Six Steps to Building an AI Roadmap That Doesn't Fail

We're in the unsexy phase of AI right now. It's no longer about the flashy bet that sounds good on an earnings call. It's all about having a thoughtful rollout strategy that doesn't lead to more false starts.

Here's the way we've built AI roadmaps for 100+ companies, and it's an approach you should copy.

Step 1: Interviews at the Top

Ideally start with the CEO. If not possible, prioritize the most senior person with the widest aperture and clearest sense of goals and challenges.

Focus the interview on the company's biggest goals (OKRs, Rocks, etc.) and the biggest blockers standing in the way of those goals. Those blockers will always boil down to some combination of people, process, and technology.

Finish the interview by asking who else you should interview to get valuable perspective on goals, blockers, and business context.

Step 2: First Round Interviews

If you're doing an organization-wide AI audit, interviews are typically focused on ELT (Executive Leadership Team).

If you're doing a functional audit (Engineering, Data, Marketing), interviews typically include the highest ranking functional leader and all N-1s.

Step 3: Gather Data

Based on goals and gaps, that will inform survey questions and data requests.

Examples include:

• Financials for ROI studies
• ERP data for supply chain processes
• GA/customer data for marketing workflows

Step 4: Go Deeper

The second round of interviews is focused on specific opportunities called out above. If steps 1-3 were about figuring out where the treasure is buried, step 4 is about filling out the entire map.

This is where you go deeper on process mapping, org chart and people dynamics, and tech stack.

Pro tip: people, process, data, and technology are equal blockers. Most people get data obsessed and neglect the others.

Step 5: Draft Recommendations

Your first round recommendations and roadmap should include:

• A list of opportunities with ROI estimate inclusive of all costs (people, process, technology, financial)
• Governance frameworks like start/stop/continue/edit on existing initiatives

Sequence by the business's appetite with a bias for highest expected ROI. Translation: prioritize initiatives that have a high success rate and high ROI. Cultural momentum building is the most important initial priority.

Step 6: Final Presentation

This is where you bring it all together. Present the roadmap, the recommendations, and the sequencing to leadership for alignment and buy-in.

The Takeaway

This is the high-level approach. Notice that only a fraction of the work is actually about AI. Most of it is discovery, alignment, and understanding the real blockers. That's why AI transformations fail: companies skip the hard work and jump straight to the technology. If you want to understand all 10 steps to AI transformation and why only one is actually AI, that context matters here.

The companies that win aren't the ones with the flashiest AI tools. They're the ones that do the unglamorous work of interviewing, mapping, and sequencing before they ever write a line of code.

If you want the full AI diagnostic process with interview and survey questions, reach out. This approach has worked for 100+ enterprises, and it can work for you too.