Rethinking Agency Retainers in the AI Era: Ensuring Real Client Benefits

Traditional Retainers Under Pressure

Historically, agency retainers provided brands with guaranteed access to creative resources based on estimated human hours or dedicated personnel. This model worked when content production was heavily dependent on human effort. However, generative AI, which significantly reduces the time and effort required for production tasks, calls this approach into question.

Today, AI tools can dramatically enhance productivity—tasks that once required hours or days can now be completed within minutes. Consequently, traditional retainers based purely on time or human resources increasingly seem outdated. Forward-thinking companies rightly ask: If AI is making agencies significantly more efficient, should we still be paying the same fees?

Toward Output-Based and Performance-Based Models

As generative AI reshapes the production landscape, we’re seeing innovative agencies and brands transitioning towards output-based or performance-based compensation. Rather than paying for hours worked, brands pay for tangible deliverables and measurable results. This model not only rewards efficiency but also aligns agency incentives directly with client success.

Bain & Company suggests that as agencies automate their processes through AI, brands should reasonably expect reduced agency fees—potentially up to 20%. This reduction should not undermine agency profitability, but instead reflect shared efficiencies made possible by AI. Transparent conversations and renegotiations around this new reality are essential to maintaining fair and productive relationships.

Ensuring Clients Reap the Benefits

However, simply shifting compensation models is not enough. To ensure that the benefits of AI-driven efficiencies genuinely flow back to brands, several critical steps must be taken:

Demand Transparency: Brands must require their agencies to disclose explicitly when and how generative AI is used. Transparency ensures that costs are fair and reflective of actual work performed.
Update Contracts: Incorporate clear terms regarding AI usage, output-based pricing, and performance incentives. Clearly define expectations around AI-driven cost savings and increased content output.
Build Internal AI Knowledge: Develop internal expertise to effectively evaluate and manage agency proposals and AI-generated outputs. Internal knowledge empowers brands to engage critically and ensures agencies deliver genuine value.
Leverage Competitive Benchmarks: Regularly benchmark agency proposals against the market to ensure pricing fairness and transparency, encouraging healthy competition and optimal pricing.
Accelerate Workflows and Quality Checks: Insist on accelerated turnarounds enabled by AI, while maintaining rigorous quality and ethical standards. Brands should set clear guidelines for AI-produced content to safeguard brand integrity.
Collaborate Actively: Brands should actively engage with their agencies in piloting and optimizing AI-powered workflows, ensuring collaborative learning and continuous improvement.

Looking Ahead

👉 As we continue this series, my next article will focus on the new skill sets and team structures needed within organizations and agencies to fully leverage AI-assisted content workflows. Stay tuned!

Generative AI’s potential to transform the economics of content production is immense. Yet, without careful management and thoughtful recalibration of agency relationships, brands risk missing out on these opportunities. By embracing transparent, outcome-based compensation models and ensuring active collaboration, companies can guarantee that AI efficiencies truly benefit them—delivering greater value, faster results, and stronger brand consistency.