Dreamforce 2024 has made one thing very clear: autonomous AI agents are here to stay. In fact, according to a recent Gartner study, it’s estimated that 33% of enterprise software applications will include agentic AI in their operations by 2028. In this context, Agentforce is the future of customer success, supporting both clients and employees. But what exactly is it and how does it work? Today we will see more about this next step in the human-AI relationship.
However, we can already anticipate this: AI agents won’t replace human talents. On the contrary, human talent is more essential than ever as it is necessary to manage and plan its integration into existent workflows. At Inclusion Cloud we can help you. Let’s meet and see how we can seamlessly integrate Agentforce agents into your current business structure.
What Is Salesforce Agentforce?
Let’s see then what Salesforce’s Agentforce is. We are talking about a low-code platform that enables organizations to create and deploy AI-powered autonomous agents for supporting employees and customers. It allows teams, even without extensive coding experience, to build autonomous AI agents using templates and Salesforce tools like Flows and Apex.
These agents can handle tasks using CRM data, external sources, and metadata, all while complying with privacy and security standards. But, unlike traditional chatbots, Agentforce agents adapt in real-time to interactions, automating tasks and escalating complex issues to human agents when necessary. And the secret of its autonomy is the integration of Agentic AI.
What Is Agentic AI?
As we said before, Agentic AI is the secret behind the Agentforce autonomous agents. With this, we are referring to a type of Artificial Intelligence systems designed to operate autonomously, making decisions and taking actions without human intervention. In this case, business just sets predefined tasks, and the AI analyzes the context to operate autonomously to solve them.
These systems are capable of understanding, adapting, and executing actions based on real-time data, often using advanced models like large language models (LLMs). In this sense, Agentic AI can respond dynamically to changes, making it highly versatile across various applications.
Atlas reasoning engine: What sets Agentforce apart
While it is true that its autonomy is a major advancement, this is not the only thing that sets Agentforce agents apart. Another of its key features is Atlas: the agent reasoning engine designed to enhance user interaction through faster, more capable, and more multi-turn conversations.
Properly speaking, this is the brain of the Agentforce agents. This is why explaining how it works is not an easy task. However, to save you some time, we summarize its main characteristics in the following table:
| Characteristic | Description |
| Multi-turn chat | Supports interactive conversations, adapting to added context for improved service accuracy. |
| Topic classification | Classifies user inputs into topics using predefined descriptions, ensuring relevant responses. |
| Instructions & actions | Provides specific instructions and actions per topic for accurate user assistance. |
| Knowledge retrieval | Uses advanced retrieval augmentation generation (RAG) techniques to refine queries and retrieve the most relevant information. |
| Searchable public data | Accesses public data securely through the Einstein Trust Layer to expand the agent’s knowledge base. |
How Agentforce Autonomous AI Agents Work?
Now let’s see how autonomous AI agents work. While they have a great degree of autonomy, they act and adhere to human guardrails using natural language descriptions that outline the tasks and operational boundaries. In this sense, the operation process can be summarized as follows:
Step 1: Trigger command
First, Agentforce autonomous AI agents receive a trigger action in natural language, which can be a conversation with an employee or customer, a change in data, or automation.
Step 2: Context identification
Then, the agent uses LLMs and natural language descriptions to identify context and select the topic that best suits the job. This process includes identifying the scope, data required, and necessary conditions for the task selected.
Step 3: Chain of actions
Once the context is identified, and depending on the task, the autonomous AI agent will select and chain actions. This is one of the main characteristics of Agentforce agents, as they can decompose complex actions in a chain of simpler tasks autonomously. Then, they executed them via flows, apex classes, APIs, or direct prompts.
Step 4: Autonomous execution
Finally, Agentforce AI agents will plan and execute tasks strictly following the predefined guardrails set by you. Additionally, by using the Einstein Trust Layer, they have built-in mechanisms for harm and toxicity detection to prevent inappropriate or harmful activities.
As you see, customizing an autonomous AI agent on the Salesforce Agentforce platform is not difficult. However, like any digital transformation, this requires careful planning aligned with your business goals. In this sense, human talent has become more strategic than ever since it’s now in charge of managing and applying this technology to generate real value. At Inclusion Cloud we can help you. Let’s meet and see how you can integrate Agentforce to enhance your current workflows!
What are the key attributes of an Agentforce Agent?
Agentforce agents have some parameters to define the type of job to do, and the action or chain of actions required to do it. These key components are:
- Role: Defines the agent’s purpose and broader goals.
- Trusted Data: Information the agent needs to carry out its role (e.g. company knowledge articles, CRM data, etc.).
- Triggers: Events that prompt the agent to act.
- Actions: Predefined tasks an agent executes to do its job (based on the trigger).
- Guardrails: Operational boundaries and security guidelines.
- Channels: Platforms where agents can operate (websites, apps, CRM, etc.).
Agentforce Pre-Built Autonomous AI Agents
While Agentforce agents can be built from scratch according to your needs on the Salesforce platform, they have also some pre-build settings. These out-of-the-box agents are easy to customize and can be deployed without needing any coding. They are designed to perform specific tasks across different business functions like the following:
- Service Agent: Handles a wide range of customer service issues 24/7.
- Sales Development Representative (SDR): Engages with prospects, managing objections and scheduling meetings.
- Sales Coach: Provides role-play sessions for sales teams.
- Merchandiser: Assists with e-commerce tasks like product descriptions and promotions.
- Buyer Agent: Enhances the B2B buying experience.
- Personal Shopper: Offers personalized recommendations for e-commerce.
- Campaign Optimizer: Automates marketing campaign management.
What Is the Difference Between Agentforce and Einstein AI?
While they are both AI-powered solutions designed to optimize business processes within the Salesforce ecosystem, Agentforce and Einstein AI are very different. Each one has distinct functionalities and purposes but, to be more synthetic, we summarized their differences in the following table:
| Feature | Einstein | Agentforce |
| Purpose | Offers predictive insights and analytics. | Automates tasks using autonomous agents. |
| Capabilities | Provides predictions and automates simple tasks. | Handles complex workflows autonomously. |
| Task Complexity | Focuses on simpler tasks and recommendations. | Manages dynamic, multi-step tasks. |
| Role in Business | Assists with data-driven decisions. | Executes tasks independently. |
| Autonomy Level | Primarily offers suggestions and predictions to users. | Performs end-to-end autonomous actions without manual oversight. |
| AI Focus | Predictive analytics and data-driven insights. | Dynamic task execution and automated customer or business operations. |
AI Ethical Concerns: The Preoccupation Behind Agentforce Agents
As with other tech advancements, AI ethics are still a concern when it comes to autonomous AI agents. In fact, according to a recent MuleSoft study, 37% of IT leaders cite risk management, compliance, and/or legal implications as one of the most common challenges in digital transformation processes.
But, while there are several topics where the use of AI raises concerns, these can be summarized in two main issues. On the one hand, the classic question of whether Agentic AI will replace human labor. On the other, the problem of how to define the limits of action to ensure it doesn’t lead to negative outcomes for the organization or its clients, like poor customer experiences that damage trust and loyalty.
However, the key behind this is to understand that these types of technologies do not come to replace human talent. On the contrary, they make its role more strategic than ever, as it now focuses on management, planning, and integration. In summary, we must understand that, at the end of the day, these are like any other tools.
Integration: The First Step to Incorporate Autonomous AI Agents
As Bill Gates pointed out, “In many ways, software is still pretty dumb.” In this sense, Agentforce is a huge step forward since its deep context comprehension and higher autonomy degree give them a better understanding of what users need, whether they are customers or employees. But, like any other digital transformation process, integration is the key to incorporating this new technology.
That’s because this process is what ensures that business logic flows properly between systems. Without this, agents can’t perform tasks efficiently since they won’t be able to access critical data from your various systems, gradually becoming just another expensive and useless tool. But that’s exactly where we can help you. Have a meeting, find the best way to incorporate Agentforce into your existing workflows, and improve your business operational efficiency.
Meet Your Agentforce at the Salesforce World Tour Dallas 2024
This December 10, you will have the opportunity to see the launch of Agentforce directly from the main stage of Dreamforce at the Salesforce World Tour in Dallas. There, you will have a unique chance to see how AI agents will empower business by the hands of AI experts and the experience of other customers’ use cases.
But that’s not it. This is also the chance for you to build your first agent guided by Salesforce experts. Don’t waste this chance to engage with industry leaders and peers to share ideas and discover new solutions to augment your employees and improve productivity. Follow us on LinkedIn and start preparing for one of the last key events of the year!
