A good AI roadmap for a mid-sized company is a short document, not a 40-slide deck. It ranks a handful of workflows, names an owner for each, records where the data and hosting sit, sets who approves AI output, says how each one will be measured and puts them in order. A board can read it and ask useful questions.
#Key takeaways
- A roadmap is a ranked list of workflows with owners, not a vision statement or a maturity score.
- Every workflow on it needs a data and hosting decision and a named person who approves the AI output.
- Each workflow needs a measure taken before AI, so the board can see whether it worked.
- The sequence matters more than the length of the list: the first workflow should be the one most likely to reach production.
- Leave out tool catalogues and architecture diagrams that come before any understanding of how the work is done today.
#What should a good AI roadmap contain?
- ranked workflows: a handful of specific pieces of work, such as supplier query replies or invoice entry, each with the reason it made the list.
- owners: one named person per workflow on the business side, accountable for the result, not only for the project.
- data and hosting decisions: which data each workflow touches, where it is stored, where the model runs and who the processor is.
- approval rules: who checks the AI output before it reaches a customer or a system of record, and what they can override.
- measures: the baseline for each workflow, such as volume, handling effort, error rate and backlog, and how it will be measured again.
- sequence: which workflow goes first, which follow, and what has to be true before the next one starts.
Each item answers a question a board member is likely to ask: what are we doing, who is responsible, is the data safe, who checks it, how do we know it worked, and what comes next.
#Why do so many AI strategies stall before they pay back?
Gartner expected 30% of generative AI projects to be abandoned after proof of concept by the end of 2025, citing poor data quality, inadequate risk controls, escalating costs and unclear business value (Gartner, july 2024). Coverage of the MIT NANDA report found 95% of organizations saw no business return from generative AI (virtualization review, august 2025).
Most of those causes are decisions a roadmap can make before anything is built: which data is usable, who controls the risk, and how value will be measured. A strategy that leaves them for later is the version most likely to stall.
#What should you leave out of the roadmap?
A vanity maturity score instead of an owner-assigned roadmap is one of the most common complaints buyers make about readiness reports. A score tells the board where the company sits on someone else's scale. It does not say what to change, who changes it or how anyone will know.
Leave out long tool lists and multi-agent architecture diagrams too. Anthropic's own guidance on building with models is to start with the simplest approach and add complexity only when it is needed (Anthropic, december 2024). A roadmap should follow the same rule.
#How do you rank the workflows?
Rank them on criteria you can check: volume, how rule-based the work is, how costly a mistake is, who would approve the output and whether the data is reachable. We set out the criteria Stennir uses in how to pick the first process to automate with AI.
We are
Stennir runs an AI Opportunity Audit that returns five ranked workflows, each with a cost and a payback case, and one recommended build with its scope and hosting region. The report is yours whether or not you build with us.
We aren't
Stennir does not sell a maturity score, a 40-slide strategy deck or an architecture that comes before understanding how your operations work.
#What should a CEO or COO do next?
Before the board meeting, list the workflows people already complain about and name a possible owner for each. That list is the start of the roadmap. AI consulting turns it into a ranked one with hosting and measures, and AI for operations shows typical workflows. take the free readiness assessment or book a 30-minute call.
#Common questions
How long should an AI roadmap be?
Long enough to name each workflow, its owner, its data and hosting decision, its approval rule and its measure. For most mid-sized companies that fits on a few pages. A much longer document usually means the ranking has not been done, and the reader is being asked to do it instead.
Who should own the AI roadmap?
One executive sponsor owns the roadmap as a whole, usually the COO or the head of operations. Each workflow on it has its own owner in the business. The it or data team owns the hosting decisions. If nobody's name is on a workflow, it is not ready to be on the roadmap.
What do you need from us to build it?
Access to the people who do the work, the process documents you already have, a view of the systems involved and someone who can speak for data and compliance. Stennir interviews the teams, maps the workflows and writes the ranking. The report stays with you.
Does the roadmap need to cover Arabic?
Yes, if any workflow handles Arabic documents or customer messages. The roadmap should say which workflows involve Arabic, whether that includes Gulf dialect, and how output quality will be tested on your own data. Stennir works in Arabic and English, and other languages on request.
