A mid-market company wants to deploy AI. The conventional advice: hire a Chief AI Officer, build a data science team, recruit ML engineers. Total cost: Rs 2-3 Cr per year, minimum. Time to first deployment: 6-12 months.
There's a better way.
The Problem with Building In-House
Most mid-market companies (Rs 100-1000 Cr revenue) need AI capabilities, but they don't need a permanent AI organisation. Here's why:
The talent gap is real. Good AI engineers are expensive and scarce. You're competing with Google, Microsoft, and well-funded startups for the same talent pool. Mid-market compensation rarely wins this race.
Utilisation is low. After the initial deployment, a full AI team often has insufficient work to justify its cost. AI projects come in waves — intense during implementation, sparse during steady state.
Knowledge decays fast. AI moves quickly. A team that built great models in 2024 needs to completely retool for 2026's approaches. Continuous learning requires dedicated R&D time that's hard to justify in a cost centre.
The Fractional Model
Fractional AI leadership works like a fractional CFO: senior expertise on demand, without the permanent overhead.
What you get:
- Senior AI architects and engineers when you need them
- Access to a team that's deployed across dozens of companies (pattern recognition)
- Continuous exposure to the latest tools and techniques (because R&D is built into their model)
- Implementation, not just strategy — they build and deploy, not just advise
What you don't get:
- Rs 2-3 Cr annual AI team payroll
- 6-month ramp-up while new hires learn your business
- The risk of hiring the wrong AI lead (an expensive mistake)
When Fractional Makes Sense
Good fit:
- Revenue Rs 100-1000 Cr
- 2-5 AI use cases identified
- No existing AI team (or a small one that needs senior guidance)
- Want results in 90 days, not 12 months
- PE-backed companies with value creation timelines
Less suitable:
- Companies building AI as their core product (you need full-time)
- Very large enterprises with ongoing AI programme needs
- Organisations that need dedicated on-site resources daily
The Economics
| Item | In-House Team | Fractional |
|---|---|---|
| Time to first deployment | 6-12 months | 60-90 days |
| Breadth of expertise | Limited to hires | Full team on demand |
| R&D investment | Hard to justify | Built into model |
| Risk if it doesn't work | Severance + restart | Pause and reassess |
How We Do It
At CoVector AI, fractional engagement typically looks like:
- **Discovery Sprint (4-6 weeks):** Understand your business, identify AI opportunities, build a prioritised roadmap
- **Implementation (6-16 weeks):** Deploy Digital Employees for the highest-ROI use cases, with milestone-based delivery
- **Ongoing support (optional):** Retainer for optimisation, new use cases, and capability building
The key difference from traditional consulting: we don't hand over a PowerPoint and leave. We build, deploy, and stay until the solution is operational.
The Bottom Line
You need AI expertise, not AI headcount. Fractional leadership gives you the former without the latter — at a fraction of the cost and a fraction of the time.
