Why an AI Roadmap Is the Missing Link in Enterprise Transformation

📍 Introduction

AI has moved from being an experimental technology to a crucial business priority. But despite all the talk, most companies are stuck. According to the Marketing AI Institute, 75% of organizations lack an AI roadmap, and over half report having no generative AI policy, no AI governance, and no formal oversight council.

The result? AI projects that are disconnected, risks that aren't managed, and unclear value. An AI Roadmap is essential for getting the full business value from AI and driving change across the whole company.

In this article, I introduce the Enterprise AI Maturity Model, a practical framework designed specifically for business leaders. It outlines five stages of AI readiness across key areas—roadmap presence, education, governance, and leadership—and shows how companies can move from random experiments to company-wide transformation in today’s fast-evolving AI landscape.

🔍 1. The Real Problem: Disconnected AI Efforts AI is appearing in different ways across business functions like operations, finance, HR, legal, and customer experience. But most of these efforts are:

• Isolated and uncoordinated
• Lacking clear goals or return on investment
• Unsupported by proper oversight or training
• Vulnerable to compliance and ethical risks This isn't a technology problem. It's a problem of leadership and clear direction. Without a clear overall plan, even the most promising tools won't deliver.

🧭 2. Roadmaps Are the Foundation for Growing AI Use An AI roadmap is more than just a list of projects. It's a strategic plan. It provides:

• A shared understanding of how AI creates value
• A prioritized list of ways to use AI that match business goals
• A basis for training, oversight, and managing change
• A way to track progress and reduce risk
• Support for effective change management and company adoption
• Ensures strong governance and risk control Companies with AI roadmaps are about twice as likely to have the necessary support in place: education for specific roles, policies, and AI councils. Without a strategic roadmap, AI efforts risk going nowhere, no matter how much effort is put in. Good planning is vital for any project's success. It helps with communication, getting people on board, and measuring results.

📊 3. The Enterprise AI Maturity Model To help business leaders, I created the Enterprise AI Maturity Model. It describes five different stages of readiness across four key areas: Roadmap Presence, Education & Literacy, Policies & Governance, and AI Leadership Structures. This model highlights that a clear AI roadmap isn't just a checklist; it's the main driver that moves education, governance, and leadership forward. Effective AI leadership balances centralized oversight with decentralized execution to ensure both strategic alignment and tactical agility.

Here’s a simple example: In a retail company, the central AI council handles big-picture issues like legal compliance, cybersecurity, and ensuring AI projects align with business goals. Meanwhile, marketing’s AI team focuses on practical tasks, like using generative AI to personalize emails. When they hit a privacy question, they quickly get advice from the council—so the project keeps moving safely and smoothly. This teamwork lets the company innovate fast without losing control or direction.

This blend of centralized governance and empowered teams is critical for scaling AI across the enterprise while managing risks and maximizing value.

🔁 4. Roadmaps Drive Learning, Not the Other Way Around

Many companies first focus on tools or training, hoping AI knowledge will simply spread on its own. It won't. Without a clear plan, teams won't know what to learn, why it matters, or how to use AI responsibly.

A roadmap creates a ripple effect:

• Training becomes relevant
• Policies become useful
• Oversight becomes focused
• Leaders become aligned

This strategic structure builds the organizational strength needed to keep innovating.

🏁 5. What Leading Organizations Do Differently

High-performing companies are leading the way by:

• Defining and publishing a company-wide AI roadmap
• Starting broad training programs tied to business uses
• Putting responsible AI policies into practice
• Creating AI governance groups to oversee progress and risk
• Making AI a core part of their strategy, not just a set of tools

They treat AI as a business capability, not just a technology project.

💬 Final Thought: Start Small, Plan Smart

You don’t need to launch a company-wide AI program overnight. But you do need to start with purpose. A 12-24 month roadmap that prioritizes key uses and sets ethical and educational groundwork can align your teams and speed up adoption, safely and effectively. Remember, the roadmap doesn't have to be a big, overwhelming project; you can start small and build it step-by-step, gaining momentum and value gradually.

👉 Call to Action

If you're a business or technology leader looking to build a practical AI roadmap, let’s connect. I help companies design smart, responsible AI programs that grow across the business, focusing on real value, not just hype.

What are the biggest challenges your organization faces in truly using AI for transformation? Share your experiences with AI roadmaps or strategic AI planning in the comments below!

📚 References

• Marketing AI Institute – State of Marketing AI Reports (2023–2024) https://www.marketingaiinstitute.com/blog Provides industry-wide statistics on roadmap adoption, policy gaps, AI councils, and training.
• Gartner – AI Maturity Model Gartner Research, 2021–2023 Offers a framework for evaluating AI readiness across awareness, adoption, and transformation stages.
• McKinsey & Company – Global AI Adoption Reports https://www.mckinsey.com/capabilities/quantumblack Data-driven insights on AI capability building, training, ROI, and scaling challenges.
• World Economic Forum – AI Governance and Ethics Guidelines https://www.weforum.org/reports Outlines principles for responsible AI implementation, risk management, and multi-stakeholder governance.
• Original Analysis and Framework Development by TechElevate Advisors. The Enterprise AI Maturity Model presented in this article is an original synthesis based on the above sources, designed to help organizations assess and improve their enterprise-wide AI readiness.

About Me and TechElevate Advisors

I’m John Manzanares, founder of TechElevate Advisors, a consultancy built to help mid-market and growth-stage companies unlock business value through strategic technology leadership. After serving as CIO across public, private, and PE-backed companies, I saw firsthand how many organizations face big technology challenges without the executive leadership to match. That’s where we come in.

At TechElevate Advisors, we serve as fractional and interim CIOs, aligning IT strategy with business goals to drive measurable outcomes, whether you're preparing for growth, navigating AI transformation, or getting ready for a sale. We don’t just advise; we lead alongside you.

Our clients are typically founders, CEOs, and CFOs of privately held and PE-backed companies who need experienced guidance without full-time overhead. We tailor our approach to your needs, helping you modernize operations, improve decision-making, and execute with confidence.

If your business is at an inflection point and you need strategic technology leadership to move forward, I’d love to connect. Contact me at: john@techelevateadvisors.com