About the role

AI Transformation and Enablement Manager accountable for making AI work at scale in a global performance media agency. Collaborating across media, data science, and technology to identify AI opportunities and automate workflows.

Responsibilities

You map how work actually flows across the agency — where time is spent, where handoffs break down, where decisions stall, and where the same effort repeats.
You bring process mining discipline to this analysis: decomposing workflows into their component steps, quantifying the cost of each, and identifying precisely where AI intervention creates the most leverage.
From the process analysis, you identify and prioritise the workflows best suited for automation.
You score opportunities by recoverable time and implementation effort, brief the implementation team to build in n8n, and sign off before anything reaches the people using it.
You are continuously scanning for AI opportunities that fall outside the automation backlog — the knowledge management problems, the information retrieval gaps, the workflow friction that structured tooling could solve without a custom build.
When a new need surfaces — from a team conversation, a champion observation, or your own analysis — you evaluate the right tool to address it.
You track usage and outcomes across everything deployed — automations, knowledge tools, AI-assisted workflows.
A significant part of this role is making good technology decisions quickly.

n8n — workflow building, reviewing, and quality sign-off
Genuine working fluency across the current AI tool stack
Hands-on tool evaluation — prototypes against real content before recommending
Prompt engineering — design and evaluate for specific, production-grade use cases
Claude Projects and custom AI workspace configuration and deployment
NotebookLM and knowledge synthesis tools
Google Workspace AI (Docs, Meet, Gmail AI features)
Structured data layers: Google Sheets, Notion API and webhook concepts in automation environments
Process mining — decomposes workflows into steps, identifies value loss, quantifies automation opportunity
Business operations experience — understands how agency functions actually work, not just how they are described
Workflow analysis and process mapping across complex, cross-functional operations
Leverage prioritisation — scoring and sequencing opportunities under time pressure
Technology selection judgement — matches tool to operational problem based on real testing
Brief writing — translates process analysis into tight, actionable implementation specs
Outcome accountability — tracks adoption and results, not just delivery
Change management — moves resistant teams from scepticism to habitual use
High-trust relationship building at every level of seniority
Clear written communication — briefs, process maps, recommendations, escalation documents