AI strategy consulting: where AI fits, in what order, at what cost

Who is AI strategy consulting for?

It suits a business that can see AI could help but can’t yet say where to start, or one that has tried a tool or two and wants a plan before it spends more. What the work involves depends on how large the business is:

• Established local businesses: an owner, a small team and a few everyday systems, such as an inbox, an accounting package and a spreadsheet or two. A roadmap here can be short: the two or three tasks that take up the most time, in order.
• Multi-location and regional businesses: managers, a back office and the same job done a little differently at each location. Part of the work is settling which version of a workflow AI should be built around.
• National businesses: several brands or divisions, many connected systems, and legal and procurement reviews. A useful roadmap here names an owner for each phase and the reviews each one has to clear.

If one workflow is all you need, we will tell you so on the call, and AI automation may be the place to start.

What does an AI business strategy cover?

An AI business strategy is a decision about where AI will do work in your business and where it won’t. Making it well takes two things a product demo can’t show you: how your workflows actually run, and the numbers behind them.

Part of that decision is sorting each step by the kind of fix it needs:

• A model: steps that mean reading, sorting, drafting or answering, where the input varies each time. That is AI work.
• Fixed rules: steps that follow the same rule every time, such as moving a form entry into a CRM. A Zapier, Make or n8n workflow does those without a model.
• A system of its own: work that needs its own database, screens and users. That is custom software.

We build all three, so nothing in the strategy is steered toward AI for its own sake. When fixed rules would do a step, the roadmap says so.

How do you build an AI strategy?

Whoever does the work, an AI strategy holds up when it is built in this order:

1. List the work. Write down the tasks your team repeats each week, who does them and how long they take.
2. Find the reading and typing. Mark the steps where someone reads a document or an email and types what it says into a system, sorts incoming requests, or drafts the same kind of reply again.
3. Put numbers on them. For each step, estimate the hours it takes, what an error costs, and what automating it would cost to build and to run each month.
4. Rank and group. Steps that would save more than they cost go first, grouped into phases you can deliver one at a time.
5. Set the measure before the build. Agree how each phase will be judged, on numbers you can check, before any of it is built.

A roadmap from us follows the same order. The interviews are the step that can’t be skipped: a strategy written without talking to the people who do the work is a guess about the work.

How do you choose the best AI strategy for a company?

Put the same questions to each candidate first phase:

• Does it save time or errors you can count? Start where your costs and delays actually are.
• What does it cost to build and to run each month? Count model fees, tool subscriptions and upkeep as well as the build.
• What data does it need, and do you have it? A step that depends on data you don’t keep yet belongs in a later phase.
• What happens when it is wrong? A step where a mistake is caught before it reaches a customer makes a safer first phase than one where it isn’t.
• Can it be switched off? A first phase you can stop without stopping the business is easier to try.

Pick the strategy whose first phase you can measure, and be ready to stop if it doesn’t pay off. A small phase that proves itself is a better start than a large one that can’t be judged.

How do you create an enterprise AI strategy?

An enterprise strategy has the same core as any other, plus the questions that come with size: who decides, how risk is handled and how the work is bought.

One reference for the risk side is the National Institute of Standards and Technology’s AI Risk Management Framework, released on January 26, 2023 for voluntary use. It sorts the work into four functions: govern, which builds a culture of managing AI risk; map, which sets the context for an AI system’s risks; measure, which assesses them; and manage, which puts resources against them. Govern runs across the other three. NIST added a profile for generative AI in July 2024.

In practice, an enterprise roadmap names an owner for each AI system, sets a review step wherever regulated data is involved, and plans the route through legal and procurement for each vendor. A roadmap that leaves those reviews out can stall at the first one. We don’t give governance or compliance sign-off: that stays with your counsel and your compliance team.

What should an enterprise AI roadmap include?

Whatever the size of the business, a roadmap you can act on covers:

• The workflows that change, in order: which steps AI takes over in each phase, and why in that order.
• A cost for each phase: what it would cost to build and what it would cost to run each month.
• A measure for each phase: the number that shows it worked, and the point at which a phase that isn’t working is stopped.
• The systems each phase connects to: the inbox, CRM, ERP or order system, and how each one is reached.
• The data and who owns it: what each phase reads and writes, and who in the business answers for it.
• Reviews and owners: the reviews regulated work needs, and a named owner for each phase.

What does AI cost to run once the roadmap is built?

A phase that pays for itself on paper can still lose money once it is live, because AI keeps costing after the build. That is why a roadmap should carry each phase’s running cost as well as its build cost.

The market gives a sense of scale. For an established local business, the October 2026 figures in US agency price pages and guides put running AI automation at $500 to $2,000 a month (ProsperSpark, BetOnAI, Main & Machine and Sam Automates), with a setup of $1,500 to $5,000 for the build (Sam Automates and Builts.ai). A multi-location or regional business sees $2,000 to $4,500 a month, and a national one $5,000 to $10,000 a month, both from BetOnAI and Sam Automates. ProsperSpark, an exception, puts the setup inside its monthly fee.

Those fees are not the whole bill. Builts.ai lists tool subscriptions on top of what it charges, and Main & Machine counts model usage and third-party tools as separate costs. A roadmap that leaves those out understates what each phase costs. Our AI consulting cost page gives the market’s setup and monthly ranges for each level.

What happens after the roadmap?

A roadmap only pays off if someone keeps it moving. On the price pages we read, ongoing AI advice comes as a monthly retainer. Read in October 2026, US agency price pages and guides put one at $1,800 to $7,500 a month for an established local business, from a monthly strategy call to about 16 hours a month (Vantage Point, IT Partner, Erin Moore and Leanware). At the multi-location or regional level it is $8,000 to $15,000 a month for about one to two days a week (Kore1 and Iternal), and for a national business $15,000 to $30,000 a month for 25 hours a month or more, up to two to three days a week (Iternal, Kore1 and Leanware). Ours is the fractional chief AI officer retainer: $2,250 to $3,000 a month for about 6 to 8 hours, $5,500 to $7,000 for about 16, and $13,000 to $18,000 for about 25 to 32.

Ours comes as coaching: working sessions with you and your team that keep the roadmap moving. Your proposal sets what the sessions cover and what they cost.

When a phase is ready to build, the work moves on. AI implementation sets one deployment out in full before it is built, AI integration connects a model to the systems you already use, and AI automation builds the workflow and runs it for you each month. Each is scoped in a proposal of its own.

What does AI strategy look like in practice?

We operate before we advise. We use what we recommend. Our working example is the order intake in AlvyOne, the operations system we built and run with Alvy Logistics; DSI Transportation shares the order system. Alvy is owned by our co-founder Noah Alvarez, and DSI is an Alvy company. The AlvyOne case study follows it from the first build to today.

The intake reads the emails that reach the order inboxes, sets aside what isn’t an order, and pulls each order’s details from the message and any attachments. It matches the order to the client account that sent it, checks the address and creates the order in the dispatch system through its API. That is the kind of step a roadmap looks for: reading and retyping that is the same job each time, even when orders arrive in different formats, with a clear point where a person takes over.

Running it took planning beyond the model. When something is missing or unclear, the intake holds the job and posts a note in the dispatch team’s chat saying what is missing, for a person to pick up. A health report runs every 15 minutes, and two switches can stop it. It stops at the order, too: no driver is assigned automatically. A roadmap phase built on that pattern names who answers the held items, how the step’s health is checked and how it is switched off.

When is an AI strategy not worth paying for?

AI roadmap consulting isn’t always the right first purchase, and we will say so on the call when it isn’t:

• You already know the one task: if a single workflow is eating your team’s week, start with AI automation, or with AI implementation if the build needs planning in full first.
• The task follows the same rule every time: then a Zapier, Make or n8n workflow does it without a model, and a roadmap would only tell you that.
• You want to look before you commit: an AI readiness assessment on its own ranks where AI fits without the full roadmap, and our guide to what to automate first helps you sort your own list.
• The decision is about a person: hiring screens and other significant decisions about people are work we don’t take on.

If you aren’t sure which of these fits, book a 15-minute call and bring your list of tasks. We will tell you whether a roadmap is worth it before you pay for one.