A full-time AI lead costs $150,000 or more per year before benefits and overhead. Most small businesses don't need that, and can't justify it. What they do need is someone accountable for AI results, not just AI advice. That's what a fractional AI consultant delivers.
Most small businesses know AI can help them. The challenge isn't finding AI tools. It's figuring out which ones are worth your time, getting them implemented correctly, and making sure they keep producing results after the initial setup.
A dedicated AI director or VP of AI is a $150,000-plus annual commitment. That overhead makes sense for a large enterprise. For a 10- to 75-person business, it doesn't. The fractional model gives you the same expertise at 20 to 30 cents on the dollar.
A consultant builds something, hands it off, and leaves. Three months later, the workflow is half-broken, nobody knows why it was built the way it was, and you're back where you started. Ongoing engagement is what keeps AI implementations working as your business evolves.
Webinars and blog posts tell you AI is transformative. They don't tell you which tool to connect to your scheduling system, how to test whether it's actually working, or what to do when it produces the wrong output. That translation work is what a fractional consultant does.
A fractional consultant is a senior professional who works with your business on a part-time, ongoing basis rather than as a full-time employee. You get the expertise and accountability of a dedicated hire without the salary, benefits, and overhead that come with it.
The concept is well established in finance (fractional CFO) and marketing (fractional CMO). The same logic applies to AI leadership. Your business needs someone who understands the technology, knows your operations, and is responsible for producing measurable results, but probably doesn't need that person in-house 40 hours a week.
QP's managed retainer is built around this model. You get a named consultant who learns your business, sets the AI strategy, handles or oversees implementation, and stays engaged month to month to make sure things are working. Not a support queue. Not a project team you'll never see again. One person, accountable for your outcomes.
Discovery and Assessment
We start by understanding your operations: where time is lost, what tools you already use, and where AI can produce a real return. No assumptions about your industry or your setup.
Strategy and Prioritization
We build a clear roadmap: what gets built first, what success looks like, and how we'll measure it. Prioritized by ROI, not novelty.
Implementation
Workflows get built and tested against your actual data and systems. Everything is documented so your team understands what was built and why. Nothing goes live until it passes.
Ongoing Optimization
Monthly check-ins, performance reviews, and iteration as your needs evolve. Your AI implementations stay current and keep producing results.
The retainer covers the full cycle, from strategy through implementation to ongoing management. You are not buying advice. You are buying results.
Not a generic AI roadmap pulled from a template. A strategy built around your actual operations, your team's capacity, and the places where AI will produce the clearest return. Updated monthly as priorities shift.
Your consultant builds the workflows, connects the tools, and tests everything before it touches your live operations. You are not left to figure out the technical setup on your own. Implementation is part of the engagement.
AI workflows drift over time. Tools get updated, business processes change, and outputs that worked well six months ago may need adjustment. Monthly performance reviews catch these issues before they become problems.
Your team needs to understand and trust the tools they use. Your fractional consultant explains what was built, trains staff on new workflows, and makes sure the knowledge stays in your organization, not just in a consultant's head.
Both models can work. The question is which one makes sense for your business stage and budget right now.
A full-time AI director or engineer makes sense when AI is central to your product or you have enough ongoing work to justify full-time attention. The costs are substantial and the hiring process is slow.
The fractional model delivers the strategy, implementation, and ongoing management you need at a cost that fits a small business budget. Engagement starts in days, not months.
Greg Stone built his career doing Commissioning, Qualification, and Validation work inside FDA-regulated pharmaceutical and biologics manufacturing. That background shapes how QP approaches every AI implementation, regardless of industry.
In regulated environments, a workflow that "mostly works" is not good enough. Systems are tested against defined requirements, results are documented, and nothing goes into production until it passes. That discipline is not common in the AI consulting space, where most consultants are optimizing for fast delivery over reliable outcomes.
QP brings the same standard to small business AI work. Before any workflow goes live, it is tested against your actual data, with documented results. Your team understands what was built and why. And when something needs to change, there is a clear record of the original design to work from.
That is what makes the fractional model work over time. Not just getting something built quickly, but building it correctly so it stays working and keeps producing the results you hired it to produce.
Not sure where to start? Take the free AI Readiness Assessment to identify where AI can make the most impact in your business. If you are already looking at AI for a specific industry context, the SMB AI integration page covers the most common starting points.
The retainer makes sense for businesses that need ongoing AI leadership but are not at the stage where a full-time hire is justified. Here is a plain-language breakdown.
A fractional AI consultant is a senior AI professional who works with your business on a part-time or retainer basis rather than as a full-time employee. You get strategic direction, implementation oversight, and ongoing optimization without carrying a full salary, benefits, and overhead. It is the same concept as a fractional CFO or fractional CMO, applied to AI leadership.
A project consultant builds something and leaves. A fractional consultant stays engaged, monitors what was built, adjusts as your business changes, and keeps your AI implementations producing results over time. The ongoing relationship is what separates retainer-based work from a one-time delivery.
The retainer includes a monthly strategy session, hands-on implementation and workflow development, performance monitoring, and ongoing optimization as your tools and business needs evolve. You have a named consultant who knows your business rather than a support queue.
Small and mid-sized businesses that know AI is relevant to their operations but do not have the budget or workflow for a full-time AI hire. Typically 5 to 100 employees, across industries ranging from professional services and healthcare to construction, financial services, and non-profit. If you need someone accountable for AI results, not just AI advice, the fractional model fits.
Greg Stone's background is in CQV engineering inside FDA-regulated pharmaceutical and biologics manufacturing. That means QP approaches AI implementation with validation-grade rigor: defined requirements, documented testing, and a clear audit trail. The discipline comes from industries where something not working correctly has real consequences. That standard applies to every engagement, not just regulated ones.