A practical guide to Salesforce generative AI

The push for generative AI is pretty much everywhere you look, and it makes sense. Businesses are trying to find smarter ways to work, and plugging AI directly into their daily tools feels like a no-brainer. Salesforce, being the giant it is in the CRM world, has definitely gone all-in, launching a whole suite of AI tools with names like Einstein GPT, Einstein 1, and Agentforce.

But what does all this actually mean for you? With so many different product names and tech layers, getting a straight answer can be surprisingly tough.

This guide is here to give you a clear, practical look at what Salesforce generative AI is, how it really works, and what it’s going to cost you. We’ll break down the main parts and, just as important, look at some simpler, more nimble alternatives for teams that need to get things done now, not next quarter.

What is Salesforce generative AI?

If you've been keeping up, you’ve probably heard of Einstein GPT. That was the first name Salesforce threw out there, but the branding has changed a bit since then. Now, their AI tools fall under the big Einstein 1 Platform, which is home to products like Einstein Copilot and Agentforce. It's less of a single tool and more of an ecosystem of connected AI services.

Under the hood, Salesforce's AI is a mix of its own private models and technology from partners like OpenAI. The big promise is that the AI is "grounded" in your company's specific customer data. It pulls this off by linking up with the Salesforce Data Cloud, a separate platform designed to bring all your scattered customer info into one place.

To handle the obvious security questions, Salesforce created the "Einstein Trust Layer." This basically acts as a security guard, masking sensitive data before it ever gets sent to a large language model (LLM). This ensures your private customer info isn't getting used to train public AI models. It’s a must-have feature for any serious enterprise AI.

A look at the Salesforce generative AI interface in action.

Key Salesforce generative AI components

Salesforce's generative AI isn't something you just switch on. It’s a collection of tools that need to work together, offering different features for your team and the admins who have to set it all up.

Einstein Copilot: The user-facing Salesforce generative AI assistant

Einstein Copilot is the part your team will actually see and use. It’s a conversational AI assistant that lives in the side panel of your Salesforce apps. Your team can ask it questions in plain English to get summaries of customer records, draft emails, or look up data. It can also create multi-step action plans, suggesting a checklist of tasks to guide a user through a process.

An example of the Einstein Copilot, the user-facing Salesforce generative AI assistant.

Copilot Studio: The admin's Salesforce generative AI customization toolkit

Behind the curtain, Copilot Studio is where your admins and developers get to decide how the AI actually behaves. It's a powerful toolkit, but this is also where things can start to get complicated. It's broken down into three main pieces:

• Prompt Builder: This lets admins create and save reusable prompt templates. So, instead of typing a prompt from scratch every time, a user can just click "draft a follow-up email" or "summarize this service case," and the AI has the right context to get started.

The Prompt Builder in Copilot Studio allows admins to customize the Salesforce generative AI.

• Skills Builder: This is where you can teach the AI to perform custom actions. For example, you could build a "skill" that lets the AI check an order status, update a customer's contact information, or assign a task to another team member.

• Model Builder: This part lets you pick and choose which AI models you want to use. You can stick with Salesforce's own models, connect to partners like OpenAI, or even use a "Bring Your Own Model" (BYOM) approach if your company has custom models hosted somewhere else.

While the studio gives you a ton of control, it comes with a steep learning curve and often requires some real technical know-how to get right. If you don't have developers on standby, a more intuitive, self-serve platform can deliver results much faster. For example, a tool like eesel AI offers a simple prompt editor and action builder that a support manager could use to customize their AI agent without having to write any code.

The Einstein Trust Layer: Securing your data with Salesforce generative AI

The Einstein Trust Layer is Salesforce’s answer to data security in the AI era. It works as a secure go-between for your Salesforce data and the LLM. When a user asks a question, the Trust Layer steps in, masks any private details (like names or credit card numbers), sends the clean query to the model, and then un-masks the response before showing it to the user.

This is a really important feature for keeping your data private and compliant. Of course, a secure setup is table stakes for any AI platform you'd trust with your data. eesel AI has a similar commitment, ensuring customer data is never used to train general models and is built on a foundation of SOC 2 Type II-certified infrastructure, giving you that same peace of mind without the complicated configuration.

The reality of setting up Salesforce generative AI

Here’s the thing: getting started with Salesforce generative AI isn't as easy as flipping a switch. Because it’s so tightly woven into the Salesforce ecosystem, the setup involves some pretty big technical hurdles that can quickly turn into a major project.

According to Salesforce's own documentation, here's a rough idea of what implementation involves:

1. Provision Data Cloud: This isn't just a small step; it's the foundation for everything else. You can't use any of the generative AI features until you have Data Cloud set up and running. Data Cloud is a beast of a data platform on its own, and configuring it correctly often requires specialized expertise.

2. Turn on Einstein: With Data Cloud in place, an admin can finally go into the settings and flip the main Einstein toggle. This starts a syncing process between Einstein and Data Cloud.

3. Configure the Einstein Trust Layer: Next, you have to actually set up the Trust Layer to match your company's privacy and security rules. This means making some key decisions about how data is masked and stored.

4. Enable Data Collection and Auditing: Lastly, you have to explicitly agree to store your AI activity logs and feedback in Data Cloud. This is important for auditing, but it also has billing implications, since you're on the hook for the costs of storing and processing all that data.

Salesforce generative AI pricing explained

Trying to figure out the cost of Salesforce generative AI can be a headache because it’s not a single, flat fee. The pricing model has several layers, which makes it tough to predict what you’ll actually spend each month, especially if your usage goes up and down.

Here’s a breakdown of how the costs stack up:

• Add-On Licensing: First, you have to buy specific add-on licenses for your users. For example, you might need Einstein 1 Service or Einstein for Sales, which often run about $50 per user, per month on top of what you already pay for Salesforce.

• Credit-Based Usage: Those add-on licenses don't give you a free-for-all. They come with a set number of "credits" that get used up every time the AI generates text or completes an action. If your team is busy, you can burn through those credits surprisingly fast.

• Enterprise Expansion Packs: Once your initial credits are gone, you have to buy more. Salesforce sells these as "Enterprise Expansion Packs," which is basically a pay-as-you-go system for any overages. This can lead to some nasty surprises on your bill, especially during busy seasons.

This model makes it really difficult to forecast your budget. A sudden spike in support tickets could cause your AI bill to jump without warning. That’s a stark contrast to platforms that offer clear, predictable pricing.

This video explains the fundamentals of Generative AI within the Salesforce ecosystem.

eesel AI's pricing is designed to be simple and predictable. Plans are based on a flat monthly fee for a certain number of AI interactions, with no hidden fees or extra charges per resolution. You know exactly what you’re paying each month, so you can scale without worrying about surprise bills.

Is there a simpler, more flexible alternative to Salesforce generative AI?

Salesforce offers a powerful, deeply integrated AI platform for companies that live and breathe its ecosystem. But all that power comes with a price: complexity, vendor lock-in, and unpredictable costs. For a lot of teams, especially in customer support, a more agile and straightforward solution just makes more sense.

This is where a tool like eesel AI comes in. It's built to plug into the tools you already use, giving you powerful AI features without making you overhaul your entire tech stack.

Go live in minutes with a self-serve setup

You can forget about long sales cycles and mandatory demos. With eesel AI, you can sign up and get going all on your own. It has one-click integrations for popular help desks like Zendesk, Freshdesk, and Intercom, plus knowledge sources like Confluence and Google Docs. You can have a working AI agent up and running in minutes.

eesel AI offers one-click integrations with various help desks and knowledge bases as a simpler alternative to a complex Salesforce generative AI setup.

Test with confidence using risk-free simulation

One of the scariest parts of launching an AI is not knowing how it will actually perform. eesel AI solves this with a simulation mode that lets you test your AI setup on thousands of your past tickets. This gives you a solid forecast of automation rates, answer quality, and how much money you could save before you ever turn the AI on for your customers. It’s a huge help for building confidence and making sure your launch is a success.

Unify your knowledge without a massive data project

While Salesforce AI depends on its Data Cloud (a huge project in itself), eesel AI connects to your knowledge wherever it is. It can securely learn from your past tickets, help center articles, and internal wikis right away. This means it can start giving accurate, context-aware answers from day one, without you needing to undertake a massive data engineering effort.

Final thoughts on Salesforce generative AI

So, what's the final word? Salesforce generative AI is an impressive set of tools for businesses that are deeply invested in the Salesforce world. The integration with your CRM data is top-notch, but it comes with some serious trade-offs. The reliance on Data Cloud, the complicated setup, and the confusing pricing can be big roadblocks for teams that need to move fast and keep budgets predictable.

For anyone looking for speed, simplicity, and transparency, modern platforms like eesel AI offer a compelling alternative. By focusing on a self-serve setup, predictable pricing, and easy integrations with the tools you already use, you can start automating support and helping your team almost immediately.

Ready to try an AI support agent that works with your existing tools? Sign up for eesel AI and see how you can get started in minutes, not months.