How I Evaluate a 12‑Month AI Roadmap Answer

TL;DR: Learn a 3-part framework to evaluate a candidate's 12-month AI roadmap, scoring them on phasing, architecture, and data governance.

A framework for assessing senior technical candidates on strategy, architecture, and governance.

When hiring a senior engineer, architect, or CTO, their ability to articulate a realistic 12-month AI roadmap is a critical signal. I use a simple framework to score them, which you can lift directly into your own hiring process. First, I set the context: a mid‑size B2B SaaS company with an existing monolith, messy data, a small team, and a CEO who wants “AI copilots” in under a year. I’m not grading on fantasy architectures; I’m grading on how they think under real-world constraints.

Then I score them across three dimensions:

Phased, Outcome-Driven AI Roadmap (25 points)

I’m looking for a clear sequence of phases over twelve months, with each phase tied to real outcomes, not just activity. Strong answers sound like: “Phase one earns the right to build by de‑risking data and shipping a prototype. Phase two ships the first copilot with measurable business impact. Phase three doubles down on what works and formalises governance.”

Fit-for-Context Architecture and Build-vs-Buy (35 points)

Here I want them to respect the current stack and team. Do they keep the core on the existing cloud and introduce AI through sidecar services? Do they lean on managed LLMs and platforms early, and only talk about custom hosting or sovereign options when scale or regulation justify it? Top answers make explicit trade‑offs: “We choose this managed service over building our own because of X, Y, and Z.”

Data Foundations, PII Handling, and Governance (40 points)

This is non‑negotiable and a core component of any professional AI Governance & Risk Advisory. I expect them to identify where PII lives, centralise and classify it, enforce data residency, and bring legal into the process early. Bonus points if they’re opinionated about which AI use cases are off‑limits in year one because of governance risk, and how they’ll monitor and audit AI behaviour in production.

If a candidate can move comfortably across these three axes—phasing, architecture, and governance—while acknowledging resourcing limits and trade‑offs, I know they’re ready to lead a real AI roadmap, not just talk about one.

Further Reading

• Hire AI Architect Vetting Framework 2026
• Five Strategic Imperatives Your 2025 AI Roadmap
• Build Vs Buy AI Systems 120k Decision Framework 2026
• AI Copilots Playbook Fractional CTO 2026

Written by Dr Hernani Costa, Founder and CEO of First AI Movers. Providing AI Strategy & Execution for Tech Leaders since 2016.

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