By 2028, 33% of enterprise software apps will utilize agentic AI. The transition from Predictive to Generative AI has accelerated, allowing businesses to move beyond simple forecasting to defining optimal actions. Despite ethical concerns, the value of training AI for growth is clear. Teaching AI to understand human language enhances its ability to respond and perform useful tasks.
With Salesforce introducing AI Agents through Agentforce, a new revolution is underway. Agentforce AI Agents are both assistive and autonomous, equipped with well-processed knowledge and human-level expertise. These agents can recommend actions, reason effectively, and handle multiple queries without human intervention at every step. However, while they offer greater autonomy than other AI systems, building AI agents requires careful preparation and strategic planning.
Agentforce Agent Builder
Agent Builder is a low-code tool in Salesforce for customizing AI agents across various business functions. Users can create tasks for agents by defining topics with natural-language instructions and setting guardrails. It features testing options, seamless human handoff, and built-in templates for customer service, sales, or e-commerce. This allows businesses to easily automate processes and customize agents for any industry by using existing Salesforce tools like Flows, Apex, and APIs
Building AI agents involves multiple techniques, which can be broadly categorized into six key areas:
Data Collection:
Acquiring large and diverse datasets to train AI models effectively.Model Training:
Leveraging supervised, unsupervised, and reinforcement learning methods to develop AI capabilities.Natural Language Processing (NLP):
Enabling AI to interpret, understand, and communicate using human language.Reinforcement Learning:
Enhancing the agent’s ability to refine its actions through feedback and rewards.Decision-Making Algorithms:
Implementing computational strategies that analyze data and determine optimal actions.Action Generation:
Designing mechanisms that allow AI agents to execute decisions in real-world scenarios.
Agent Builder streamlines the process, enabling business users to create AI agents without the need for extensive coding skills.
Step-by-Step Guide to Building an AI Agent with Agentforce
Step 1: Define Your AI Agent’s Purpose
- Automating customer service responses
- Managing internal workflows and approvals
- Assisting sales teams with lead qualification
Step 2: Set Up Your Agentforce Environment
- Sign in to Agentforce and navigate to the agent creation module
- Select the pre-built templates or opt for a custom AI agent
Step 3: Use Agentforce Agent Builder
- Open the Agentforce Agent Builder for an intuitive development experience
- Choose from various pre-configured AI components to speed up the setup
- Utilize drag-and-drop tools to design workflows effortlessly
Step 4: Configure AI Capabilities
- Choose the AI model that aligns with your agent’s purpose (e.g., NLP for chatbots, predictive analytics for forecasting)
- Train the model using historical data or integrate it with external data sources
Step 5: Define Workflows and Actions
- Use the drag-and-drop workflow builder to design the agent’s decision-making logic
- Set up triggers, responses, and escalation rules to guide interactions
Step 6: Integrate with Enterprise Systems
- Connect your AI agent to Salesforce, SAP, or third-party APIs to streamline data exchange
- Ensure secure authentication and compliance with data policies
Step 7: Test and Optimize
- Run simulations to validate the agent’s responses
- Gather feedback and refine its behavior using continuous learning capabilities
Step 8: Deploy and Monitor Performance
- Deploy your AI agent in production and monitor KPIs such as response accuracy, resolution time, and user satisfaction
- Use Agentforce’s analytics dashboard to track performance and make improvements
Components that Build and Customize AI Agents
Metadata
Salesforce metadata establishes universal rules for data access across applications and agents, ensuring:
Permissions:
Controls access to datasets.Sharing Models:
Defines data-sharing rules.Validation Rules:
Enforces data integrity.Workflow Automation:
Enhances efficiency.
Metadata enhances AI accuracy by providing context, enabling LLMs to present CRM data in an actionable format.
Data Cloud
High-quality, unified data powers AI. Salesforce Data Cloud consolidates Salesforce and external data both structured and unstructured.
200+ Connectors:
Seamless integration with various sources.Custom Connectors:
Tailored data connections.
Once unified, Data Cloud activates data across AI agents, analytics, and applications, eliminating silos and delivering personalized experiences.
Models
Agentforce’s flexible model architecture allows easy integration of:
Hosted Foundation Models:
Ready-to-use AI innovations.Fine-tuned Models:
Custom AI models.User-defined Models:
Built with proprietary data.
Tooling
Agentforce provides low-code tools for AI development:
Prompt Builder:
Creates reusable, data-driven prompt templates.Agent Builder:
A visual tool for configuring and testing AI agents.
With these core components in place, let’s start building your first AI Agent with Agentforce!
Einstein Trust Layer
Ensures secure AI usage without compromising data through:
Secure Gateway:
Enforces security policies.Data Masking:
Anonymizes PII.Zero Retention Policy:
Prevents model providers from storing data.Post-processing:
Detects toxicity and maintains audit trails.
Actions
Actions empower AI agents to execute logic and integrate with external systems. Standard and custom actions can be created using:
- Custom Code
- APIs
- Flows
- Prompt Templates
Types of AI agents You can build using Agentforce
Agentforce AI agents help scale the workforce across various industries. Their user-friendly, low-code customization allows business users to leverage multiagent systems effectively. Here are their main roles and functions in different sectors:
Customer Support Agents
- Automate responses, handle FAQs, and escalate complex queries.Sales Assistants
- Qualify leads, recommend products, and assist in closing deals.HR & Recruitment Bots
- Screen candidates, schedule interviews, and manage onboarding.Finance & Accounting Agents
- Automate invoice processing, expense tracking, and fraud detection.IT Helpdesk Bots
- Resolve common technical issues, reset passwords, and manage IT tickets.Marketing Assistants
- Personalize customer engagement, run campaigns, and analyze trends.Supply Chain Optimizers
- Track shipments, manage inventory, and predict demand.Compliance & Security Agents
- Monitor policy adherence, detect anomalies, and flag risks.
Future-Proof Your AI Agent to Revamp the Customer Experience
We saw that building an AI agent with Agentforce is a straightforward process that enables businesses to utilize AI-driven automation. With the Agentforce Agent Builder, any user can create agents using natural language queries. To ensure long-term success, continuously update your AI agent with new datasets for improved accuracy, enhanced integrations with emerging technologies, and regular audits to maintain compliance and security. However, successful deployment also requires an integrated technological infrastructure for agents to access up-to-date data and perform effectively.
Rialtes helps businesses easily adopt AI agents using Agentforce. We provide customization and deployment to meet your needs, enhancing customer service and streamlining operations for a smooth transition into the AI-driven world.
