
• AI/Data Architecture capability – technical dependency for architecture, data readiness, build/buy/configure recommendations and integration design.
• Business Technology, Infrastructure, Legal, DPO and InfoSec – implementation, operational handover, security, data governance, GDPR, model risk and compliance gates.
• Functional AI Domain Leads – business‑side ownership, use‑case identification, local prioritisation and adoption.
• AI Transformation Steering Group – executive alignment, investment decisions, escalation and enterprise‑level prioritisation.

What You Will Own

You will own and maintain Cint’s enterprise AI transformation strategy and roadmap, aligned to business priorities and executive direction. You will identify where AI can create value across productivity, quality, speed, cost‑to‑serve, risk reduction, employee experience and operating leverage, and decide which opportunities enter the transformation portfolio, how they are sequenced, and where Cint should focus first.

You will own the AI Transformation Office operating model, including how work is prioritised, governed, delivered, measured and escalated. The ATO operates through three clear pathways:

• Enable– broad adoption, manager tools, playbooks, training and reusable practices.
• Guide– decision frameworks, guardrails, prioritisation, standards and governance.
• Co‑build– deeper support for complex, high‑value, cross‑functional or higher‑risk workflows.

Your job is to ensure each AI opportunity receives the appropriate level of ATO support based on value, complexity and risk.

You will prioritise initiatives based on business value, feasibility, risk, readiness and scalability. You will define success measures, track impact and ensure AI initiatives create measurable operating change – not just activity, usage or enthusiasm. You will challenge, reshape or stop work that is not delivering value.

You will be accountable for ensuring AI transformation work has clear outcomes, owners, governance, dependencies, adoption plans and measurement. You will hold the AI Workflow Transformation Lead accountable for practical workflow outcomes and the AI Enablement & Adoption Lead accountable for adoption, capability and behaviour‑change outcomes. You will surface blockers quickly and escalate decisions where delivery risk threatens business value.

You will own the executive narrative for enterprise AI transformation and prepare clear updates for the Chief People & AI Transformation Officer, CEO, Steering Group and Board: what has shipped, what value has been created, what is blocked and what decisions are needed. You will make AI transformation visible, measurable and credible at leadership level.

You will define common standards for AI transformation work, including intake, prioritisation, value cases, governance checkpoints, measurement and handover. You will ensure successful workflow patterns are captured, reused and scaled across the organisation.

AIT can enable, guide and co‑build AI‑enabled ways of working, but it cannot deliver sustainable enterprise impact without committed technical architecture and implementation capacity. You will work closely with Business Technology to ensure priority workflows have clear technical ownership, data readiness, integration paths, security input, governance gates, support models and production handover.

You will work with the AI Enablement & Adoption Lead and People team to make AI transformation a capability, not a series of projects. You will help leaders understand their role in sponsoring AI‑enabled change, support adoption rituals and success sharing, and ensure the human side of transformation is treated as core delivery work.

Who You Will Be / Requirements

Demonstrated experience driving large‑scale tech or operational transformations, specifically focusing on bringing legacy organisations forward into the modern tech era.

Experience in AI‑native companies or organisations recognised as early, aggressive adopters of AI.

You do not need to be a software engineer, but you must possess a deep, practical understanding of how AI works, its terminology and its architectural ecosystem.

You actively use and experiment with AI, building prompts, developing skills or deploying AI agents.

Ability to confidently partner with deeply technical leaders, understanding the practical "domino effects" of implementing AI, e.g. when you prompt X, Y happens; when deploying this agent, Z is the infrastructure impact.

Seamless comfort working in modern tech environments such as GSuite and Slack.

• Navigating Ambiguity: Comfort operating as a pioneer in an undefined, rapidly evolving space. You can build structure out of chaos.
• Change Management & Resilience: Proven ability to navigate organisational resistance. You know how to align traditional business units and deeply technical engineering teams with enthusiasm about change.
• Stakeholder Management & Critical Thinking: Sharp judgment and exceptional communication skills. You can manage complex relationships with senior European stakeholders and technical partners alike.

What Success Looks Like

Within the first 3 months, you will have established the enterprise AI transformation roadmap, ATO operating model, portfolio view, governance cadence, prioritisation framework and first wave of priority initiatives. Within 6–9 months, Cint should have visible AI‑enabled workflow improvements in priority areas, with clear adoption data, measurable value and board‑ready evidence of progress. Over time, you will help Cint move from scattered AI experimentation to AI‑enabled operating leverage: redesigned workflows, stronger capability, clearer governance, better tooling decisions and measurable improvements in how work gets done.