Why Purpose-Built AI Matters for DDQ & RFP Responses And Why Generic AI Tools Fall Short

Why Purpose-Built AI Matters for DDQ & RFP Responses And Why Generic AI Tools Fall Short

AI has quickly become part of everyday workflows across asset management. On the operational side of things, many teams have experimented with tools like ChatGPT or Copilot to help draft responses, summarize documents, or reword content. While these tools can be useful in isolated tasks, they were never designed to support the full complexity, risk sensitivity, and collaboration demands of the DDQ and RFP response process. For asset managers facing increasing diligence volume, tighter timelines, and heightened scrutiny, the difference between using AI and implementing a purpose-built AI solution is material.

Here’s why:

1. DDQ & RFP Responses Demand a System of Record, Not a Standalone AI Prompt

Generic AI tools operate in a stateless, ad-hoc manner. Each prompt is disconnected from prior answers, approvals, and context. That’s fundamentally misaligned with how diligence responses actually work. A purpose-built platform like CENTRL’s Response360 is anchored by a centralized Answer & File Library that serves as a true source of truth:

• Fully customizable answer records tied to strategies, products, vehicles, and business units
• Supporting files (ie, ESG reports, compliance manuals, policies) are oftentimes linked directly to answers
• Maintenance workflows that prompt periodic reviews and updates to ensure freshness

Instead of re-creating responses every time or trusting an AI model to “remember” prior language, teams work from approved, version-controlled content that evolves systematically over time. This is foundational. Without it, AI simply accelerates inconsistency.

2. End-to-End Workflow Matters More Than Point Solutions

DDQs and RFPs are not just about writing answers. They are operational workflows with multiple stages and stakeholders.

Generic AI tools do not:

• Import structured questionnaires
• Preserve formatting
• Track question-level edits
• Export responses back into the original file

A purpose-built solution supports the full end-to-end lifecycle:

• Seamless import of Word, PDF, and Excel questionnaires
• AI-powered answer population, prioritizing verbatim Answer Library matches and generating new responses only when needed
• Structured editing at the question level
• Export to the original format, maintaining the exact structure required by LPs and consultants

This is the difference between experimenting with AI and operationalizing it.

3. Collaboration, Approvals, and Audit Trails Are Non-Negotiable

DDQ and RFP responses are inherently cross-functional. IR, Compliance, Legal, IT, ESG, and senior leadership all touch the process - and accountability matters. Generic AI tools were never built for this environment.

Purpose-built platforms enable:

• Assignment of questions or sections to specific individuals or teams
• Defined review and approval workflows
• Commenting, redlining, and iterative feedback
• Full audit trails showing who edited what, when, and why

This ensures responses are not only efficient but consistent, compliant, and defensible, which is a requirement for regulated asset managers.

4. Accuracy Comes From Domain Training, Not General Intelligence

Large, general-purpose language models are impressive, but they are not experts in asset management.

They struggle with:

• Industry-specific acronyms
• Nuanced strategy distinctions
• Regulatory terminology
• Product-level differentiation

Response360 leverages vertically trained, asset-management-specific models designed to understand how DDQs are written, evaluated, and reviewed.

This results in:

• Higher accuracy
• Fewer hallucinations
• Better alignment with how institutional investors expect answers to be structured

Accuracy is not just a quality issue - it’s a risk issue.

5. The Goal Is Scalable Confidence, Not Faster Guesswork

AI should not replace diligence. It should elevate it. The true value of a purpose-built AI solution is not simply speed - it’s enabling teams to scale their diligence response process with confidence:

• Confidence that answers are consistent
• Confidence that content is current
• Confidence that responses are explainable and traceable

Generic AI tools can help draft text. Purpose-built platforms help run the business.

The DDQ and RFP response process sits at the intersection of revenue generation, compliance, and reputation. It demands more than generic AI assistance. For asset managers looking to drive efficiency without sacrificing accuracy, consistency, or control, purpose-built AI platforms like CENTRL’s Response360 are not a nice-to-have; they’re a necessity.