Wiley
autonomous genAI customer service agent (conversational self-service)
Wiley increased its case resolution by more than 40% within the first weeks with the Salesforce Agentforce genAI agent, while onboarding its seasonal agents 50% faster, for a Salesforce ROI of 213%.
Objective
Absorb routine service requests (account access, password reset) during peaks, to free up human agents for complex cases.
The deployment
Wiley, an academic and training publisher, deploys Agentforce for conversational self-service. The agent answers by drawing on Wiley's knowledge base and automatically resolves account access and password reset cases. When a case ends, Agentforce summarizes the conversation for the next person or supervisor, and Wiley uses these summaries to spot trends. Einstein separately helps agents draft their responses from the CRM and the knowledge base.
Results Proof C
Quantified Salesforce customer story (T2) corroborated by the established tech press diginomica (T3) covering the announcement at Dreamforce 24. Multiple concordant sources with independent press, hence C.
How it works
Documented architectureThe stack in detail
- plateforme Salesforce Agentforce Autonomous genAI agent that resolves routine requests (account access, password) and summarizes each case for the human handoff.
- plateforme Salesforce Service Cloud Foundation of Wiley's customer service: cases, routing, and escalation to human agents.
- outil Salesforce Einstein Helps human agents draft their responses from the CRM and the knowledge base.
- infra Base de connaissance Wiley Corpus that grounds the agent's responses; if it is outdated, the resolution rate drops and escalation rises.
How it runs, concretely
For ops teams-
1Grounding the agent Customer service team / AI
Agentforce is configured to answer from Wiley's knowledge base and CRM data.
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2Self-service resolution AI (Agentforce)
The agent handles routine requests (account access, password reset) conversationally and autonomously.
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3Summary and handoff AI (Agentforce)
At the end of a case, the agent summarizes the conversation for the next person or supervisor.
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4Escalation and analysis Human agents / supervisors
Complex cases go to a human agent; the summaries are used to spot trends and surface product feedback.
Wiley's knowledge base, which grounds the agent's responses. If it is incomplete or outdated, the agent resolves fewer cases and has to escalate more to humans.
How your customers perceive this type of use
Sourced studiesLes consommateurs n'acceptent pas les chatbots par defaut : 64% prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (Gartner, 2024) et pres d'un utilisateur sur cinq du service client par IA n'en retire aucun benefice (Qualtrics, 2025). L'acceptation se construit sur trois conditions mesurees par Salesforce : savoir qu'on parle a une IA, pouvoir escalader vers un humain, comprendre la logique de l'agent.
Acceptance conditions
- Etre informe qu'on parle a une IA et non a un humain (pres de 75% le demandent, Salesforce 2024)
- Un chemin d'escalade clair vers un agent humain (45% plus enclins a utiliser l'agent IA, Salesforce 2024)
- Une logique de l'agent clairement expliquee (44% plus enclins, Salesforce 2024)
Red lines
- Rendre l'humain injoignable : c'est la premiere inquietude des consommateurs sur l'IA dans le service client (Gartner 2024) et 50% craignent que l'IA les coupe du contact humain (Qualtrics 2025)
- Remplacer le service client par l'IA sans alternative : 53% envisageraient de partir chez un concurrent (Gartner 2024)
Sources: Salesforce 2024 · Gartner 2024 · Qualtrics 2025
How to replicate
Inference, not sourcedData prerequisites
- structured and up-to-date knowledge base
- customer CRM data accessible to the agent
- case history to frame the intents
Org prerequisites
- customer service on Salesforce Service Cloud
- human escalation process for complex cases
- governance over the agent's responses
Possible stack
- Salesforce Agentforce + Service Cloud
- any genAI service agent platform grounded on a knowledge base and CRM
The plan, step by step
- Step 1Update and structure the knowledge base on the highest-volume requests (account access, password).Deliverable: Up-to-date articles covering the target intents.
- Step 2Configure the agent: grounding on the base and the CRM, guardrails, escalation rules.Deliverable: Agent in sandbox validated on test scenarios.
- Step 3Launch the pilot on a share of chat traffic.Deliverable: Resolution rate compared to the old chatbot.
- Step 4Activate case summaries and the supervisor loop (trends, product feedback).Deliverable: Documented handoffs + trends surfaced each week.
- Step 5Widen the scope of intents based on the observed resolution rates.Deliverable: Extension plan prioritized by volume and success rate.
First step: Update and structure the knowledge base on the most frequent requests (account access, password), then ground the agent on it before widening the scope.
The same pattern, proven in other industries
ADT
genAI customer agent
Air India
genAI customer agent (automated customer service)
AT&T
Governed enterprise genAI assistant: an LLM connected to internal knowledge, open to tens of thousands of employees and called at scale by automated systems
Sources
- S1 Agentforce in Action: Customer Success Stories (Salesforce) Interested party archive pending
- S2 Wiley sees 213% return on investment with Salesforce Interested party archive pending
- S3 Dreamforce 24 - Wiley turns the page on productivity gains with Agentforce (diginomica) Established press archive pending
An error, newer info, a source?
This page lives on its accuracy. If a figure has moved, if the deployment has changed, or if you have a higher-quality source, tell us. Every sourced correction is verified before publication.