Accelerating AI Adoption in GTM: A 90-Day Roadmap

From Tactical Experiments to Teamwide Proficiency: What 90 Days of Focus Can Actually Deliver

AI sales adoption fails when companies confuse access with proficiency. Simply giving your reps a ChatGPT login isn’t a strategy, and it’s not enough. What actually drives adoption is structure: clearly defined phases, role-specific use cases, cultural reinforcement, and executive accountability.

To pressure test this belief, we spoke with Conor Dragomanovich, GTM leader and head of sales MM ENT at OpenAI, who shared how his team doesn’t treat AI like a trick, but a muscle that needs to be developed. Building that muscle means daily repetitions, cultural reinforcement, and a structured plan to ramp proficiency across every level of the organization.

This is the shift revenue leaders need to make:

From hype → to habit.
From curiosity → to proficiency.
From “Who’s using it?” → to “How are we scaling it?”

That’s what this page delivers: a 90-day tactical roadmap to build AI adoption across your GTM team, from individual contributors to frontline managers to cross-functional leadership.

We’ll break it down into focused phases:

1. 1. Days 1-30: Democratize Access & Establish Fluency
   2. Days 31-60: Operationalize Use Cases & Measure ROI
   3. Days 61-90: Scale and Shift Mindsets
   4. What Comes After 90 Days? GTM AI Maturity

Related Content: The 5 Stages of AI Maturity in GTM Organizations

Days 1–30: Democratize Access & Establish AI Fluency

AI adoption starts with mindset and alignment.

According to SuperAGI, the top barriers to AI adoption include lack of skilled personnel (29%), integration challenges (28%), resistance to change (28%), and budget constraints (25%). None of those are solved simply by provisioning a tool.

The biggest threat to early adoption is hesitation. Teams stall when there’s a fear of “doing it wrong,” or when AI is only championed by a few isolated users. The first 30 days are about breaking that pattern and removing the invisible friction that slows down momentum.

The first month should be about readiness. This phase is where you start breaking organizational inertia by removing friction, building fluency, and creating a psychologically safe space for reps and managers to experiment.

If you skip this phase, you don’t build muscle, you build shadow adoption.

Key Objectives

• Remove barriers to access and cultural fear around using AI
• Create a safe space to experiment
• Begin tracking usage and common friction points
  

30-Day Checklist

Enable universal access to ChatGPT Teams or Enterprise.

Avoid isolated rollouts. Every team (SDR, AE, CS, RevOps, and Enablement) should have access from day one.

Run a team-wide onboarding session

You have to get hands on keyboards to understand the possibilities of Generative AI. This session is as simple as a “Build Your Own GPT” –  hours of hands-on, focused exploration. It’s not about mastery or ROI.

Create AI User Guides for ICs and leaders

Capture working styles, preferences, and workflows. Feed these into role-specific GPTs to drive relevance.

Start with 1–2 clear use cases per role

Think deep research for sellers, call prep for managers, or persona summaries for marketers. Keep it simple, tactical, and repeatable.

Adopt a “no big bet” mindset

Don’t boil the ocean. Focus on embedding AI into core workflows one role at a time, rather than an org-wide transformation.

Success Metrics

• % of GTM organization using ChatGPT or with AI tool access
• % completion of AI fluency or onboarding training
• Number of AI user guides and GPTs created
• Baseline usage rate by department (daily/weekly active users)

Why This Phase Matters

The goal of the first 30 days is to turn experimentation into habits. If you get this phase right, you create a foundation of comfort and curiosity that will accelerate everything that follows.

Get Your Team AI Certified

This 90-day roadmap is going to take you from individual to team proficiency. We suggest creating and using custom GPTs, projects, and workflows. Knowing how to create these AI assistants and automations is going to become table stakes for your people, like using sales engagement platforms and CRMs. Get your reps and frontline managers training ASAP in our next Certification cohorts.

Days 31–60: Operationalize Use Cases & Measure ROI

The second month is where the adoption curve takes shape.

Yet, only half of GTM professionals use AI at least weekly, and nearly one-third either never use it or don’t even know how often they do. That’s not an adoption curve; that’s an adoption cliff.

This is where you build the bridge. In this second month, the goal is consistency. If Phase 1 introduced AI, Phase 2 makes it operational.

Curiosity got your team started. Now it’s time to drive consistency. In this phase, AI moves from “something we’re trying” to “something we rely on.” Exploration becomes execution. Use cases become workflows. Reps stop asking if they should use AI and start asking how to make it better.

This is the point where usage becomes measurable. Leadership should begin treating AI performance the same way they treat sales performance: tracked, reviewed, and improved.

Key Objectives

• Normalize daily use of AI tools
• Integrate AI into critical workflows
• Begin quantifying business impact
  

Next 30-Day Checklist

Create structured projects for every account
Centralize CRM data, prospect research, call transcripts, and prep into unified projects. Make GPTs the single source of context before every meeting.

Assign Custom GPTs per rep and manager
Reps use GPTs to surface deal risks, get coaching feedback, and prep for calls. Managers track performance trends and create coaching loops that scale.

Run department-level AI kanban boards
Prioritize and score GPT/AI initiatives by business impact. For example, if a use case doesn’t deliver a 20%+ productivity lift, it gets reworked or paused.

Launch real-time usage dashboards
Go beyond logins. Track prompt volume, workflow adoption, and qualitative feedback (e.g., “How much time did this save you?”)

Success Metrics

• Number of GPTs and projects created per rep/team
• Average time saved per role or workflow
• Changes in deal velocity or pipeline progression
• Internal NPS or satisfaction with AI tools

Why This Phase Matters

Beyond tools, your team needs AI workflows that are visible, repeatable, and tied to real outcomes.

This is where AI proficiency starts to show up in revenue motion. Once you can track time saved, deals moved, or friction removed, you’ve now operationalized AI

“We started seeing real traction when teams stopped asking for AI tools and started asking for AI help with specific tasks. That shift, from tools to workflows, was the unlock.”  – Conor Dragomanovich, GTM Leader, OpenAI

Related Content: Why 70% of GTM Teams Fail to See AI ROI

Days 61–90: Scale & Shift Mindsets

The final phase is where adoption becomes identity.

McKinsey reports that 78% of organizations now use AI in at least one business function. Yet only 1% of company executives say their AI deployments are truly “mature.” Translation? Most companies are still stuck in pilot mode.

This phase is where you break out of that trap. You’ve proven use cases. You’ve created momentum. Now it’s time to scale that behavior across the organization and embed AI into coaching, onboarding, performance reviews, and strategy.

This is where you move from reps using AI to a culture that runs on AI.

Key Objectives

• Expand from individual and team usage to org-wide adoption
• Embed AI into sales coaching, onboarding, and enablement
• Showcase success stories to fuel a flywheel of momentum
  

Next 30-Day Checklist

Promote AI champions across the org
Recognize early adopters and highlight their GPT builds. Treat these internal success stories like product launches: celebrate and scale them.

Embed AI into performance reviews and check-ins
Use custom GPTs to track rep development, surface insights, and prep for 1:1s or QBRs. This normalizes AI in the systems that matter.

Host internal AI demos or hackathons
Let teams show off GPTs they’ve built or use cases they’ve mastered. Cross-functional learning accelerates cross-functional adoption.

Elevate executive visibility and behavior modeling
Require leaders to use AI in public ways: team meetings, forecasting, and QBRs. And tie AI initiatives to business outcomes. What leadership models, the team will mirror.

Success Metrics

• Number of GPT-generated insights or outputs used in QBRs
• Revenue impact tied to AI-influenced deals
• Number of shared GPTs or projects adopted cross-functionally
• Documented AI playbooks per department or workflow

Why This Phase Matters

At this point, AI should no longer feel experimental. It should be expected.

When reps see their peers succeeding with AI, managers coaching on it, and execs using it in reviews, it stops being a “tech initiative” and becomes the norm. That’s what drives real AI maturity. It goes beyond sage to behavior changes at scale.

Guiding Principles for Long-Term AI Sales Adoption

Tactics get you started. Principles keep you scaling.

Whether you’re in week one or month six, the team that turns AI into a competitive advantage focuses on the fundamentals. Here’s what we’ve learned working with dozens of GTM teams rolling out AI in the real world:

Guiding Principles for Long-Term AI Sales Adoption

Start small, go deep

Don’t over-engineer a strategy before proving the basics. Tactical use cases like call prep, persona research, and GPT-based coaching deliver faster ROI than big-bang rollouts. Prove value at the rep level before scaling org-wide.

Adoption ≠ Access

Just giving teams a login won’t change behavior. Real adoption requires enablement, repetition, and leadership accountability. Training must be ongoing, not a one-time event.

Projects > Playbooks

Custom GPTs are powerful, but GPT projects are transformational. By centralizing sales inputs (CRM, notes, transcripts, deal strategy) into one workspace, AI becomes part of how your team executes.

Leaders set the tone

If AI only lives in the hands of ICs, adoption will stall. The fastest-scaling teams have execs who publicly use GPTs, ask for AI-generated insights in meetings, and tie performance back to innovation. Visibility drives momentum.

Think department by department

The best results come from designing GPTs around specific workflows vs. generic prompts. Each team (rev ops, enablement, sales, and marketing) needs their own tools, language, and success criteria.

What Comes After 90 Days? GTM AI Maturity

You’ve built early fluency. You’ve operationalized use cases. You’ve shifted mindsets. Now it’s time to make AI sustainable.

Here’s how to keep scaling: We call it the 5 Stages of GTM AI Maturity. 

Following this 90-day roadmap to build the adoption and usage muscle will get you somewhere between Stages 2 and 3 with team-level adoption. At this stage, AI is no longer just an experiment. Teams are using it in daily workflows, managers are starting to build it into coaching and reviews, and early pockets of productivity are clear. But success is still uneven. Different teams may be moving at different speeds, and insights aren’t yet connected across functions.

The next stage is department-level maturity, characterized by operational consistency, measurable improvements, and repeatable workflows. Aka, Stage 3: Connected Workflows. This is where AI stops being a team-level tool and starts becoming departmental infrastructure. CRM and BI integrations bring consistency, workflows become standardized, and the business begins to see measurable lift – faster ramp times, stronger pipeline progression, and repeatable results.

This 90-day roadmap is foundational to giving your team momentum and making a case for the applications of AI to leadership, as well as addressing user resistance. But if you want to move from adoption and some power users, continue your journey with The 5 Stages of AI Maturity in GTM Organizations. It will help you move your organization from basic AI Assistant usage to a fully AI-First GTM Platform.