SBA · SBA-30 · record R3186

SBA.gov External Customer Chatbot

Small Business Administration · OCPL: Office of Communications & Public Liaison

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not high impact: This AI system does not meet the criteria of any of the six pillars that make up High Impact AI in Memorandum M-25-21.
Start date: 2026-01-10 (day precision)Source: 01/10/2026 00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Service Delivery
Operational functions: Chatbot or virtual assistant, Public-facing customer service Derived by keyword rules; see methodology

Problem the AI is intended to solve

Customer service teams are overwhelmed with routine inquiries that slow response times and prevent agents from focusing on complex, high-value customer issues. Manual case classification and routing is time-consuming and inconsistent. Customers expect 24/7 support and instant, personalized responses based on their account history.

Expected benefits

Automates 30-40% of routine customer service interactions, reducing agent workload and response times by up to 50%. Provides 24/7 instant customer support with personalized responses grounded in CRM data. Enables intelligent case classification and routing to appropriate agents. Allows human agents to focus on complex and emotional customer issues. Improves customer satisfaction through faster resolutions and consistent service quality. Scales customer service capacity without linear growth in headcount.

System outputs

AI-powered autonomous customer service agent and chatbot integrated into Salesforce CRM. Uses natural language processing (NLP), generative AI, and machine learning to understand customer intent, provide personalized responses grounded in Salesforce CRM data, and automate routine customer service interactions. Handles case classification, intelligent routing, 24/7 customer support, and seamless escalation to human agents. Input: customer inquiries via chat, email, or web. Output: conversational responses, case creation and routing, personalized solutions based on customer history, account information, and service recommendations.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Salesforce Service Cloud with Einstein
Custom-developed code: No
Public source code: Not applicable - No custom code

Sourcing

How it was built: Purchased from vendorSource: a) Purchased from a vendor
Vendor (as reported): Salesforce, Inc.
Vendors (standardized): Salesforce

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Yes
Privacy Impact Assessment: Not publicly available
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Commercial vendor-managed training data with Salesforce CRM data integration
Federal Data Catalog: Not applicable - Proprietary vendor training data

Governance

8 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingReported in placeSource: a) Yes

AI impact assessmentReported in placeSource: a) Yes

Independent reviewReported in placeSource: a) Yes – by another appropriate agency office or reviewer not directly involved in the AI’s development

Ongoing monitoringReported in placeSource: a) Yes, sufficient monitoring protocols have been established

Operator trainingReported in placeSource: a) Yes, sufficient and periodic training has been established

Fail-safeReported in placeSource: a) Yes

Appeal processReported in placeSource: a) Yes, an appropriate appeal process has been established

User and public consultationOther or ambiguous answerSource: Conducted pilot testing with customer service teams, collected agent feedback on chatbot performance and handoff quality, monitored customer satisfaction scores and resolution times, established feedback loops through case reviews and quality assurance processes, and continuously refined bot responses based on customer interactions and agent insights.Flag: free-text answer

Potential impacts and how they were identified

Potential impacts include quality and consistency of customer service responses, case routing decisions, and customer satisfaction. Impacts identified through vendor documentation, pilot testing with customer service teams, and usability studies. Mitigation includes human agent oversight and escalation protocols, CRM data validation, response accuracy monitoring, customer feedback mechanisms, and Einstein Trust Layer security protections for data privacy.