3-Step Framework for AI Integration

Overview #

This framework provides a practical, phased approach to AI integration specifically designed for professional services firms—agencies, consultancies, and similar organizations where billable expertise is the product.

The framework is built around three sequential "acts" that build on each other:

1. Act 1: Governance and Tool Standardization
2. Act 2: Adoption, Enablement, and Automation
3. Act 3: Making AI Your Own

Each act has clear milestones and deliverables. Skip ahead and you'll likely face resistance or poor adoption. Follow the sequence and you'll build sustainable AI capabilities.

Act 1: Governance and Tool Standardization #

The Reality Check #

Most organizations we work with already have AI tools being used internally—often without leadership realizing it. Because OpenAI has been so aggressive about brand-building, when most people think "AI" they jump straight to ChatGPT. But there are other tools maturing rapidly for specific tasks:

• Coding: Cursor, Claude Code
• Media: Midjourney, Synthesia
• General purpose: ChatGPT, Claude, Copilot, Gemini

If you haven't explicitly communicated which tools are allowed, there's a high probability that tech-savvy early adopters are already experimenting.

Step 1: Survey the Landscape #

Start by understanding what people are already using:

1. Send an anonymous survey asking about current AI tool usage
2. Make it safe to share - emphasize no penalties for honest answers
3. Capture aspirations - what tools do people want to use?

This gives you intel and helps identify internal champions for later phases.

Step 2: Pick ONE General-Purpose Tool #

Choose one of the "Core Four" general-purpose chat applications:

Our recommendation: Stick with what aligns with your tech stack. If you run on Microsoft, Copilot gives you the easiest on-ramp through Office integration. If you run on Google, Gemini integrates with Drive and Docs.

All four are actively developed and constantly one-upping each other—there's no wrong choice.

Important caveat: None of these tools currently do connectors well (CRMs, project management, etc.). If your teams rely heavily on tools beyond the standard Office/Drive suite, factor this into your decision.

Step 3: Establish Governance #

Once you have even a single tool selected, put a governance policy in place. The policy should cover:

• Approved tools and prohibited alternatives
• Data classification (what can go into AI tools)
• Usage guidelines (do's and don'ts)
• Oversight structure (who reviews and updates policy)

See our AI Governance Framework Template for a ready-to-customize policy document.

Act 1 Deliverables #

• [ ] Survey completed; current tool usage documented
• [ ] Primary general-purpose AI tool selected
• [ ] Governance policy drafted and approved
• [ ] Enterprise licenses procured with proper data protections

Act 2: Adoption, Enablement, and Automation #

2A: Getting Started on Enablement #

Critical insight: Most of your organization will not progress beyond basic AI uses ("rewrite this email") without structured training.

The 10-20% who are tech-savvy will figure it out. But for the majority, usage will remain limited and sporadic. The value of governance isn't primarily about driving adoption—it's about limiting risk and setting expectations.

Building Your Champion Network #

A simple way to start enablement:

1. Identify the tinkerers - people already using AI regularly
2. Create recurring sessions - knowledge sharing or office hours
3. Have craft leads facilitate - Creative Directors, Dev Leads, etc.
4. Embrace struggle - demo what's working AND what's failing

This structure communicates two critical things:

• Allocating time for AI experimentation is OK
• Some failure is normal and expected

2B: Eliminate Work Humans Shouldn't Be Doing #

A common theme across professional services: highly skilled team members getting bogged down with work that's too expensive for their hourly rate:

• Meeting minutes and client follow-ups
• Internal comms to keep teams aligned
• Status updates and reporting across projects

This work is important, but the real value comes from delivering great work that keeps clients coming back.

The Automation Stack #

To eliminate this friction, you need two tools:

1. Workflow Automation Platform

• Make - solid, economical option
• Zapier - more features, higher price

2. Meeting Recording Tool

• Fireflies - best API, polished outputs (our pick)
• Alternatives: Otter, Granola, Read AI

High-Value Automation Workflows #

Once you have meeting transcripts flowing, the possibilities open up:

From a single client call, you can automatically:

Across multiple calls:

• Aggregate transcripts for an account → Generate weekly/monthly account summaries

Back-office automation:

• Time entries → Aggregate by project codes → Calculate invoice amounts → Generate invoice

Act 2 Deliverables #

• [ ] Champion network established with regular sessions
• [ ] Workflow automation platform implemented
• [ ] Meeting recording tool deployed
• [ ] 3-5 high-value workflows automated

Act 3: Making AI Your Own #

What You've Built #

By completing Acts 1-2, you have:

• Rules of the road established for the organization
• Internal champions who can lead change and train others
• Menial work automated so people have capacity to learn

These are the ingredients for scaling AI across the organization.

The Transition #

Now you transition from following a playbook to defining YOUR playbook.

This is where you see creative, ambitious team members doing some of the best work of their careers:

• Crushing their to-do lists with AI assistance
• Consistently raising the bar on output quality
• Leading by example for their peers

Identifying Organization-Specific Opportunities #

Look for workflows where multiple factors align:

The more factors present, the higher the potential ROI.

Examples in Practice #

Developing a Training Program:

1. Analyze internal data for skill gaps
2. Deep research on best practices
3. Draft curriculum structure
4. Create guides and scenarios
5. Auto-generate session summaries

Personalized Outreach:

1. Pull contact context from CRM
2. Reference past interactions
3. Apply brand voice guidelines
4. Draft personalized message
5. Queue for human review

Building Momentum #

• Start small: Pick one high-value workflow per team
• Document everything: Create playbooks others can follow
• Celebrate wins: Share successes in all-hands and team channels
• Iterate quickly: Refine based on what's actually working

Key Takeaways #

1. Sequence matters: Governance before enablement before innovation
2. Champions are essential: Organic adoption only reaches 10-20% of your team
3. Automation unlocks capacity: People can't learn new tools if they're drowning in admin work
4. Context is everything: The same AI tools produce different results based on the data and workflows you build around them

Related Resources #

• AI Governance Framework Template
• AI Use Case Scoring Framework

Get Help #

Need assistance implementing this framework in your organization? Schedule a consultation with our team.