🌐 77% are stuck experimenting. 23% are scaling intelligently. Which are you?

I was on a call last week with a consulting firm owner who told me, "We're using AI everywhere now. ChatGPT for proposals, Claude for research, Midjourney for visuals. We're fully in."

Then I asked him: "So what's changed in your business?"

Pause.

"Well... we're faster at some things."

That conversation stuck with me. Not because he's wrong—he's doing what everyone else is doing. But because "faster at some things" isn't transformation. It's optimization at best.

Here's what I keep seeing: Everyone's experimenting. Everyone's testing tools. But very few are actually redesigning how work happens.

And that difference? That's everything.

This week, I'm breaking down something most people aren't talking about yet—but the 23% who are scaling it are seeing results that make the rest look like they're standing still.

As always, our Growth Stack team has also curated three reads that connect to this theme: one on why disciplined stability can create more value than growth obsession, another on building personal wealth while you build your business, and a third on the productivity habits that separate high performers from everyone else.

The thread running through all of it? Real leverage doesn't come from working harder or adding more tools. It comes from building systems that multiply your capacity.

So as you dig into this week's issue, ask yourself: Are you optimizing tasks, or are you redesigning workflows?

Let's go!

Every week, we break down the big-picture strategy behind the shifts happening in business—so you can see around corners while others are still catching up.

Everyone's talking about ChatGPT.

Everyone's experimenting with AI assistants. Prompt libraries. Workflow hacks. Tool after tool after tool.

But here's what most people miss: while 88% of companies are now "using AI," only 23% are scaling the technology that actually transforms how service businesses operate.

That technology? Agentic AI.

And if you haven't heard the term yet, you're about to understand why it matters more than every other AI conversation happening right now.

The Difference Between Assistants and Agents

Let's get clear on what we're talking about.

Most AI tools you're using today are assistants. ChatGPT helps you write an email. Midjourney creates an image. Claude drafts a proposal. You ask, they respond. You review, you approve, you move forward.

They're helpful. But they're passive.

Agentic AI is different.

An agent doesn't just respond to a single prompt and wait for your next instruction. It plans, decides, and executes across multiple steps in a workflow—autonomously. It connects to your systems, evaluates options, takes action, and adapts based on results.

Think of it this way: If your current AI is power steering, agentic AI is autopilot.

One helps you turn the wheel. The other takes you from point A to point B while you focus on strategy.

Here's a real example: A traditional chatbot answers a customer question about a delayed shipment. An agentic AI system accesses live shipping data, determines the cause of the delay, offers solutions like expedited replacement or partial refund, updates your records, and executes the chosen resolution—all without you touching it.

One interaction. One customer. Fully handled.

That's not automation. That's transformation.

Why Only 23% Are Scaling—And What They Know

According to McKinsey's latest research, 88% of organizations are using AI in at least one business function. But when you dig into the data, most are stuck in pilot mode—experimenting with chatbots, testing prompts, playing with tools.

Only 23% have scaled agentic AI systems. And those companies? They're not just incrementally more efficient. They're fundamentally operating differently.

They're seeing:

The gap isn't about better tools. It's about reimagining what work looks like when intelligent systems handle the execution while humans focus on judgment, strategy, and relationships.

The companies scaling agents aren't asking, "How can AI help me write faster?" They're asking, "Which entire workflows can run without me?"

The Service Business Advantage

Here's where this gets interesting for service-based business owners.

Most enterprise AI stories focus on manufacturing, logistics, or massive corporations. But agentic AI is uniquely powerful for service businesses—because service delivery is exactly what agents do best.

Think about your business right now. How much of your time is spent on:

These aren't creative tasks requiring your unique insight. They're orchestration tasks—multiple steps, decision points, and systems that need to work together.

That's the agentic AI sweet spot.

A law firm used agentic AI to handle client intake, document preparation, and case research. Their agents autonomously gather information, draft initial briefs, and surface relevant precedents—cutting preparation time by half while their attorneys focus on strategy and client relationships.

A consulting firm deployed agents to manage proposal workflows—from initial inquiry to customized pitch deck to follow-up scheduling. Their sales team productivity jumped 67% because they stopped doing administrative orchestration and started doing high-value relationship building.

A marketing agency built agents to handle client reporting, pulling data from multiple platforms, generating insights, and delivering formatted reports on schedule. Their account managers went from spending 12 hours per week on reporting to spending 30 minutes reviewing and personalizing the output.

Same revenue. Fraction of the operational drag.

The Pilot Trap—And How to Avoid It

Here's the trap most businesses are falling into: They're treating agentic AI like another tool in the stack instead of a fundamental redesign of how work happens.

They build a single agent for one task. It works. Everyone celebrates. Then... nothing scales.

Why? Because they're thinking in use cases, not business processes.

The companies winning with agentic AI aren't deploying isolated bots. They're rewiring entire workflows—connecting agents across systems, data sources, and decision layers.

Instead of "an agent that drafts emails," they're building "an agent that manages the entire client communication workflow from inquiry to close."

Instead of "an agent that schedules meetings," they're building "an agent that orchestrates project kickoffs including calendar coordination, document preparation, and stakeholder alignment."

This is the shift from assistance to agency. From tool to system. From incremental to transformational.

What Separates the 23% From Everyone Else

The research is clear on what high performers do differently:

1. They Start With Process, Not Tools They don't ask "What can this AI do?" They ask "What workflows are consuming human capacity that shouldn't be?"

2. They Redesign, Don't Automate They don't take existing processes and slap AI on top. They reimagine how work should flow when intelligent systems handle execution.

3. They Focus on Integration, Not Isolation They connect agents to their CRM, project management, communication platforms, and knowledge bases—creating orchestrated systems instead of point solutions.

4. They Define Clear Boundaries They establish exactly when agents act autonomously and when they escalate to humans—creating trust through clarity, not hoping for perfection.

5. They Measure Capacity, Not Just Efficiency They track how much human capacity is freed up, not just how much faster tasks complete—because freed capacity creates strategic advantage.

The Bottom Line

The AI conversation is moving fast. But most people are focused on the wrong things.

They're chasing better prompts when they should be building better systems.

They're optimizing individual tasks when they should be redesigning entire workflows.

They're treating AI as an assistant when they should be deploying it as an agent.

The 23% who are scaling agentic AI aren't smarter or better funded. They're just playing a different game—one where intelligent systems handle orchestration and humans focus on the high-judgment, high-relationship work that actually creates competitive advantage.

The question isn't whether agentic AI will transform service businesses.

It's whether you'll be in the 23% who lead the transformation or the 77% who eventually have to catch up.

Here's where strategy meets action. Each week, we give you the tactical steps to implement what you just learned—so you can capitalize on the insight immediately.

How to Identify Your First Agent-Ready Workflow This Week

You don't need to rewire your entire business to capture value from agentic AI. You need to identify one high-leverage workflow and build your first intelligent agent around it.

Here's exactly how to do that in the next 60-90 minutes:

Step 1: Map Your High-Frequency, Multi-Step Workflows

Grab a document and list every recurring workflow in your business that meets these three criteria:

✓ Happens at least weekly (ideally daily)

✓ Involves 3+ distinct steps across different tools or systems

✓ Requires decision-making but follows logical rules

Common examples for service businesses:

Write down 5-7 workflows that fit this pattern. Be specific about each step.

Step 2: Score Each Workflow on Agent-Readiness

For each workflow, rate it on these dimensions (1-5 scale):

Frequency: How often does this run? (1 = monthly, 5 = multiple times daily)

Time Drain: How much human time does it consume? (1 = minutes per occurrence, 5 = hours per occurrence)

Decision Clarity: How rule-based are the decisions? (1 = requires deep judgment, 5 = follows clear logic)

System Integration: How many tools does it touch? (1 = single tool, 5 = multiple connected systems)

Human Value: How much strategic value do humans add? (1 = high-judgment creative work, 5 = execution and orchestration)

Add up the scores. Your highest-scoring workflow is your agent-ready candidate.

Step 3: Break Down the Current vs. Desired State

Take your top-scoring workflow and document:

Current State:

Desired Agent State:

Be brutally honest about what requires genuine human judgment (strategy, relationship management, creative problem-solving) vs. what's just execution (data entry, status updates, information retrieval, rule-based decisions).

Step 4: Build It in GoHighLevel

Here's the truth most people won't tell you: You don't need a dozen different platforms to build intelligent workflows. You need one system that does it all.

That system is GoHighLevel.

Why GHL is perfect for Agentic Workflows:

Unified System Architecture

Built-In Automation Engine

Native AI Integration

Service Business DNA

Whether you're automating client intake, proposal follow-up, onboarding sequences, or customer communication—GHL gives you everything you need to build your first agentic workflow without duct-taping multiple platforms together.

Start with GHL's workflow builder. Map your agent-ready workflow from Step 3. Build it step by step. Test it. Refine it. Scale it.

(Our team is GoHighLevel certified and can handle full CRM installation and setup. We can also build a full AI agent suite custom to your business. Get a FREE Trial here. Already a GHL user? We can customize your existing GoHighLevel CRM setup and build custom AI agents right inside your current ecosystem. Questions or to schedule a demo, email The Growth Stack team: [email protected] 👈)

Step 5: Build Your Minimum Viable Agent (MVA)

Don't try to automate the entire workflow on day one. Start with the highest-value segment:

Week 1: Set up basic workflow monitoring and data connections
Week 2: Automate the most time-consuming step with agent oversight
Week 3: Add the second step and test the handoffs
Week 4: Expand to full workflow with human oversight at decision points
Week 5: Refine based on what worked and didn't
Week 6: Scale or move to your second workflow

The key is getting one agent actually running—not getting trapped in planning mode.

Step 6: Define Success Metrics That Matter

Track three things:

Capacity Freed: How many hours per week did this give back to your team?

Cycle Time: How much faster does this workflow complete?

Quality Consistency: Are outcomes meeting or exceeding human performance?

If you're not tracking capacity freed, you're missing the point. The goal isn't just faster execution—it's strategic capacity to do higher-value work.

What Success Looks Like

You'll know your first agent is working when:

That's when you've moved from tool user to system builder. From the 77% to the 23%.

Start today. Pick the workflow. Map the steps. Build your first agent.

The service businesses winning in 2026 won't be the ones with the best AI prompts. They'll be the ones whose intelligent agents handle orchestration while humans focus on strategy, relationships, and judgment.

That transformation starts with one workflow. This week.

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