What is Salesforce AI: A practical guide for 2025

You’ve probably seen the hype around Salesforce AI. With flashy names like Einstein and Agentforce, it’s pitched as the next big thing for businesses. But if you’re like most people, you’re probably wondering if it’s genuinely useful or just another layer of clever marketing.

Spend a little time on any community forum, and you’ll find a mixed bag of opinions. Some folks see the potential, but many others find it too complex, way too expensive, and not quite ready for day-to-day use. This article is here to give you a straight answer. We’ll walk through what Salesforce AI actually is, what its main parts do, where it misses the mark, and how it compares to more flexible, modern solutions.

What is Salesforce AI?

First off, Salesforce AI isn’t one single product. It’s a collection of artificial intelligence tools built directly into the Salesforce platform. You can think of it as an AI layer that reads and uses the customer data you already have stored in Salesforce.

It all started with predictive AI, the first version of Einstein, which was all about forecasting sales and scoring leads. Lately, the focus has shifted to generative AI with Agentforce (which you might have known as Einstein Copilot). This newer tech is designed to create content and run conversational assistants.

The whole point is to leverage your CRM data to make AI interactions more useful for your sales, service, and marketing teams. The two main names to remember are Einstein, the AI engine doing the heavy lifting, and Agentforce, the conversational assistant your team actually interacts with.

The core components of Salesforce AI

To really wrap your head around Salesforce AI, it helps to understand the different pieces working together. It’s more than just a chatbot; it’s a whole system with a powerful engine and a customization toolkit chugging along in the background.

Einstein: The predictive and generative engine

Einstein is the foundational tech that makes everything else run. It’s the brain of the operation and has two main jobs.

• Predictive AI: These are the classic features that have been around for a bit. Think of tools like Einstein Lead & Opportunity Scoring, which looks at your past deals to guess which new ones are most likely to close. Or Einstein Forecasting, which helps you get a better handle on future sales numbers.

• Generative AI: This is the newer, headline-grabbing side of Einstein. It’s the engine behind features that create new content, like drafting sales emails, summarizing support cases, or generating knowledge base articles. It’s the magic that makes Agentforce tick.

Agentforce (formerly Einstein Copilot): The conversational assistant

Agentforce is the part of Salesforce AI your employees will actually use every day. It’s the user-facing chatbot or side-panel assistant that lives right inside the Salesforce interface.

Its main purpose is to be a helpful sidekick that can answer questions, summarize long conversations, draft emails, and suggest next steps using plain English. You can ask it things like, "Give me the short version of the last call with this customer" or "Draft a follow-up email about their renewal." Of course, how well it works depends entirely on how clean, complete, and current your Salesforce data is.

Einstein 1 platform & Copilot Studio: The customization layer

This is the toolkit that lets your admins and developers tweak how the AI behaves. It’s a powerful layer, but it’s definitely not for the average user and can get complicated fast. It’s broken down into three main parts:

• Prompt Builder: This is where you can create and save prompts for the AI that you plan to use over and over. For example, you could set up a template for "Summarize this support case in a friendly, empathetic tone for a follow-up email."

• Skills Builder: This tool lets you teach the AI how to do specific, repeatable tasks, like "check a customer’s warranty status" or "find a knowledge article about billing."

• Model Builder: This part lets you connect to different large language models (LLMs), including your own custom-built models or those from other providers.

While having this much control sounds great, it points to a major hurdle. Getting real value from Salesforce AI requires serious technical know-how and a ton of time to get everything configured. For teams that don’t have dedicated developers on hand, that’s often a dealbreaker.

Key use cases for Salesforce AI

So, how does all this tech actually help your teams get stuff done? Here’s a look at some of the most common ways it’s used.

For service teams

For customer service folks, the main goal is to solve customer issues faster and cut down on manual work for agents. Here are a few common examples:

• Generating Service Replies: Drafting quick answers to common customer questions.

• Creating Work Summaries: Automatically summarizing long, complicated support tickets so the next agent can get up to speed without reading a novel.

• Drafting Knowledge Articles: Turning the solutions from solved tickets into new articles for your help center.

• Einstein Case Classification & Routing: Looking at incoming tickets and sending them to the right agent or department automatically.

These are all genuinely helpful features, but they come with a huge string attached: they only work well with data inside the Salesforce ecosystem. If your company’s knowledge is spread out in other places like Confluence or Google Docs, the AI can’t see it without a difficult and expensive integration project.

For sales teams

For sales reps, the focus is on getting rid of admin tasks so they can spend more time actually talking to customers. Some key uses are:

• Generating Sales Emails: Creating personalized outreach and follow-up emails using data from the CRM.

• Creating Call Summaries: Automatically transcribing and summarizing sales calls.

• Updating the CRM: Pulling key details from conversations and updating the right fields in Salesforce automatically.

Challenges and limitations of Salesforce AI

Even with a compelling vision, the reality of putting Salesforce AI to work comes with some pretty big challenges you should know about before you jump in.

The reality of implementation and adoption

A feeling you’ll quickly pick up online is that Salesforce AI can feel a bit "half-baked" or just too complicated for the average team. It is definitely not a solution you can just turn on and use.

To get any real value, you need to have exceptionally clean data that lives only within Salesforce. This "walled garden" approach is a massive drawback for most modern companies. Your team’s knowledge is likely scattered across internal wikis, shared drives, and other apps, and Salesforce AI is completely blind to all of it. Getting it to work means having a dedicated admin or developer spend weeks, maybe even months, tweaking everything in the Copilot Studio.

The hidden costs of pricing

Salesforce isn’t exactly upfront about what its AI costs. You won’t find a simple pricing page laying it all out. From what people have reported, the model is usually an add-on license (around $50 per user per month) that runs on a "credits" system.

The issue with credit-based systems is that your costs can become totally unpredictable. A busy month for your support team could leave you with a surprisingly high bill. This model makes budgeting a real headache and, in a way, punishes you for being successful and using the tool a lot.

Is there a more flexible alternative?

This all leads to a pretty important question: what if you want the benefits of AI without the high costs, complexity, and vendor lock-in that come with the Salesforce platform?

For teams that need a more nimble solution, it’s worth checking out other options. A tool like eesel AI was built for flexibility and ease of use. It works with the tools you already have (including Salesforce, but also Zendesk, Intercom, Slack, and more) instead of locking you into one ecosystem.

eesel AI: A simpler, more powerful approach

eesel AI was built to solve the very problems that make platforms like Salesforce AI so tough for many teams to use.

• Go live in minutes, not months: You can forget about long implementation projects. eesel AI is a truly self-serve platform. You can connect your helpdesk, point it to your knowledge sources, and start seeing results in minutes, all without having to talk to a salesperson or hire a developer.

• Unify all your knowledge: Unlike Salesforce AI, which is stuck in its own data silo, eesel AI securely connects to all of your knowledge sources right out of the box. Whether your answers are in Confluence, Google Docs, Notion, or past support tickets, eesel AI brings them all together to give complete and accurate answers.

• Test with confidence and pay predictably: eesel AI’s powerful simulation mode lets you test the AI on thousands of your past tickets before you ever show it to customers. This gives you an accurate preview of its performance and automation rate. And instead of a confusing credit system, eesel AI offers transparent, flat-rate pricing with no per-resolution fees, so your bill is always predictable.

Feature	Salesforce AI	eesel AI
Setup Time	Weeks to months; requires admin/developer	Minutes; fully self-serve
Knowledge Sources	Primarily Salesforce data; limited external access	Unified knowledge (Confluence, Google Docs, Zendesk, etc.)
Testing	Limited; no robust simulation environment	Powerful simulation mode on past tickets
Pricing Model	Complex, credit-based, unpredictable costs	Transparent, predictable plans; no per-resolution fees
Flexibility	Deeply tied to the Salesforce ecosystem	Works with your existing helpdesk and tools

Choosing the right AI for your team

So, what’s the bottom line? Salesforce AI is a powerful suite of tools that makes a lot of sense for businesses that are all-in on the Salesforce ecosystem and have the technical staff to manage a complex system.

However, its complexity, "walled garden" approach to data, and confusing pricing make it a tough sell for many others.

For teams that want a flexible, easy-to-use, and transparently priced AI that works across all their existing tools, a solution like eesel AI is the much more practical choice.

Get started with AI that works for you

Want to see what an AI that plays nice with your existing tools can do? You can connect your knowledge sources and simulate eesel AI on your real support conversations in just a few minutes. You’ll get to see your potential automation rate before you even commit.