By 2030, 80% of humans will engage with smart robots daily, according to Gartner’s study. This shows how important Agentforce will be, as it gives business users the opportunity to create their own AI agents. However, to understand this kind of tool, it is useful to explore its bases, in this case, Salesforce Einstein AI.
But what exactly are the differences between Agentforce and Einstein AI? What sets AI agents apart from AI assistants for business? In today’s article, we’ll examine the particularities of Agentforce and highlight the top four improvements from its predecessor.
However, if you want to know more, meet the Inclusion Cloud team at the Agentforce World Tour in Dallas. There, we will explore the Agentforce ecosystem, helping you both build your first AI agents and plan how to create the integrated digital business ecosystem they need to work properly. Register today and meet us this December 10th!
AI Assistants vs AI Agents
Let’s be clear from the beginning: we’re talking about two separate AI systems. In short terms, while both use AI, their purposes and levels of independence differ. But, to save you some time, we condense their differences in the following table:
| AI Assistants | AI Agents | |
| Purpose | Assist users by responding to queries or tasks. | Perform tasks and make decisions autonomously. |
| Interactivity | Requires user interaction to provide output (e.g. prompts). | Operates independently, with minimal user input. |
| Focus | User-guided and support-focused. | Goal-driven and action-oriented. |
| Environment | Works in predefined, controlled settings. | Handles complex, dynamic scenarios. |
| Examples | Agentforce AI agents | Einstein AI Copilot |
What Are the Differences Between Agentforce and Einstein AI?
Now that we know what sets AI assistants and AI agents apart, we can advance over the differences between Salesforce Einstein AI and Agentforce. While they have many differences, we can summarize them as follows:
- Autonomy degree
- Context comprehension capabilities
- LLMs vs Agentic AI
- Customization
In the next sections, we will explore what each one of them consists of. However, bear in mind that, no matter the type, all AI tools rely on data to perform their tasks. This implies a whole tech framework that supports them, from cloud storage capacity to an integrated digital ecosystem that secures a seamless dataflow.
But don’t worry. At Inclusion Cloud we can help you create the right working ecosystem for your AI tools. Book a meeting and let’s discuss the integration solutions for your business’s digital transformation!
Autonomy degree
Agentforce provides AI agents with a high autonomy degree, which can perform independent actions, automate workflows, and make decisions across multiple systems. To put this in simple terms, Agentforce agents act almost without human input according to diverse enterprise needs.
Einstein AI, in contrast, functions more as an assistant or copilot. So, while it can offer predictive insights and suggestions, it requires user input to execute actions. In other words, it is primarily user-guided, offering recommendations, predictions, and insights that require explicit human approval or action to be executed.
Context comprehension capabilities
Agentforce employs the Atlas Reasoning Engine and Salesforce Data Cloud to deeply understand and act on both structured and unstructured data. It can extract relevant information from PDFs, call transcripts, or customer photos to provide actionable responses. This enables it to perform complex, context-aware tasks, such as addressing nuanced customer queries.
In contrast, Einstein AI primarily analyzes structured CRM data, providing insights like sales predictions or customer behavior patterns. This makes it useful for data-driven decision-making, but it lacks the depth to process unstructured data with the same proficiency. In other words, it can analyze data and make suggestions, but it cannot perform tasks or anticipate possible outcomes like autonomous agents.
LLMs and Agentic AI
Agentforce combines LLMs with agentic AI capabilities to move beyond interaction-based AI. This means that its agents don’t just answer queries—they autonomously execute tasks, such as optimizing workflows or orchestrating multi-platform actions, without relying on user direction.
Einstein AI, on the other hand, although it also uses LLMs for natural language understanding and generation, lacks the independent decision-making and action-oriented design of Agentforce. In a few words, these AI assistants cannot take the interaction beyond pre-programmed responses.
Customization
Agentforce offers extensive customization options through its Agent Builder, allowing business users to design agents with unique skills or integrate pre-built actions from a partner network. This flexibility enables companies to tailor autonomous workflows for specific industries or use cases, like logistics optimization or employee services.
On the other hand, Einstein AI is configurable for CRM-related scenarios (e.g., sales forecasting or service case resolution), but it doesn’t support the creation of entirely new agent capabilities. In short terms, while customizable, Einstein AI assistants cannot scale their capabilities as easily as Agentforce autonomous agents do.
Einstein Trust Layer: Bridging the Future and the Past
While Agentforce autonomous agents and Einstein AI assistants are very different, they have some things they have in common. But the most significative p convergence point comes from one of the majors’ ethical concerns regarding the use of AI agents: the privacy and security risks.
It’s through Einstein’s Trust Layer that Agentforce can secure sensitive information. In short terms, this is what enables Agentforce to use any LLM safely by ensuring that no Salesforce data is viewed or retained by 3rd-party model providers. Basically, it acts as a filter that controls data access, ensuring that AI agents can access only the information necessary for their tasks, minimizing data exposure.
Salesforce Einstein AI vs Agentforce: Which Should You Choose?
Now that you know the difference between Einstein AI assistants and Agentforce AI agents, you can choose the AI solution that best adapts to your business needs. However, bear in mind that these are not incompatible tools. On the contrary, in many ways, they complement and enhance each other, as we see with the example of Einstein Trust Layer on Agentforce.
However, no matter the case, all AI tools need an integrated digital ecosystem. This is what grants the necessary dataflow that ensures their access to updated and consistent information. Let’s meet and plan the integration process you need to adopt AI-powered solutions into your workflows!
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