You bought Copilot licenses and nobody uses them
You bought Copilot licenses for the team six months ago. You pay for 50 seats every month. You checked the usage dashboard last week and maybe eight people are actually logging in, and most of them are using it to summarize emails. Nothing in the operation has changed. You are starting to wonder whether you picked the wrong tool, or whether the problem is somewhere else entirely.
The condition is that every AI SaaS tool on the market is excellent at what it does. The reality is that what they do is deliver a productivity layer on top of a working foundation, and most mid-market operations do not have the foundation in place. What to do is to stop blaming the tool and look at the data layer underneath it. That is usually where the real problem is, and it is not a problem a SaaS license can fix.
Fractional Head of AI vs AI SaaS tool, side by side
Nine dimensions that matter for a mid-market operator. Cost numbers use the published Work-Smart.ai ranges and list pricing for the enterprise AI SaaS category (Copilot, ChatGPT Enterprise, Glean) at 50 seats over 12 months.
| Dimension | Fractional Head of AI | AI SaaS tool (Copilot, ChatGPT Enterprise, Glean) |
|---|---|---|
| What it is | A person who builds your AI operating system. | A product you rent per seat. |
| What it solves | Your actual workflows on your actual data. | A generic use case, well. |
| Data readiness required | I fix the data layer first. | You need the data layer already in place. |
| Customization | Built on your documents, your processes, your language. | Generic model with enterprise controls. |
| Cost (50 seats, 12 months) | $60K to $144K retained, plus any build scope. | $12,600/year for Copilot Business at $21/user/month (50 seats), plus the base M365 license on top. Annual commitment required, no monthly billing option. |
| Active user conversion | Systems map to real workflows the team already runs. | Copilot: 35.8% of licensed users are active. ChatGPT Enterprise: 83.1%. When companies buy SaaS AI tools, only a third of Copilot seats produce output. |
| What actually gets used | Custom systems built on your workflows from day one. | Gartner found only 5% of companies that completed Copilot pilots moved to larger deployment. 70% of users with access to all three platforms choose ChatGPT as their primary tool. |
| Ownership | You own the systems, the data, the prompts. | You rent access. Cancel and the access ends. |
| When it fails | I fix it. One person, one phone number. | Support ticket. 3 to 5 business day response. |
| Best fit | You need someone who will build, not someone to call. | Mature data stack, you want a productivity layer on top. |
The row that decides most engagements is "data readiness required." A SaaS tool assumes the foundation is already there. A fractional engagement fixes the foundation first and then decides which tools belong on top. If your team is sitting on unused licenses, that is the row to reread.
When a SaaS tool is actually the right choice
If your data layer is already clean, your team is already adopting the tool, and you just want a productivity layer on top, buy the SaaS license. Copilot, ChatGPT Enterprise, and Glean are good at what they do. Microsoft and OpenAI and Glean have shipped excellent products and I recommend them often. If your workflows are already mapped, your documents are already indexed, your CRM is already a single source of truth, and your team has already said yes to AI tools, the SaaS license is the right call and there is no fractional engagement that will do better.
If your company runs on Microsoft 365 and your team's highest-value AI use cases are meeting recaps, email summarization, and document drafts, Copilot is a strong fit. It works inside the apps you already use without introducing a new platform.
If you bought the license and nothing changed, the problem is upstream. That is what I fix. For a detailed breakdown of Copilot capabilities, cost, and failure patterns, read the full mid-market Copilot guide.
When a Fractional Head of AI is the right choice
Your data is scattered across Excel, email, WhatsApp, a CRM nobody updates, and a shared drive with 40,000 files. Your team is not adopting the AI tools you already bought. Your workflows are tribal knowledge. You have 20 to 500 employees and $5M to $100M in revenue. You want a partner who ships production systems, not a vendor who ships a login page.
The most common pattern I see: a company buys Copilot because they already have Microsoft 365, then discovers that Copilot only works inside Microsoft apps. Their CRM, their WhatsApp conversations, their QuickBooks, their industry-specific tools: none of it is visible to Copilot. That is when they call me. The Copilot handles what it handles. I build everything else.
A Fractional Head of AI starts with the data layer, writes a prompt library for your business, builds the custom systems the SaaS tools do not cover, and trains the team on whichever tools actually fit. The service page has the pricing, deliverables, and engagement phases. Most of my clients end up running SaaS licenses and a fractional engagement side by side, which is usually the right shape for a 50 to 150 person operator.
A client where Copilot did not solve the real problem
A mid-market construction client had rolled out Copilot across a team of 40 before I was brought in. The usage dashboard showed a predictable pattern. Email summaries. Meeting recaps. A little bit of drafting. The problem the CEO had hired Copilot to solve, which was that site managers were spending 60 minutes per project finding the right document across project folders and email, had not moved. Copilot could not solve it because the documents were not indexed, the folder structure was inconsistent across projects, and the naming conventions were tribal knowledge.
The fractional engagement started with the data layer. We built a custom document search system that actually understood the folder structure and the naming conventions. Search time dropped from 60 minutes to roughly 30 seconds. Copilot stayed in place for email and meeting work, where it was genuinely useful. The two tools coexisted because they solved two different problems. The license was not the issue. The foundation was.
The point is not that Copilot was the wrong product. The point is that a productivity layer cannot fix a broken foundation, and no amount of license spend will change that. Once the foundation was in place, the SaaS tool became useful again.