How Josh Newman is turning work insights into practical AI guidance at WPP

The work began with a question from WPP’s board: what would the organization’s workforce look like as AI changed the business?

For Josh, answering that required a clearer understanding of the work behind WPP’s roles. Across a decentralized organization, job titles alone couldn’t provide that picture.

The business was already redesigning workflows through the technology it was building. Josh saw the implications extending into how teams were organized, what people needed to learn, and how their responsibilities might evolve.

Josh’s team partnered with an internal machine learning engineer to build a model using WPP’s job architecture and available workflow information.

The model helped consolidate approximately 55,000 job titles down to around 5,000. Further consolidation produced roughly 600 role archetypes, making the work easier to examine across the organization.

Changing employees’ job titles was not the objective. Josh wanted a clearer basis for understanding what people did and where AI could support their work.

The initial analysis connected tasks with broad categories of AI technology and estimated the capacity those technologies might create.

When the team shared the analysis, business leaders recognized the tasks. But they questioned how the capacity estimates had been calculated and what they were supposed to do with the findings.

That feedback exposed the gap between identifying potential and giving leaders practical direction.

Josh needed to deepen the validation and connect recommendations with WPP’s actual workflows and tools. The analysis had to help a leader understand what could change in their part of the business and how to act on it.

That became the turning point in WPP’s partnership with Reejig.

WPP worked with Reejig to validate the work in greater detail and develop playbooks incorporating its own workflows and technology.

The recommendations could then connect a particular role with relevant tools within WPP Open. That gave leaders more specific guidance than a broad suggestion to apply AI to a category of tasks.

The work also strengthened Josh’s contribution to conversations about business-model redesign. Understanding the work gave his team evidence to discuss how workflows, team structures, and employee development could change.

Estimated capacity gains helped inform those conversations. Realizing the opportunity would depend on how the work was redesigned and how people were supported to use the tools.

Josh’s focus extends to what changing work means for the employee journey.

As AI reshapes tasks, WPP is exploring how career development might evolve, including opportunities for junior employees to gain exposure to higher-level work through rotational programs.

Josh also sees a need to help clients understand and prepare for changes in how agency work gets delivered.

His approach connects those longer-term questions with a practical foundation: understand the work, validate the opportunities, and give leaders guidance they can use. The aim is to help people spend more time on meaningful work that benefits clients while developing the expertise their changing roles require.