Over the past 18 months, the conversation around agency value has shifted dramatically. No longer is differentiation solely about capabilities, client roster, or margin profile. Acquirers are scrutinizing how agencies adopt, integrate, and operationalize AI and automation, not simply as tools, but as fundamental components of their delivery model. Those who are lagging are already facing compressed margins and commoditized service offerings; those who are leading are redefining what it means to scale creativity, strategy, and performance.
As an M&A advisory with deep operating experience, having personally built and exited agencies and services businesses, we are witnessing a clear delineation in how AI-readiness is impacting valuation. Below, we unpack the trends driving this shift, how they affect EBITDA multiples, and what founders / leaders must prioritize to remain competitive and valuable to customers and to retain and expand value through the lens of M&A criteria.
1. Key Trends in AI and Automation Reshaping the Agency Landscape
a. Generative AI in Content and Creative Production
The deployment of generative tools (e.g., Sora, Stability, Runway, Adobe Firefly) has dramatically altered the cost-to-output ratio. High-volume content creation, post-production editing, and adaptation for multiple platforms can now be semi-automated, reducing labor intensity and delivery timelines. Examples of additional platforms include:
- Skyword – A pioneer in content strategy and production at scale, Skyword leverages AI-enhanced editorial workflows and a global freelance network to drive brand storytelling efficiency. Their platform combines algorithmic editorial planning with human insight, bridging AI-generated outlines and performance-optimized narratives.
- Veylan – Veylan is pushing the boundaries of AI-assisted content operations with a platform that unifies strategic planning, brand governance, and automated asset production. Its strength lies in facilitating consistency and speed across complex, multi-brand portfolios.
b. Predictive Intelligence in Media and Performance
Machine learning algorithms are being integrated into media optimization, bid modeling, audience targeting, and real-time campaign adjustments. Platforms like Adgile, Scibids, and CreatorIQ enable agencies to drive better outcomes with fewer human interventions. Agencies such as PMG, Tinuiti, The Brandtech Group, and Mars United, represent the future driven by their investments in automation and agentic workflow.
c. Workflow Automation and Delivery Efficiency
AI-enhanced project management platforms (e.g., ClickUp AI, Notion AI) are improving internal operational efficiency across service delivery. These are shifting agency labor models away from a linear headcount model toward lean, tech-enabled delivery.
- Collective OS is an invite-only platform built for professional services and agency networks. It enables firms to extend capabilities and scale delivery without adding headcount by intelligently matching the right partners at the right time. This curated matchmaking model turns trusted relationships into operational leverage, accelerating project turnaround, unlocking new revenue streams, and strengthening competitive position.
- Veylan also plays a role here, offering intelligent orchestration capabilities that stitch together content planning, compliance, and production across internal teams and external partners—reducing manual touchpoints and improving turnaround cycles.
d. Custom AI Models for Client IP and Competitive Moats
Advanced agencies are training proprietary LLMs and prompt libraries using client data, enabling bespoke campaign ideation, sentiment analysis, and strategic recommendations, creating scalable intellectual property and defensible client lock-in. These agencies represent the “next generation” and most valuable companies both from a customer needs / demand perspective and valuation as clients mature in their understanding of value and Buyers recognize the implications of rapidly atrophying capabilities.
2. Implications for the Future of Agencies and Client Value
- Agencies are no longer service firms; they are platforms.
The most valuable agencies will be those that treat themselves as productized, AI-enabled service platforms. This enables faster onboarding, lower marginal costs, and higher throughput, representing the foundation for value creation and defensibility. - Client expectations are recalibrating.
Clients now expect faster insights, more creative options, and clear performance metrics with higher impact and return rates from agentic workflows. - The value narrative is shifting.
“AI-enhanced growth partners” appeal to buyers for their adaptability, scalability, and resilience, traits that lead to higher valuations.
3. The Impact on EBITDA Multiples
In our recent transactions and buy-side conversations with PE-backed holding companies, we observe a widening valuation spread based on AI adoption:
“What drives this disparity is not just cost efficiency, it’s scalability, margin expansion, and perceived resilience. Buyers reward predictability and margin leverage, and AI-enabled delivery unlocks both.”
– Bob Morris, Managing Partner, Bravery Group
4. A Mandate for Evolution: Rethinking the Agency Operating Model
AI is not simply additive; it is transformative. To sustain relevance and value, agencies must reimagine their core model:
- From billable hours to outcomes-based pricing
- From manual execution to AI-orchestrated delivery
- From people scale to tech leverage
- From isolated creative to dynamic, data-fed content systems
We see the most progressive agencies organizing around Centers of Enablement (CoEs) for AI, investing in AI literacy for all staff, and shifting their recruiting toward prompt engineers, AI product managers, and automation specialists.
5. Why the multiple gap is widening
- Scalability premium: AI platforms decouple revenue from headcount, driving 3 – 5 points of EBITDA expansion versus labor-intensive peers.
- Revenue durability: Proprietary models trained on client data create switching costs and net-revenue-retention, prized by PE roll-ups and strategic buyers.
- Capital efficiency: Investors reward tech-driven margins with higher forward EV/EBITDA.
6. Operating model playbook for value creation
- “Platformise” delivery: Stand up an internal “Agency OS” integrating prompt libraries, workflow orchestration and knowledge graphs.
- Build an AI Centre of Enablement: Cross-functional hub owning model-governance, measurement, and upskilling to close the talent gap.
- Pivot to outcomes-based pricing: Translate AI productivity into client-facing commercial models (e.g., cost-per-incremental conversion) to capture unlocked margin.
- Codify proprietary IP: Fine-tune domain-specific LLMs on anonymized client datasets to generate defensible differentiation and due-diligence-ready moat narratives.
Agencies adopting AI as a central tool will attract more clients, gain buyer attention, and secure better exits. In contrast, those slow to adopt will face shrinking margins and struggle to maintain profitability.
