A practical guide to Salesforce Generative AI in 2025

Generative AI is everywhere, and Salesforce is obviously a huge part of that conversation. They’ve baked a powerful suite of AI tools right into the CRM you use daily, promising to make every employee more productive and every customer experience a little smoother. But what does that actually mean for you and your team?

This guide will give you a clear, practical look at what Salesforce Generative AI is, how its main parts work, and what it looks like in the real world for sales and support teams. We’ll cut through the hype to explore both the good and the not-so-good, because while the tech is impressive, getting it set up involves some serious things to think about, like complexity, cost, and flexibility.

What is Salesforce Generative AI?

So, what exactly is Salesforce Generative AI? Think of it as Salesforce’s collection of AI tools, all living under one roof on what they call the Einstein 1 Platform. The main idea is to help you create new content on the fly, like personalized emails, quick meeting summaries, or helpful knowledge articles, and knock out boring, repetitive tasks without ever leaving Salesforce.

It works by mixing Salesforce’s own private AI models with big-name large language models (LLMs) from partners like OpenAI. The really clever part is how it uses your own data. Salesforce calls this "grounding." Instead of spitting out generic answers, the AI taps into your company’s customer data from the Salesforce Data Cloud to give responses that are actually relevant. It learns from your past sales calls, support tickets, and customer histories to create content that sounds like your brand and speaks to what your customers need.

The whole system is designed to feel like a natural part of Salesforce, blending AI help into the daily grind for your sales, service, and marketing folks.

The core components of Salesforce Generative AI

The platform really stands on three legs: an AI assistant that your team interacts with, a customization engine for your admins to control everything, and a security layer to keep your data safe.

Salesforce Generative AI’s Einstein Copilot: The user-facing assistant

Einstein Copilot is the AI assistant your team will actually talk to. It pops up as a handy side panel in Salesforce, ready for you to ask it questions in plain English. You can think of it as a smart helper that already knows its way around all your Salesforce data.

Here’s what it typically does:

• Answers questions about your records (e.g., "What was the last thing that happened with the Acme account?").

• Summarizes long email chains, sales opportunities, or support cases so you can get up to speed in seconds.

• Creates step-by-step action plans to guide users on what to do next, like suggesting follow-up tasks for a brand-new lead.

Salesforce Generative AI’s Copilot Studio: The customization engine

While your team sees Einstein Copilot, your admins and developers will be working in Copilot Studio. This is the behind-the-scenes toolkit where you get to decide how the AI works, setting up rules and custom commands so it fits your company’s needs.

It’s split into three main tools:

• Prompt Builder: This is where you can create and save prompt templates. Instead of everyone writing a new prompt from scratch, you can have pre-built templates for common tasks, like "Draft a follow-up email after a product demo."

• Skills Builder: This tool lets you teach the AI new tricks. A "skill" could be something as simple as updating a ticket status or as complex as triggering a custom workflow you’ve already built.

• Model Builder: This gives you the option to plug in different AI models from other providers or even use your own custom-trained models, giving you a bit more choice over the AI engine.

While this level of customization is great, it’s all built to work inside the Salesforce bubble. That can be a real problem for teams whose knowledge is scattered across different apps. If your most important documents are in Confluence, Google Docs, or Notion, they might as well not exist to Salesforce’s AI. It’s a big reason tools like eesel AI exist, they’re built to connect all your knowledge sources from the get-go, without needing a developer to build tricky API connections.

Salesforce Generative AI’s Einstein Trust Layer: The security promise

Let’s talk about the big one: data security. The Einstein Trust Layer is Salesforce’s solution to keep your sensitive customer info safe. It acts as a secure wall between your Salesforce data and the large language models the AI relies on, making sure the LLMs don’t hang onto your private data.

It does this in a few ways:

• Dynamic Grounding: The AI gets the context it needs from your data to give a relevant answer, but without sending a full copy of your records over to the LLM.

• Data Masking: It automatically finds and hides personally identifiable information (PII) like names and phone numbers before a prompt is sent off.

• Toxicity Detection: It scans both the prompts you write and the answers you get back to check for anything inappropriate.

• Audit Trails: It keeps a log of all AI interactions, so you have a complete record if you ever need it for compliance checks.

Use cases: How teams actually use Salesforce Generative AI

Salesforce has shaped its AI features to solve real-world problems for different departments. The most common uses you’ll see are for sales and customer service teams.

Salesforce Generative AI for sales teams

For sales reps, it’s all about cutting down on admin work and getting smarter insights to close deals faster. Some key features are:

• Sales Emails: It can automatically draft personalized emails for any point in the sales process, from the first cold outreach to a follow-up after a demo, using the customer’s history to make it relevant.

• Call Summaries: After a sales call, the AI can create a quick summary with the main points, customer feelings, and next steps, saving reps from having to type up notes.

• Account Summaries: Before a big meeting, a rep can ask for an AI-generated brief on an account that pulls in recent activities, open deals, and any outstanding support issues.

This video demonstrates how Salesforce’s generative AI features can be used to draft and personalize sales emails directly within the CRM.

Salesforce Generative AI for customer service teams

On the customer service side, the goal is to help agents answer questions faster, better, and with less hassle.

• Service Replies: During a live chat or email conversation, the AI can suggest responses based on the customer’s question and past issues, which the agent can quickly review and send.

• Work Summaries: When a support case is closed, the AI automatically writes up a summary of the problem, what was done to fix it, and the final outcome. This is great for record-keeping and handoffs.

• Knowledge Articles: The AI can look at resolved support tickets and draft new articles for your knowledge base, helping you turn one-off solutions into helpful content for everyone.

See how the Einstein Knowledge Creation feature uses AI to analyze support cases and draft helpful knowledge base articles.

These features sound great, but there’s a huge string attached: they assume your entire world lives in Salesforce Service Cloud. For the thousands of teams happily using fantastic helpdesks like Zendesk, Freshdesk, or Intercom, this is a non-starter. You’d have to migrate everything, which is a massive headache. This is where an integration-first tool like eesel AI comes in handy. It’s designed to plug into the tools you already use and love, getting you up and running in minutes, not months.

The reality check for Salesforce Generative AI: Costs and hidden hurdles

While the tech sounds cool, adopting it is a lot more involved than just enabling a new feature. It’s important to get a real sense of the challenges and hidden costs that come with it.

The challenge of Salesforce Generative AI implementation and complexity

Getting Salesforce Generative AI up and running isn’t a simple plug-and-play situation. It’s a full-blown IT project that requires a lot of planning and technical know-how. You first have to get the Salesforce Data Cloud set up correctly so the AI can see the right information. Then, you have to configure the Einstein Trust Layer to meet your security standards. Finally, you have to spend time in Copilot Studio building out the prompts, skills, and models that actually match how your team works.

This complexity can be a major roadblock for teams that need to move quickly. It’s the exact kind of problem eesel AI was built to avoid. It’s designed to be radically self-serve, you can connect your helpdesk and knowledge bases with a few clicks and have a working AI agent in a matter of minutes, without needing a developer or a six-month onboarding project.

Salesforce Generative AI pricing: More than just a license fee

Let’s talk money, because the pricing for Salesforce AI can get a little… complicated. Einstein is usually sold as an add-on, often for around $50 per user per month. The catch, however, is the credit system. Your license comes with a set number of "Einstein GPT credits," and every time the AI does something for you, it uses up some of those credits.

If you burn through your monthly credits, you have to buy expensive "Enterprise Expansion Packs" to keep things running. This creates costs that can be hard to predict, especially during busy months. A sudden spike in support tickets could leave you with a surprisingly big bill.

This model almost penalizes you for growing. In contrast, eesel AI’s pricing is straightforward and predictable. You pay a flat fee based on a set number of AI interactions, with no extra fees per resolution. Your bill stays the same each month, so you can scale up your support without worrying about costs spiraling out of control.

Feature	Salesforce Generative AI	eesel AI
Model	Per-user license + usage credits	Flat monthly/annual fee
Usage Fees	Yes (via "Expansion Packs")	No (no per-resolution fees)
Predictability	Low (costs can vary)	High (predictable monthly cost)
Trial	Requires sales engagement	Free trial, self-serve setup

Rolling out Salesforce Generative AI with confidence

With a system as complex as Salesforce AI, how do you test it safely before letting it talk to your customers? One bad AI response can hurt trust, and a poorly configured automation can create a mess for your support team. Salesforce’s approach often feels like you have to build it, deploy it, and cross your fingers.

This is where a feature like eesel AI’s powerful simulation mode makes a huge difference. You can test your AI agent on thousands of your actual past support tickets in a totally safe environment. This gives you a clear picture of its potential resolution rate, shows you exactly how it would have answered real customer questions, and helps you spot any gaps in your knowledge base. It lets you fine-tune everything with zero risk, so you can go live feeling confident it’s ready.

Is Salesforce Generative AI right for you?

So, what’s the verdict?

Salesforce Generative AI is a seriously powerful set of tools for companies that are already all-in on the Salesforce ecosystem. If your business lives and breathes Salesforce and you have the technical team and budget to handle a big project, its direct access to your CRM data and strong security layer are hard to beat.

However, that power comes with real trade-offs in complexity, unpredictable costs, and being locked into one vendor. For teams who need a solution that’s fast, flexible, and works with the tools they already have, it’s probably not the right fit. The long setup times, confusing pricing, and inability to see knowledge outside of Salesforce are tough pills to swallow for a modern, agile business.

If you’re looking for a generative AI solution you can launch in minutes, connects to all your knowledge wherever it lives, and has pricing that actually makes sense, it might be time to look at a more nimble alternative.

Try eesel AI for free and see how quickly you can bring smart automation to the tools you already use.