7 May 2026
Agency AI - Common issues to overcome
Use cases and concerns are far and wide, but some common themes emerge.
After running AI training inside a 60-person agency a few common themes kept arising, which reflects what many teams must be facing in getting the most out of AI tools.
AI adoption has accelerated rapidly across marketing agencies but the real challenge now is integration. Many are asking the same questions: Are we using AI as effectively as we can? Can we streamline processes further? Are teams using it consistently? And perhaps most importantly, are we still maintaining strategic thinking and real client understanding alongside automation?
I see these challenges falling into three key pillars for teams to tackle:
Governance
- Responsibility. Includes concerns around data security, compliance, and accuracy. Businesses want to understand what information can safely be entered into AI platforms.
- Human monitoring. Nothing leaves the building without human oversight, ensuring outputs remain aligned with genuine client context.
- AI policy. Every agency needs one, and it needs to accurately reflect usage.
Access
- Inconsistent workflows. Many marketing teams still only use a fraction of what AI platforms can actually do, and often go in different directions with siloed departments, with inconsistent access and approaches.
- AI confidence. As platforms evolve rapidly, teams are struggling to keep up and organise themselves effectively around AI adoption.
Realising efficiency
- Measuring improvements and setting KPIs. Pressure is shifting from experimentation to proving operational value as agencies look for measurable improvements.
- Continued training. Continual upskilling has never been more vital as the pace of change with AI tools exceeds previous software eras.
Ultimately, the agencies seeing the greatest success with AI are not necessarily the ones using the most tools. They are the ones building clear governance, shared processes, and practical workflows around them.