AI RFP Template: Key Sections and Questions to Include

A well-structured RFP (Request for Proposal) separates serious AI vendors from those who can't deliver. It forces clarity on your requirements and generates comparable responses. This guide provides a comprehensive AI-specific RFP template.

Executive Summary

• RFPs establish clear requirements and enable apples-to-apples vendor comparison
• AI-specific RFPs must address data handling, model performance, and ongoing learning
• Balance comprehensiveness with response burden—overly long RFPs get poor responses
• Include security and compliance requirements upfront to avoid surprises later
• Define evaluation criteria in the RFP for transparency and fairness
• Set realistic timelines—too short limits quality responses; too long loses momentum
• RFP responses reveal vendor maturity and attention to detail
• Follow-up questions and clarifications are normal and expected

Why This Matters Now

AI procurement differs from traditional software:

• Performance claims are harder to verify
• Data handling raises unique privacy questions
• "AI" can mean anything from simple rules to sophisticated ML
• Integration complexity is often underestimated
• Vendor landscape changes rapidly

A strong RFP surfaces these issues early, before contracts are signed and implementations begin.

Definitions and Scope

RFP (Request for Proposal): Formal document requesting vendor proposals for a specific project or procurement.

RFI (Request for Information): Preliminary inquiry to gather vendor information before formal RFP.

Scope of Work (SOW): Detailed description of work to be performed, often attached to RFP or contract.

Scope of this guide: Creating AI-specific RFPs for commercial software/platform procurement—not custom development or consulting services.

AI RFP Structure

Section 1: Introduction and Background

Company overview:

• Brief company description
• Industry and relevant context
• AI maturity and existing capabilities

Project overview:

• High-level project description
• Business drivers and objectives
• Timeline overview

RFP process:

• Key dates (questions, submission, evaluation)
• Contact information and communication rules
• Confidentiality expectations

Example content:

1. INTRODUCTION

1.1 Company Background
[Company Name] is a [industry] company with [X] employees operating 
in [geography]. We are seeking to implement AI-powered [capability] 
to support our [business objective].

1.2 Project Overview
This RFP seeks proposals for [specific solution/capability]. The 
successful vendor will provide [brief scope]. Target implementation 
is [timeframe].

1.3 RFP Timeline
- RFP Issue Date: [Date]
- Vendor Questions Due: [Date]
- Response to Questions: [Date]
- Proposal Submission Deadline: [Date]
- Vendor Presentations: [Date range]
- Selection Decision: [Date]
- Projected Contract Signing: [Date]

Section 2: Scope and Requirements

Functional requirements:

• Detailed capability requirements
• Use cases to be supported
• User types and volumes
• Performance expectations

Technical requirements:

• Integration requirements
• Data requirements
• Architecture constraints
• Scalability needs

AI-specific requirements:

2.4 AI/ML SPECIFIC REQUIREMENTS

2.4.1 Model Performance
- Required accuracy/performance levels
- Performance measurement methodology
- Benchmark data availability
- Performance degradation handling

2.4.2 Data Requirements
- Training data: who provides, how much, what format
- Ongoing data requirements
- Data quality expectations
- Handling of edge cases and exceptions

2.4.3 Model Transparency
- Explainability requirements
- Model documentation expectations
- Audit/traceability needs
- Bias monitoring and mitigation

2.4.4 Continuous Learning
- Model update frequency
- Retraining process and triggers
- Version control and rollback
- Performance monitoring requirements

Section 3: Security and Compliance Requirements

Data protection:

• Data classification and handling
• Encryption requirements
• Access control requirements
• Data retention and deletion

Compliance:

• Regulatory requirements (PDPA, industry-specific)
• Required certifications
• Audit requirements
• Geographic restrictions

Example questions:

3. SECURITY AND COMPLIANCE

Please respond to the following:

3.1 Data Handling
a) Where will our data be stored and processed (geography/jurisdiction)?
b) Describe your data encryption approach (at rest and in transit).
c) How is access to customer data controlled and audited?
d) Is our data used to train your AI models? If yes, how can we opt out?
e) What happens to our data upon contract termination?

3.2 Certifications and Compliance
a) List all security certifications held (SOC2, ISO27001, etc.)
b) Provide copies of current certification reports.
c) Describe your compliance with PDPA (Singapore/Malaysia).
d) What is your data breach notification process?

3.3 Security Practices
a) Describe your secure development lifecycle.
b) How often do you conduct penetration testing? Provide summary.
c) Describe your vulnerability management process.
d) What is your incident response process?

Section 4: Implementation and Support

Implementation approach:

• Proposed methodology
• Resource requirements (vendor and client)
• Timeline expectations
• Risk identification

Training and change management:

• Training approach
• Documentation provided
• Change management support

Ongoing support:

• Support model and hours
• SLA commitments
• Escalation process
• Customer success resources

Example requirements:

4. IMPLEMENTATION AND SUPPORT

4.1 Implementation
Please describe:
a) Your proposed implementation methodology and phases
b) Typical timeline for implementations of this scope
c) Resources required from [Company Name]
d) Key risks and mitigation approaches
e) How you define and measure implementation success

4.2 Support
Please describe:
a) Support hours and channels
b) SLA commitments (response time, resolution time)
c) Escalation process for critical issues
d) Customer success/relationship management approach
e) How support requests are tracked and reported

Section 5: Vendor Information

Company background:

• History and ownership
• Financial stability
• Employee count and growth
• Geographic presence

Product information:

• Product history and roadmap
• Technology stack
• R&D investment
• Competitive positioning

Customer references:

• Reference requirements
• Case study requests

Example questions:

5. VENDOR INFORMATION

5.1 Company Profile
a) Year founded and ownership structure
b) Total employees and relevant team size
c) Annual revenue (or revenue range)
d) Funding history (if applicable)
e) Geographic presence and support coverage

5.2 Product
a) Product launch date and version history
b) Number of active customers
c) Product roadmap highlights (next 12-24 months)
d) Technology stack and architecture overview
e) Third-party components or dependencies

5.3 References
Please provide 3 references that are:
- In similar industry or use case
- Similar company size
- Live for at least 6 months
Include: company name, contact person, email, phone, brief description.

Section 6: Pricing

Pricing structure:

• Pricing model and components
• License/subscription terms
• Implementation costs
• Ongoing costs

Scenario pricing:

• Current state pricing
• Growth scenario pricing
• Optional components pricing

Example template:

6. PRICING

Please provide pricing for the following scenarios:

6.1 Year 1 Costs
| Component | One-Time | Monthly/Annual |
|-----------|----------|----------------|
| Software license/subscription | | |
| Implementation services | | |
| Training | | |
| Integration | | |
| Support (if separate) | | |
| Other (specify) | | |
| TOTAL YEAR 1 | | |

6.2 Ongoing Annual Costs (Years 2-3)
| Component | Year 2 | Year 3 |
|-----------|--------|--------|
| Software | | |
| Support | | |
| Other | | |
| TOTAL | | |

6.3 Pricing Assumptions
Please list all assumptions underlying this pricing.

6.4 Pricing Model
Describe your pricing model (per user, per transaction, platform fee, etc.)
How does pricing scale with increased usage?

Section 7: Evaluation Criteria

Criteria and weighting: Be transparent about how you'll evaluate:

7. EVALUATION CRITERIA

Proposals will be evaluated based on the following criteria:

| Criterion | Weight |
|-----------|--------|
| Functional capabilities and fit | 25% |
| Technical approach and architecture | 15% |
| Security and compliance | 20% |
| Implementation approach | 10% |
| Support and partnership | 10% |
| Vendor viability | 10% |
| Pricing | 10% |

Section 8: Response Instructions

Format requirements:

• Page limits
• Required sections
• File formats

Submission instructions:

• Where to submit
• Deadline (date and time with timezone)
• Late submission policy

RFP Development Checklist

Before Writing:

• Defined business requirements
• Defined technical requirements
• Defined security requirements
• Gathered stakeholder input
• Set timeline and milestones

Content Development:

• Wrote company and project background
• Documented functional requirements
• Documented technical requirements
• Included AI-specific requirements
• Included security/compliance requirements
• Defined implementation/support expectations
• Created pricing template
• Defined evaluation criteria

Quality Review:

• Legal review (if required)
• Security review
• Technical review
• Stakeholder sign-off

Distribution:

• Identified recipient vendors
• Prepared distribution list
• Set up Q&A process
• Established evaluation team and timeline

Common Failure Modes

1. Vague Requirements

Problem: Requirements too high-level to generate comparable responses Prevention: Be specific; include metrics, volumes, and scenarios

2. Unrealistic Timeline

Problem: Insufficient time for quality responses Prevention: Allow 2-4 weeks for response; longer for complex RFPs

3. Missing AI-Specific Questions

Problem: Standard software RFP doesn't cover AI concerns Prevention: Include data handling, model performance, continuous learning sections

4. Overlong RFP

Problem: Vendors provide superficial responses to exhaustive documents Prevention: Focus on what matters; eliminate nice-to-know questions

5. No Q&A Process

Problem: Vendors make assumptions that invalidate responses Prevention: Build in formal Q&A period; share answers with all vendors

6. Hidden Evaluation Criteria

Problem: Vendors can't emphasize what matters to you Prevention: Publish evaluation criteria and weights

Metrics to Track

FAQ

Q: How long should an AI RFP be? A: Typically 15-30 pages for significant procurement. Focus on requirements, not background filler.

Q: Should we include our budget? A: Opinions vary. Including budget range can focus responses; not including may reveal market pricing. Consider your leverage.

Q: How many vendors should we send the RFP to? A: Typically 5-10 for competitive process. More than 10 creates evaluation burden; fewer may not generate competition.

Q: What if vendors ask to present before submitting? A: Decide upfront and apply consistently. Brief presentations can help, but may bias toward polished presenters.

Q: How do we handle vendor questions that reveal strategy? A: Share all Q&A with all vendors (anonymized) for fairness and to improve all responses.

Q: Should we require a POC commitment in the RFP? A: You can ask about POC willingness and approach, but committing in RFP stage is premature. POC typically follows RFP evaluation.

Next Steps

A well-crafted RFP sets the foundation for successful vendor selection. It clarifies your requirements, enables fair comparison, and reveals vendor capabilities and maturity.

Need help developing your AI procurement approach?

Book an AI Readiness Audit to get expert guidance on requirements definition and vendor selection.

References

• NIGP: "Developing and Managing RFPs"
• Gartner: "Best Practices for Writing Effective RFPs"
• CIPS: "Guidance on Tendering and RFPs"
• UK Government Digital Service: "Technology Code of Practice"