Agency Interrupted: Navigating the Human Side of AI Transformation

Picture this: a storied creative agency in New York City, crafting award-winning work for Fortune 500 brands since before "digital transformation" was even a buzzword. They've got the client roster, the Soho office with its iconic neon sign, and enough industry accolades to line their walls twice over.

For two decades, they've ridden every innovation wave—from Flash microsites (remember those?), to social media war rooms, to AR experiences that landed them on the evening news.

Now they're facing their biggest transformation yet: AI. And like many seasoned agencies, they assumed this would just be another technology shift to master.

But this time, things weren't so simple.

Stepping Into the AI Transformation Crisis

When I joined Gulliver's AI transformation effort, I found a team genuinely eager for change—but stuck in an endless loop of preparation.

They had already spent a full year in "discovery mode," sitting through countless interviews, filling out surveys, and repeatedly answering variations of the same question:

"What are your AI pain points?"

Their challenge? They had shared these insights multiple times, voiced their concerns, and contributed meaningful ideas. Yet, after each round, the path forward stayed frustratingly unclear.

Leadership's response? To launch another expanded round of pain-point discovery.

This wasn't transformation—it was transformation fatigue.

Recognizing the AI Exploration Trap

I've seen this pattern before:

Leadership acknowledges the importance of AI.
A committee forms, spawning more meetings and more surveys.
Teams are repeatedly asked to define their AI needs.
An inventory of AI tools is built, but without a coherent strategy.
Momentum stalls because AI is seen as something to explore rather than integrate.

Gulliver's team wasn't resisting AI—they were exhausted by indecision. And who could blame them? With AI changing faster than any prior technology, it's daunting to commit strategically.

AI as an Afterthought Instead of a Foundation

One fundamental issue was retrofitting AI into existing processes rather than reimagining those processes entirely around AI.

Most conversations revolved around specific tools—meeting summarizers, email generators, slide creators. These tools provide incremental convenience, not transformational change.

True AI transformation isn't just about adding tools to your workflows; it's about fundamentally reshaping how work gets done by embedding AI deeply and strategically from the start.

The Testing Trap: Why Workflow Integration Fell Short

Another significant misstep at Gulliver was their approach to testing AI. Teams evaluated sophisticated tools using outdated processes—like testing a smartphone by using it solely as a desk phone.

For example, their creative teams would adopt generative image tools or copywriting assistants, attempting to slot these directly into existing workflows. They inevitably encountered friction, missed opportunities, and frustration:

1. Task vs. Workflow Mismatch

AI tools usually excel at specific tasks. Creative workflows, however, involve interconnected tasks with complex nuances. Dropping task-based tools directly into existing workflows created friction at every step.

2. Lack of Structured Testing

Without structured testing, control groups, or clear evaluation criteria, insights were anecdotal, not actionable:

"It helps sometimes."
"Speeds up basic tasks."
"The learning curve is steep."

These observations, while honest, never clarified how to fundamentally reengineer workflows using AI.

3. Future Tools, Past Habits

They evaluated innovative tools within outdated processes—like driving a sports car while never leaving first gear. This limited their ability to see and realize AI's true potential.

The outcome? Promising tools seemed underwhelming, viewed through the wrong lens.

Creative Tools vs. Creative Craft: Understanding AI Maturity

Creative AI tools occupy a distinct place in today's rapidly evolving landscape. Unlike AI solutions in other domains, creative tools aren't just automating—they're actively amplifying and reshaping the way artists, designers, and strategists work. But excitement can obscure the reality that these tools are still maturing rapidly.

Right now, creative AI sits in a tricky spot: powerful enough to spark enthusiasm, yet evolving so fast that accurately assessing their maturity is challenging. Without structured, deliberate testing, teams can misunderstand a tool's capabilities. For example, a Creative Director might declare, "We prefer KREA over EverArt because EverArt can't easily generate photorealistic images." At first glance, it sounds reasonable—but the real issue might be a skill gap in prompt engineering or missing fine-tuning.

The takeaway: test intentionally, evaluate critically, and don't mistake learning curves for product failures. Clear-eyed assessment of tool maturity helps teams set realistic expectations and avoid disappointment.

Another Watch-Out: Middle Management and Partial Perspectives

Middle managers often latch onto small insights or buzzwords without fully grasping the broader context or deeper strategy. It’s understandable—they're eager to demonstrate progress and meet expectations. Yet minor misunderstandings quickly become misguided initiatives, fragmenting rather than unifying your organization's AI efforts.

Another common trap happens when ambitious ideas casually land in developers’ laps without proper scoping. What appears straightforward—like seamlessly integrating multiple complex data sources for easy team access—can spiral into intricate challenges involving data governance, security, scalability, and accessibility.

Consider this familiar scenario: a perky executive enthusiastically blurts out, “Oh, what about DeepSeek? I've heard about that—is it safe?” Immediately, eyes glaze over. The excitement overshadows essential complexities: observability, bias detection, effective guardrails, and properly grounding outputs in your organization's unique data. Enthusiasm without understanding sets unrealistic expectations, leaving developers to bridge the gap between lofty ambitions and practical realities.

The lesson isn’t about curbing ambition—it’s about clarity. Ensure that everyone fully understands the complexity and true scope of their ideas before casually tossing them to development teams. Ambition succeeds when grounded in a realistic understanding of what's genuinely achievable and what's required to get there.

Guiding Gulliver from Exploration to Execution

My role was to help Gulliver escape paralysis by shifting their approach:

Clearly define a singular strategic AI impact.
Focus integration across workflows, not scattered tool adoption.
Treat AI as a core capability, not incremental enhancements.

How I Guided Gulliver's AI Transformation

Here's what it took to restore momentum:

Define a clear business impact.
Redesign workflows around AI, not merely around tools.
Invest in training and sustained AI literacy.
Create centralized AI leadership, governance, and clear guidelines.

Practical Takeaways for Your Organization

Gulliver's experience isn't unique. If you recognize your situation here, ask honestly:

Are we transforming or just adding tools?
Unified vision or fragmented experimentation?
Embedding AI deeply or exploring in isolation?
Investing in people's capabilities or just automating tasks?

Real transformation demands clear direction, ownership, and purposeful action—not endless planning.

Five Watch-Outs for Your AI Transformation Journey

AI Tools vs. AI System: Tools must fit a broader strategy.
Missing Business Alignment: Align clearly with objectives.
No Clear Governance or Measurement: Establish early success frameworks.
Ignoring Cultural and Organizational Change: Transformation involves people deeply.
Lacking an Operational Roadmap: Vision demands practical execution plans.

The Journey Beyond Implementation

Real transformation happens when AI moves from your goal to your greatest enabler—shifting your mindset from "How do we use AI?" to "What's possible now?"

Thriving agencies harness deeply specialized AI tailored to their unique capabilities, unlocking dynamic strategies, creative breakthroughs, and proactive client relationships.

As Douwe Kiela, CEO at Contextual AI, emphasizes:

"General-purpose assistants rarely match your organization's specialized expertise. True transformation requires deeply specialized AI tailored to your unique capabilities."

Your AI Transformation Journey: Let's Talk

Guiding organizations through AI transformation is what I do—and you don't have to navigate this alone.

If you're ready to move beyond exploration, let's connect. Schedule a call today.