Consultancy
Most marketing teams use AI for individual tasks. Few have changed how the work is organised. Inflexion redesigns operating models, agency structures and workflows so AI handles the intelligence and people make the judgements.
The problem
Tools have been layered onto the same teams, agencies and approval chains. The result is more output, with the same hand-offs and the same time to market.
Typeface survey of marketing leaders, 2025
Illustrative. Results depend on the organisation.
What we change
Most engagements start with one area. The work usually reaches the others, because each depends on the rest.
How marketing is organised, who owns which decisions and where AI changes the shape of roles.
Which work stays in house, which goes to partners, and how many agencies the brand actually needs.
How briefs, content, approvals and campaigns move, with the hand-offs that slow them removed.
Where agents, automation and synthetic audience research can replace manual work safely.
The data, measurement and governance teams need to act with confidence.
What sets the approach apart
Inflexion runs on the model it recommends. AI handles research, monitoring and reporting, and a senior team makes the decisions.
Strategy, prioritisation and decisions on budget, creative and channel.
Research, monitoring, analysis, reporting and first drafts, running every day.
Execution by the right specialist for each job, directed by one team.
Recommendations come from running AI enabled workflows every day, so they reflect what works in production.
Pilots are designed with the data, governance and ownership needed to move into everyday use.
Technology is recommended on fit, with no software of our own to sell.
Our approach
Four stages, each with a defined output. The work can run alongside existing teams and agencies.
Map how work actually happens across people, agencies, tools and decisions.
Define the target model, roles, partner scope and the AI steps in each workflow.
Test the new way of working on live campaigns and measure the difference.
Roll out across teams with training, governance and clear ownership.
Questions
Not necessarily. The review sets out which work belongs in house, with partners or with automation. Often the answer is fewer agencies with clearer scopes.
Sometimes, but most organisations already own tools they underuse. Workflow and ownership usually change before software does.
Every AI use case is assessed for data, legal and brand risk before a pilot, with governance built into the design from the start.
Yes. The work can run with current teams and agencies, or independently on a specific project such as an agency roster review.
A clear view of where time and budget go today, and what AI should change first.
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