Wake Up or Get Left Behind: AI Is Forcing Your Hand

The agency landscape is undergoing a seismic shift, driven by the rapid advancement of AI. This conversation with Chip Griffin and Gini Dietrich isn't just about adopting new tools; it's a stark warning that clinging to outdated practices will lead to obsolescence. The core thesis is that AI is no longer a supplementary technology but a fundamental disruptor, forcing agencies to fundamentally rethink their value proposition. The hidden consequence revealed is that the very tasks clients once paid agencies for--like drafting social posts or press releases--are becoming commoditized by AI. Those who embrace this reality and pivot towards strategic guidance, AI training, and specialized problem-solving will gain a significant competitive advantage, while those who delay will find their revenue streams drying up. Agency leaders, strategists, and anyone invested in the future of communications and marketing should read this to understand the urgency of adaptation and to gain a strategic roadmap for survival and growth.

The Inevitable Tide: Why AI Demands Immediate Adaptation

The ground is shifting beneath the agency world, and the pace of change is accelerating. This isn't a drill; it's a fundamental disruption that demands immediate attention. Chip Griffin and Gini Dietrich don't pull punches, framing AI not as a helpful add-on but as a force that will either propel agencies forward or leave them behind. The core issue isn't just about efficiency gains; it's about a complete redefinition of what clients are willing to pay for. The immediate, visible problem is that AI can now competently handle many of the tactical tasks that have long formed the bedrock of agency revenue. The hidden consequence, however, is the erosion of value for those very services, forcing a strategic pivot or facing obsolescence.

"If you do not change, it will replace you. It will take away your revenue. If you keep doing the same thing that you're doing today, it absolutely will destroy you."

-- Chip Griffin

This isn't hyperbole; it's a clear-eyed assessment of the market's trajectory. The conversation highlights how clients are increasingly looking to their agencies not just for execution, but for expertise in navigating this new landscape.

"We are no longer relying on our agencies to do the work. We are relying on agencies to teach us what's coming 'cause we don't have the time."

-- Gini Dietrich

This quote is critical. It signals a shift from agencies as service providers of labor to agencies as educators and strategic partners. The implication is that agencies must invest in understanding AI deeply enough to guide their clients, thereby creating a new, indispensable value proposition. This requires moving beyond simply using AI as a tool for existing tasks and instead leveraging it to redefine services and client relationships. The danger lies in the "user error" Chip mentions--applying AI superficially without deep training and strategic intent, leading to mediocre output and a reinforcement of the idea that AI-generated work is inherently inferior. The real advantage comes from treating AI not as a vending machine for content, but as a collaborator that, with proper training, can unlock new levels of strategic insight and efficiency.

Beyond the Intern Stage: Training AI for Strategic Partnership

The evolution of AI from a rudimentary tool to a capable junior employee, and potentially a mid-level one, is a central theme. The initial reaction for many is frustration with the quality of AI output. However, as Chip and Gini articulate, this often stems from a fundamental misunderstanding of how to interact with these tools. The analogy of hiring an employee is particularly apt: an untrained new hire will produce subpar work, but with clear direction, feedback, and training, they can become highly effective. This requires a shift from one-off prompts to ongoing, conversational training, explaining preferences for tone, structure, and desired outcomes.

"When somebody says to me, oh, I just can't get it to output what I need, I'm like, user error. You haven't taken the time to train it."

-- Gini Dietrich

This highlights a crucial point: the effort invested in training AI directly correlates with the quality of its output and its utility as a strategic partner. This training process itself forces a beneficial clarity about an agency's own operations, ideal client profiles, and core values. When you articulate your voice, your preferred structure, and your desired outcomes to an AI, you are, by necessity, clarifying these elements for yourself. This is where the delayed payoff lies; the upfront work of training and strategic alignment creates a durable competitive advantage that is difficult for competitors to replicate quickly.

The conversation also delves into the practicalities of selecting and utilizing different AI platforms. Chip’s approach--using Claude for writing, Gemini for competitive intelligence, Perplexity for research, and ChatGPT as a strategic baseline--illustrates a sophisticated understanding of AI as a toolkit, not a monolith. This multi-tool strategy acknowledges that different AI models have distinct strengths, much like different employees have different specializations. The implication is that agencies need to develop a similar nuanced understanding to maximize their AI capabilities. The danger for those who don't is falling into the trap of using the wrong tool for the job, leading to inefficient workflows and suboptimal results, thereby missing out on the significant time savings and quality improvements that strategic AI adoption can yield.

The 18-Month Payoff: Building Agents and Rethinking Value

The conversation moves towards the next frontier: AI agents and the construction of deeply trained AI systems. Gini’s creation of a "co-CEO" AI, trained on her personal and professional materials, exemplifies this advanced application. This agent, "Sage," as Chip mentions it’s called on the SAGA website, is not just a content generator but a strategic advisor, capable of poking holes in business plans and offering nuanced advice that mirrors Chip’s own perspective. This represents a significant downstream benefit: an AI that embodies the agency's unique expertise and strategic thinking.

The development of such agents requires time and a willingness to invest in the process, a stark contrast to the quick-fix mentality that often pervades business strategy. This is where the concept of delayed gratification becomes paramount. Building a robust AI agent, or even effectively training existing models, demands patience and a long-term perspective. The payoff, however, is substantial: an AI that can accelerate strategic thinking, identify blind spots, and deliver insights that would otherwise take months to uncover. This is precisely the kind of value that clients will pay for in 2026 and beyond--not the execution of tasks, but the strategic guidance and innovative problem-solving that AI, when properly harnessed, can facilitate.

The core message is that the true value of AI lies not in automating existing tasks, but in transforming how agencies operate and what they offer. This requires a radical shift in thinking, moving away from traditional service models and embracing a future where strategic partnership, AI expertise, and deep business clarity are the primary drivers of value. The immediate discomfort of learning new tools, retraining teams, and rethinking service offerings is a necessary precursor to the lasting advantage that comes from embracing this evolution.

Key Action Items

• Train One AI Tool Like an Employee (This Week): Dedicate 30 minutes to a deep, conversational training session with your primary AI tool (ChatGPT, Claude, Gemini). Feed it examples of your best work, explain your preferences for tone and structure, and provide explicit feedback on its outputs. This immediate action builds foundational AI literacy.
• Map 2026 Client Value (This Quarter): Allocate one hour to list all current billable services. Honestly assess which are now table stakes due to AI. Identify services that AI cannot replicate: strategy, AI training for clients, complex problem-solving, and unique expertise. This strategic clarity is a medium-term investment (3-6 months) in business direction.
• Test AI on Personal Tasks (Immediately): If intimidated, use AI for low-stakes personal projects like meal planning, fitness routines, or drafting personal messages. This builds comfort and understanding of conversational prompting without professional pressure, paying off immediately.
• Develop a Multi-AI Platform Strategy (Over the next quarter): Identify the unique strengths of different AI tools (e.g., Claude for writing, Gemini for research). Begin experimenting with how to integrate these specialized tools into your workflow for maximum efficiency and quality. This is a 3-6 month investment in workflow optimization.
• Begin Building or Training a Specialized AI Agent (6-12 months): Explore the creation of an AI agent trained on your agency's proprietary knowledge and methodologies, or significantly deepen the training of existing large language models with your specific data. This is a longer-term investment (12-18 months) that builds a unique, defensible asset.
• Reframe Client Conversations to Focus on Strategic Guidance (Ongoing): Shift client discussions from task-based requests to strategic challenges. Position your agency as a partner that can help them navigate the AI landscape and achieve outcomes, not just deliver outputs. This is an immediate and continuous strategic investment.
• Embrace the Discomfort of Change (Now): Acknowledge that adapting to AI will require effort, learning, and potentially difficult conversations. View this short-term discomfort as a necessary precursor to long-term survival and competitive advantage. This is a mindset shift with immediate implications.