In-Housing AI

In-Housing AI draws on insights from over 30 global companies, captured using quantitative and qualitative methods from April to August 2025. It explores how in-house agencies are experimenting with, adopting, and integrating Gen AI across their workflows.

Key Takeaways:

• Gen AI adoption is widespread, but full integration remains rare
• Efficiency and speed are driving early use cases, while strategic applications lag
• Creative teams are leading the charge, but cross-functional adoption is uneven
• Governance, training, and tool selection are critical to scaling responsibly

Challenges with Integration

Findings from the report show that while 71% of in-house teams are implementing Gen AI in specific areas and 65% are actively experimenting, only 12% have fully integrated AI into their workflows. Integration challenges ranging from technical friction to organisational silos are slowing progress and limiting scale.

“AI can generate an image in three minutes, but if your legal approval process takes a week, you lose a week,” notes one WFA member who participated in the study, highlighting the need for systemic change beyond just tool adoption.

The Shift from Execution to Strategy

In-house agencies are currently leaning heavily on Gen AI for creative production, with 100% of respondents reporting faster production and 71% citing improved efficiency. However, strategic applications such as personalisation, insight generation, and campaign optimisation remain underutilised.

“Everyone wants to produce more content, but nobody can answer the question ‘Why?’” says one participant, pointing to a broader need for strategic clarity when it comes to Gen AI adoption.

Talent, Training, and Culture

The report highlights a shift in recruitment priorities toward adaptability and systems thinking. The hiring process is now expanding beyond narrow expertise. In-house leaders are seeking talent that bring the whole package, including domain knowledge, problem-solving skills, and the ability to build effectively build proficiency and literacy in adjacent fields. Training is also evolving, with companies embedding AI experimentation into performance goals and development plans.

Governance and Risk Management

As AI tools proliferate, governance is becoming a central concern. From IP and copyright risks to data privacy and brand consistency, in-house teams are building guardrails to ensure responsible use. Some brands are embedding governance directly into their tools, codifying tone, brand guidelines, and compliance into the AI systems themselves.

Five Areas In-House Leaders Must Manage for the Future

• Strategy must lead technology: AI should be aligned with business goals, not the other way around. Without clear KPIs and strategic intent, experimentation risks becoming aimless.
• Integration is the next frontier: Adoption is high, but integration is low. Connecting AI tools to enterprise platforms and workflows is essential for scale and consistency.
• Building AI-savvy capabilities: Key levers for success now include targeted capabilities like AI literacy, data fluency, and creative governance
• Pilot with purpose: While pilots are undoubtedly useful, prolonged experimentation without scale risks “pilotitis.”
• Governance is non-negotiable: From ethics to compliance, governance must be embedded from the outset. Cross-functional collaboration between legal, IT, and marketing is key.

Download the full report to explore the data, insights, and practical steps to help your in-house agency unlock the full potential of Gen AI.