Every major platform is capitalizing on AI, offering tools to expand their original feature sets with new technology. This means more chat interfaces, AI-powered features, and smarter automation. But with so many marketing promises, it’s challenging to understand which apps are the best for your business.
Salesforce, known for its CRM platform, has begun marketing its new Agentforce feature set. You can use it to build agentic AI chatbots that interact with your business data, run actions, and implement response safety features. This requires a setup process where you prepare your data connections and configure pre-made actions that the bot can take.
We’ll compare this approach with Personal AI: a platform where you can multiply your workforce with AI Personas, giving you all the tools to train them with your business data. Let’s dive in.
Beyond this high-level comparison, here are the differences between Salesforce Agentforce and Personal AI:
Salesforce Agentforce’s Agent Builder flow, where you set up topics and actions for your agents.
Salesforce Agentforce is designed to augment task automation with AI. With agentic AI chatbots, it can provide better customer service by running actions on internal systems to track orders or support ticket status. This approach takes the pressure off team members, letting them focus on other tasks, improving overall productivity.
Agentforce does this by letting you use your company data to generate answers, and configuring pre-determined actions (called flows in the platform). These actions are triggered when the chatbot detects the matching intent, making changes in your internal systems.
In Personal AI, you can mention your AI Personas in chat channels, using their outputs as context for other users and Personas on the channel.
Personal AI also improves productivity but does so in a different way. When you create your account, you start creating your AI workforce: a team of AI Personas you can train with your business data. You can:
Once you finish training your Personas, you can ask them questions about the data, getting highly accurate answers. Your team can ask questions to your AI workforce, and you can also expose them to external users to answer questions. You can use advanced prompts to surface, correlate, or generate new information.
Where Agentforce seeks to automate low-value work, Personal AI is instead looking to augment higher-value work. It acts as a powerful decision-making assistance tool, offering the human brain what it can’t do natively: handle a massive amount of data with flawless memory, on-demand topic connections, and complex reasoning in a short amount of time.
If your work relies on smart decisions more than efficiency gains, Personal AI is a better choice to keep you at the top of the game—not because you’re cutting costs, but because you’re adding a lot more value to your customers.
Personal AI’s features include reply suggestions, automatic responses, and AI Persona mentions to blend human and machine intelligence.
Due to its multiple Persona framework and the ability to train each one with different data and skills, Personal AI is transforming messaging and collaboration.
First, it can be used as a copilot of key people in your team. It can gather everything they know to assist them in the daily workflows they need to do, improving access to information. Other team members can chat with AI to get direct answers to simple questions, reducing the number of emails or Slack messages necessary to keep everyone aligned.
But what happens if someone really needs to get in touch? Personal AI reduces the time spent searching for information to accurately reply to your teams’ questions. It does so with two conversation modes:
Beyond messaging, Personal AI offers AI-powered chat channels where you can ask for help from any AI Persona during a conversation. For example, if you’re working on a new project and need input from marketing and sales teams, you can mention those sales Personas the same way you’d mention a team member. Type @, write the Persona’s name, and a prompt that will be posted to the channel.
The best part about this feature is that, when you mention a separate Persona, it will use the entire conversation as context. For example, when your AI sales Persona posts customer objections to the channel, ask your AI CMO to generate a strategy, it will take the previous responses into account.
When compared with Salesforce Agentforce’s task-oriented product, Personal AI augments messaging between people, allowing for a more free and less time-consuming way of communicating. This allows for connections that are more based on brainstorming and creating together, not just on remembering and sharing information.
Salesforce Agentforce relies on topic configuration, defining what can and can’t be discussed.
When building a new agent in Agentforce, you start by setting the topics it can discuss. You can write instructions to define what the bot can and can’t do. While useful for external-facing use cases, such as customer support, this adds two obstacles when building your AI workforce:
Agentforce isn’t augmenting the messaging and collaboration use case: instead, it’s building upon the user experience of traditional rule-based chatbot builders such as ManyChat. While an improvement over the old conversation trees, it’s still very on-rails.
As for messaging integrations with communication apps, Agentforce can push messages to Slack or via SMS—with some initial configuration required. These work as notifications or prompts for simple data input, not a natural conversation. This enables human-in-the-loop architectures, helping you control the quality of your agents as they work, but it still feels like interacting with a computer system, not with an intelligent machine.
Training your AI in Personal AI is easy using the app’s interface. No coding required.
Today, there are two ways to customize the knowledge of AI models:
With Personal AI, you don’t have to be a machine learning expert to train your AI model. The process is completely zero-code: upload all your business files, be they text, images, or spreadsheets. All data will be stored in the MODEL-3 memory layer typically in less than a minute.
You can activate memory sync by connecting Google Drive, Microsoft OneDrive, Outlook, and Gmail. This will integrate these data sources with your AI, so any new information is added to the memory as soon as it’s created.
As you train your model, you can separate memories by AI Persona, acting as an equivalent to folders in a computer. Still, all your company data will be held in a single digital brain, ready to solve problems.
Then, when you ask a question, your AI runs a complex interpretation process that detects your intent, discovers matching memories, and strings them over a timeline. The responses are context- and timeline-aware. You can see how much your AI knows about the topic by inspecting the personal score of the response: a higher score means that more memories were used.
When compared with fine-tuning and RAG, Personal AI is simpler to configure, use, and maintain. And, since it relies on a proprietary model with an embedded memory layer, it consistently offers answers with high accuracy.
Earlier, we highlighted that Agentforce can use your company data to answer questions and run actions. Doing so requires setting up Data Cloud, the Salesforce data infrastructure platform. Due to its capabilities and complexity, this is a task reserved for developers: non-technical users won’t be able to set up this service by themselves.
If you have an IT team, they should be able to get past this initial hurdle. They’ll be able to organize your data into a collection of knowledge bases that you can expose to Agentforce. At the end of this setup process, Agentforce will classify your data and set up loops to store and retrieve it. This is now ready to plug into one of your agent projects within the platform, set up the conversation topics, and start chatting.
You’ll notice that the responses will draw on your business data. This happens thanks to the RAG framework working behind the scenes: using the vector representations of your files with an LLM to produce the most accurate answer possible.
While this is the industry standard for implementing this framework, it’s not as accurate as Personal AI’s MODEL-3. It relies on systems that are external to the language model, requiring ongoing optimization of the data structure and prompt engineering parts of the system. Moreover, it lacks timeline awareness: it can’t answer questions on, for example, the changes in a project, or how a topic has evolved.
Personal AI is designed to grow with your needs, both at a product and pricing level. You’ll be training an AI brain for your business: the more data you upload, the more accurate and valuable it can be. And, the longer you use it, the more you can leverage its timeline awareness to explore trends, think strategically, and make better decisions. Like a savings account for your data, it compounds over time.
You can get all the features of Personal AI in a single subscription package. The pricing is adapted to where you are in your company’s journey.
Agentforce is not a single-subscription stand-alone tool. It’s an add-on to the Salesforce platform, requiring an active subscription of CRM and Foundations to become active—only free for Enterprise clients.
So, while each conversation is priced at $2, activating Agentforce requires existing contracts, which can make it substantially more expensive and complicated to set up.
Salesforce Agentforce and Personal AI represent two distinct approaches to integrating AI into workflows. Agentforce, deeply embedded in the Salesforce ecosystem, focuses on task-driven automation. It leverages retrieval-augmented generation (RAG) to power context-aware AI answers but requires multiple subscriptions and a complex setup. While it excels at automating actions within Salesforce, it lacks a seamless, intuitive training process and flexible AI memory capabilities.
In contrast, Personal AI offers an AI-native solution that prioritizes knowledge retention, decision-making, and collaboration. With a memory layer built into the model, it continuously learns from uploaded files and syncs with external storage, making it a powerful tool for high-value work. Instead of focusing solely on automation, Personal AI enhances human intelligence by enabling AI Personas that support strategic thinking, project evolution, and real-time messaging augmentation.
Salesforce Agentforce is best suited for organizations already invested in the Salesforce ecosystem looking for structured automation. Personal AI is ideal for those seeking an AI workforce with perfect memory, flexible training, and enhanced collaboration—without the limitations of platform lock-in or complex infrastructure.
If your goal is to automate basic tasks, Agentforce may be the right choice. If you need an AI that learns, remembers, and supports intelligent decision-making, Personal AI is the best option.
