Agentforce Service Agent from Salesforce is an exciting new product available to enhance today’s service organizations. Explore how it works and what strategic benefits are possible for those who embrace AI customer service agent technology.
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AI customer service agent technology is a rapidly expanding market full of possibilities that can elevate how service leaders of today and tomorrow meet their goals. The market for designing agentic solutions is expected to increase from $5.1 billion in 2024 to $47.1 billion by the year 2030.¹ So, how can service organizations that want to harness Agentforce Service Agent’s capabilities get started?
Breaking down the basics
First, it’s important to explore the two types of AI agents in the Salesforce ecosystem.
These agents are part of Salesforce’s proactive, autonomous software system designed to execute specialized tasks. Using Large Language Models (LLMs), the AI customer service agents analyze interactions or triggers and make decisions on next steps autonomously. Unlike traditional chatbots that rely on rigid, declarative dialogs, these autonomous agents use Generative AI (GenAI) to operate 24/7 across self-service portals and messaging channels to handle tasks, make decisions, and provide natural responses aligned with each organization’s brand.
Agentforce is an AI-powered platform designed to revolutionize how businesses engage with their customers and support their employees. By integrating Salesforce's Data Cloud, Agentforce provides a foundation that lets teams see a 360-degree view of the customer, enabling AI agents to operate with enhanced context and precision. This means more personalized, efficient, and proactive customer service solutions for organizations.
Because Agentforce Service Agent is grounded in trusted business data and knowledge bases, it can deliver relevant, context-aware information to meet specific business or customer service goals. Agentforce Service Agent automates common tasks and frees up service teams to focus on more strategic, high-value work and building customer relationships.
Activating Agentforce Service Agent: A case study
When Deloitte Digital was selected by Salesforce as global integrators of Agentforce for its 2024 launch, we knew it was a game-changing solution to bring to our clients. Our first client happened to be Salesforce itself.
The goal of this technology implementation project was to transform the employee service experience. By becoming customer zero for Agentforce, Salesforce could strategically see all sides of the product and gather the benefits and learnings from its deployment to then bring to the rest of the market. As the earliest adopters of their own technology, Salesforce could act as the first line of defense for proactive issue resolution.
Deloitte deployed Agentforce Service Agent on the Employee Success Service Cloud platform for Salesforce’s Human Resources (HR) case management. By assessing the product value from the HR function of Agentforce, we worked with Salesforce leadership to then transpose those learnings into a customer-facing technology evaluation and iteratively improve the solution with our technology and product teams.
This brought tangible benefits to Salesforce’s employee service experience, including:
By implementing and improving Agentforce Service Agent’s capabilities internally, Salesforce is now able to bring these AI agents to the rest of the market.
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Next steps
For service leaders who are ready to embrace Agentforce, a world of possibilities and growth awaits. An example of the next generation of GenAI architecture, Agentforce is backed by Salesforce Data Cloud. This enables agentic design that spans across the entire Salesforce ecosystem, redefining problem-solving on the Salesforce platform from the ground up.
Potential use cases for Agentforce Service Agent:
Create cases based on customer feedback received through multiple channels, classify cases based on geography, priority, and customer sentiment, and assign them to skilled and available agents.
Use existing customer interactions, data, and preferences to craft messages and content that have a higher chance of resonating with a customer (e.g., sentiment, tenure, location, etc.).
Automatically create tasks based on the cases that require the most attention. Recommend next steps that need to be taken to resolve the task/case based on predictive analytics (e.g., completing milestones, sending emails to customers for follow-up pending information, addressing escalated cases, etc.).
Use Salesforce Data Cloud to generate suggested scripts, solutions, and recommendations based on current customer issues, past interactions, and trends.
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An introduction to our Agentforce AI agent accelerators
Deloitte Digital unveils Agentforce accelerators for trustworthy LLM use cases
Learn how we optimize service experiences to drive customer loyalty
Source:
1. MarketsandMarkets, “AI Agents Market Report," Sept, 2024.
