Managed AI Services vs Project-Based Consulting
Should you outsource AI operations ongoing or hire consultants for specific projects? The right model depends on your AI maturity, internal capabilities, and long-term plans.
Understanding Both Approaches
Defined scope, defined timeline, defined outcome
Best For:
Companies wanting specific AI outcomes without ongoing commitments
Ongoing AI operations handled by an external team
Best For:
Companies wanting AI handled by experts on an ongoing basis
Key Differences at a Glance
| Factor | Project-Based AI Consulting | Managed AI Services |
|---|---|---|
| Long-term Commitment | Project ends, no obligation | Monthly contract, ongoing dependency |
| Internal Capability | Team learns and owns the work | Vendor owns and manages the work |
| Continuous Optimization | Ends when project completes | Ongoing monitoring and improvement |
| Cost Predictability | Fixed project cost, then done | Predictable monthly costs |
| Vendor Dependency | Low (knowledge transferred to team) | High (vendor runs your AI) |
| 24/7 AI Operations | Your team manages post-project | Vendor handles all operations |
When Each Model Works Best
- You want to build internal AI capability
- Your AI needs are project-based (implement, then maintain)
- You don't want ongoing vendor dependency
- Budget works better as one-time investment, not monthly
- Your team can manage AI systems after handoff
- AI is mission-critical and needs 24/7 monitoring
- Your team can't or shouldn't manage AI operations
- Continuous optimization is needed (ML models, data pipelines)
- Monthly predictable costs work better for your budget
- You want someone else responsible for AI uptime
Engagement Model Comparison
Different models for different AI maturity levels and needs.
| Factor | Project-Based AI Consulting | Managed AI Services |
|---|---|---|
| Scope | Defined deliverables | Ongoing operations |
| Duration | 4-16 weeks typically | 12+ months |
| Knowledge Transfer | ||
| Ongoing Monitoring | ||
| Government Funding Eligible | Rarely | |
| Vendor Lock-in Risk | Low | High |
Choose Project-Based AI Consulting When...
- You want to build internal AI capability, not outsource it
- Your AI needs are project-based with clear start and end
- You prefer one-time investment over ongoing monthly costs
- Knowledge transfer and team upskilling are priorities
- You want to avoid long-term vendor dependency
Choose Managed AI Services When...
- AI systems need 24/7 monitoring and your team can't provide it
- Continuous ML model retraining is needed
- You explicitly don't want to manage AI operations internally
- Monthly predictable costs fit your financial model better
- AI operations complexity exceeds your team's capability
How Pertama Can Help
Whichever approach you choose, Pertama Partners can support your AI journey.
Frequently Asked Questions
Yes. Many companies start with a project to build their AI foundation, then evaluate whether they need ongoing managed services. If your team can handle operations post-project, you won't need managed services — saving significant ongoing costs.
Essentially, yes. Managed AI services means an external vendor operates your AI systems. This can be valuable if AI operations aren't your core competency, but it creates vendor dependency. For most SMBs, building internal capability through project-based consulting is more sustainable.
Your team should be able to manage and maintain the AI solutions independently. Good consultants (like Pertama) include knowledge transfer and documentation as part of every project. If you need additional help later, you can engage again for specific needs.