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Everything you need to know about AI compliance.
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AI Vendor Selection Guide
How to evaluate and select AI compliance vendors and tools for your organization.
AI Vendor Selection Guide: How to Choose the Right AI Partner
Last Updated: January 23, 2026
Build vs. Buy vs. Hybrid
Build In-House
Pros: Full control, IP ownership, custom solution
Cons: Expensive ($500K-$2M), slow (12-24 months), requires expertise
Best for: Unique problems, large companies, strategic AI
Buy Vendor Solution
Pros: Fast (3-6 months), proven technology, lower risk
Cons: Less control, ongoing fees, limited customization
Best for: Common problems, SMBs, tactical AI
Hybrid (Recommended)
Pros: Balance of speed and customization
Cons: Requires coordination
Best for: Most companies (70% choose this)
Vendor Evaluation Criteria
1. Technical Capability (30%)
- [ ] Relevant AI expertise (NLP, computer vision, etc.)
- [ ] Technology stack matches your needs
- [ ] Proven accuracy (90%+ for your use case)
- [ ] Scalability (handles your volume)
- [ ] Integration capabilities (APIs, SDKs)
2. Domain Experience (25%)
- [ ] Experience in your industry
- [ ] Similar use cases completed
- [ ] Understanding of your business
- [ ] Regulatory knowledge
- [ ] Reference customers
3. Compliance & Security (20%)
- [ ] SOC 2 Type II certified
- [ ] GDPR/CCPA compliant
- [ ] Industry certifications (HIPAA, FedRAMP)
- [ ] Data handling policies
- [ ] Bias testing capabilities
4. Cost & Value (15%)
- [ ] Transparent pricing
- [ ] ROI demonstrated
- [ ] No hidden fees
- [ ] Flexible contracts
- [ ] Payment terms
5. Support & Partnership (10%)
- [ ] Dedicated support team
- [ ] SLA guarantees
- [ ] Training provided
- [ ] Documentation quality
- [ ] Ongoing optimization
Vendor Types
Type 1: Full-Service AI Consultancies
Examples: Accenture, Deloitte, McKinsey
Cost: $500K-$5M projects
Best for: Large enterprises, complex problems
Pros: End-to-end service, strategic guidance
Cons: Expensive, slow, may use junior staff
Type 2: Specialized AI Firms
Examples: DataRobot, C3 AI, Databricks
Cost: $100K-$1M projects
Best for: Mid-market, specific use cases
Pros: Deep expertise, proven technology
Cons: Limited scope, may not integrate well
Type 3: Platform Providers
Examples: AWS, Google Cloud, Azure
Cost: $10K-$500K (mostly usage-based)
Best for: Tech-savvy companies, standard use cases
Pros: Scalable, integrated, cost-effective
Cons: Requires technical expertise, limited support
Type 4: Niche Solution Providers
Examples: Industry-specific vendors
Cost: $50K-$500K
Best for: Specific industries/use cases
Pros: Pre-built solutions, fast deployment
Cons: Limited customization, vendor lock-in
RFP Process
Step 1: Define Requirements (Week 1)
- Problem statement
- Success criteria
- Technical requirements
- Budget range
- Timeline
Step 2: Create RFP (Week 2)
- Company background
- Project scope
- Technical specifications
- Evaluation criteria
- Submission deadline
Step 3: Vendor Research (Week 2)
- Identify 10-15 potential vendors
- Review websites, case studies
- Check reviews (G2, Gartner)
- Send RFP to 5-7 vendors
Step 4: Proposal Review (Weeks 3-4)
- Score proposals against criteria
- Shortlist 2-3 vendors
- Check references
- Request demos
Step 5: Vendor Demos (Week 5)
- Live demonstrations
- Technical deep-dives
- Q&A sessions
- Proof of concept (optional)
Step 6: Final Selection (Week 6)
- Compare finalists
- Negotiate contracts
- Select winner
- Kick off project
Total timeline: 6 weeks
Red Flags
🚩 Guaranteed Results
Claim: "We guarantee 99% accuracy"
Reality: AI is probabilistic, no guarantees possible
Action: Ask for realistic accuracy ranges
🚩 No Domain Experience
Claim: "We can do any AI project"
Reality: Domain expertise matters
Action: Require relevant case studies
🚩 Black Box Solutions
Claim: "Our proprietary AI is too complex to explain"
Reality: You need explainability for compliance
Action: Require model transparency
🚩 No Compliance Discussion
Claim: "Compliance is your responsibility"
Reality: Vendor should help with compliance
Action: Require compliance support
🚩 Unrealistic Timelines
Claim: "We'll have this done in 4 weeks"
Reality: AI projects take 3-6 months minimum
Action: Demand realistic timeline
🚩 No References
Claim: "Our clients are confidential"
Reality: Legitimate vendors have references
Action: Require 3+ references
🚩 Unclear Pricing
Claim: "We'll figure out pricing as we go"
Reality: Recipe for cost overruns
Action: Demand fixed-price or clear T&M rates
Contract Negotiation
Key Terms to Negotiate
1. Scope & Deliverables
- Specific deliverables defined
- Acceptance criteria clear
- Change order process
- Milestones with payments
2. Pricing
- Fixed price vs. T&M
- Payment schedule
- Expense caps
- Cancellation terms
3. IP & Data
- Who owns the model?
- Who owns the data?
- Can you use model elsewhere?
- Data deletion after project
4. Performance
- Accuracy guarantees (realistic)
- SLA for uptime
- Response time commitments
- Penalties for non-performance
5. Support
- Training included?
- Ongoing support terms
- Bug fixes included?
- Update frequency
6. Compliance
- Vendor compliance certifications
- Bias audit support
- Regulatory change updates
- Liability allocation
Vendor Scorecard
| Criterion | Weight | Vendor A | Vendor B | Vendor C | |-----------|--------|----------|----------|----------| | Technical Capability | 30% | 85/100 | 90/100 | 75/100 | | Domain Experience | 25% | 70/100 | 85/100 | 90/100 | | Compliance & Security | 20% | 90/100 | 80/100 | 70/100 | | Cost & Value | 15% | 60/100 | 75/100 | 85/100 | | Support & Partnership | 10% | 80/100 | 85/100 | 75/100 | | Weighted Score | | 78/100 | 84/100 | 79/100 | | Recommendation | | | ✅ Select | |
Reference Check Questions
Technical Questions
- What was the final accuracy achieved?
- How long did implementation take?
- Were there any technical issues?
- How well did they integrate with your systems?
- Would you use them again?
Business Questions
- Did they stay within budget?
- Did they meet deadlines?
- How was communication?
- Were there any surprises?
- What would you do differently?
Compliance Questions
- Did they help with compliance?
- Any regulatory issues?
- How did they handle data privacy?
- Bias testing performed?
- Any audit findings?
Cost Comparison
| Vendor Type | Project Cost | Ongoing Cost | Timeline | |-------------|--------------|--------------|----------| | Big 4 Consulting | $500K-$5M | $200K-$1M/yr | 12-24 mo | | Specialized Firm | $100K-$1M | $50K-$300K/yr | 6-12 mo | | Platform Provider | $50K-$500K | $20K-$200K/yr | 3-9 mo | | Niche Solution | $50K-$300K | $30K-$100K/yr | 3-6 mo |
Next Steps
If you're ready to select a vendor:
- Download RFP template
- Review use cases - Know what's possible
- Calculate budget - Set realistic budget
- Book consultation - Get vendor recommendations
If you need more preparation:
- Assess readiness - Are you ready?
- Read: Building AI - Understand the process
- Contact us - Discuss your needs
Last Updated: January 23, 2026
Questions? Contact us