There’s a ton of chatter about AI in the CRM world, and Salesforce is usually right in the middle of it. It’s easy to get swept up in the latest features, but what are businesses actually trying to do with this tech? Let’s cut through the noise and explore the most common and useful Salesforce AI use cases that companies are looking at right now.
We’ll break down what Salesforce’s built-in tools can do, but more importantly, how you can get these results in the real world. We’ll focus on what matters most: flexibility, speed, and not needing a team of developers to get started. While Salesforce AI is a solid option for teams living entirely within its ecosystem, you’ll see there are more agile, self-serve alternatives for businesses that want to move fast without ripping and replacing their favorite tools.
What is Salesforce AI?
At its core, Salesforce AI is a collection of artificial intelligence tools built around products you might have heard of, like Einstein, Agentforce, and Einstein Copilot. The main selling point is its deep, native connection to the Salesforce CRM and Data Cloud. Simply put, it’s designed to crunch the customer data you already have in Salesforce to make its features work.
The platform generally offers two flavors of AI:
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Predictive AI: This is for forecasting. Think of it as a crystal ball that predicts which leads are most likely to become customers or which sales deals have the best shot at closing this quarter.
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Generative AI: This is all about creating new stuff. It can help draft emails, summarize long customer support cases, or even generate articles for your knowledge base.
These tools are at their best when they stay inside the Salesforce playground. That’s great if your entire company runs on Salesforce, but it can be a real roadblock for companies that use a mix of best-in-class tools for things like documentation, internal chat, and customer support.
Top Salesforce AI use cases for customer service
Making customer service better is one of the biggest reasons businesses look to AI. The promise is tempting: resolve issues faster, lighten the load on your support agents, and keep customers happy. Let’s look at how Salesforce approaches this, and where a more flexible option might be a better fit.
Automated ticket responses and case summarization
How Salesforce handles it: Service Cloud Einstein can look at new support cases and use historical data from inside Salesforce to automatically write up a reply or give an agent the short version of a long, complicated ticket thread. The goal is to save time and keep your messaging consistent.
Where it can get tricky: This whole setup lives and dies by the data inside Salesforce. If your actual source of truth is a Confluence space, your troubleshooting guides are in Google Docs, or the most current answers are buried in Slack threads, Einstein can’t see any of it. Getting it to connect to those outside sources usually means a complicated and expensive integration project that is far from a DIY weekend task.
A more flexible alternative: This is where a tool like eesel AI comes in. It’s built from the ground up to connect all your knowledge sources, pretty much instantly. You can hook it up to help desks like Zendesk or Intercom to learn from past tickets, but it also integrates with one click to Confluence, Google Docs, Notion, and over 100 other apps. This gives the AI a complete picture of your company’s knowledge, which means it can give much more accurate and genuinely helpful answers to your customers.
This infographic illustrates how eesel AI connects with various knowledge sources, a flexible approach to one of the key Salesforce AI use cases.:Generating and improving knowledge base articles
How Salesforce handles it: Einstein can be set up to suggest relevant knowledge articles to agents while they’re working on a case. It can also help create new articles by looking at the content of successfully resolved cases, helping you plug gaps in your help center.
Where it can get tricky: The process can feel a bit stiff. The AI’s suggestions are only as good as the perfectly organized data in your Salesforce Knowledge base. It often misses the context from all the informal places where solutions are actually worked out and shared.
A more flexible alternative: eesel AI has a more down-to-earth approach. It automatically spots when a ticket has been resolved successfully and turns that solution into a draft article for you to review. This helps you build out your knowledge base based on what your customers really need help with. Because eesel connects to all your tools, it can see when a brilliant solution was posted in a Slack channel or a Google Doc and suggest you promote it to your official help center. It’s a smart way to build a knowledge base that actually solves problems.
This workflow demonstrates the eesel AI support automation process, a practical example of Salesforce AI use cases for customer service.:Common Salesforce AI use cases for sales and marketing
AI isn’t just for support teams; it’s also a great way to speed up sales cycles and make marketing feel more personal. It helps teams spend more time on valuable work by automating the tedious tasks that eat up the day.
Generating personalized sales emails
How Salesforce handles it: Sales Cloud Einstein digs into your CRM data, like a contact’s job title, company info, and past conversations, to draft personalized outreach emails or follow-ups. It’s meant to give sales reps a running start on their communications.
Where it can get tricky: Let’s be honest, the tone of these AI-generated emails can feel a little… robotic. Unless you have someone technical who can dive deep into Salesforce’s Prompt Builder to customize them, they often miss the mark. The AI is mostly pulling from structured fields in the CRM, so it lacks the human touch you’d find in a real conversation.
A more flexible alternative: The AI Copilot from eesel AI learns directly from your team’s actual sent emails. By looking at thousands of real conversations, it picks up on your team’s unique voice, tone, and what messaging has worked in the past. The drafts it generates sound like they came from your best sales reps, not a generic template. You get full control over the AI’s personality through a simple prompt editor, no coding degree required.
The eesel AI Copilot drafting a personalized email, showcasing an alternative to standard Salesforce AI use cases for sales teams.:AI-powered insights and lead scoring
How Salesforce handles it: Einstein is famous for its lead and opportunity scoring. It sifts through your historical data to predict which deals have the best chance of closing, helping sales teams figure out where to focus their energy.
Where it can get tricky: This is a classic predictive AI feature, not a generative one. It’s good at telling you what to focus on, but it doesn’t help you with the action of actually responding to that lead. On top of that, its accuracy is completely dependent on having a huge amount of clean, organized data in Salesforce, which is a constant struggle for many businesses.
A more flexible alternative: While eesel AI is focused on automating actions, its AI Triage product can automatically tag, route, and categorize incoming leads based on what they’re asking. For instance, it can immediately tell the difference between a lead asking for a demo and one asking for a price list and tag them for you. This helps clean up your inbox and lets sales reps jump on the hottest leads faster, turning a simple insight into a quick action.
Comparing setup, control, and pricing
When you’re choosing an AI tool, the feature list is only half the battle. The day-to-day reality of setup, customization, and cost can be the difference between a successful project and a frustrating one. Here’s a no-fluff breakdown for decision-makers.
The setup experience: Months vs. minutes
Salesforce AI: Getting Einstein or Agentforce up and running is rarely a walk in the park. It’s often a months-long project that involves certified consultants, developer hours, and a lot of upfront meetings. It’s not something you can just try out over a weekend; it’s a major IT undertaking.
eesel AI: On the other hand, eesel AI was designed to be completely self-serve. You can sign up, connect your helpdesk and knowledge bases with a few clicks, and have a working AI agent ready to test in minutes, not months. You don’t even need to talk to a salesperson to get started, so you can see if it’s right for you right away.
This workflow shows the fast, self-serve implementation process for eesel AI, a contrast to more complex Salesforce AI use cases.:Customization and control
Salesforce AI: Salesforce gives you a ton of control with tools like Prompt Builder, Skills Builder, and Model Builder. But all that power comes with a steep learning curve and usually requires a specialist to manage it all. Making a simple tweak to the AI’s tone can quickly turn into a complicated task.
eesel AI: With eesel AI, you get total control through a simple, visual workflow engine. You can use a straightforward prompt editor to shape the AI’s personality, create custom actions that connect to your other systems, and use simple rules to automate only the types of tickets you want. It’s built for the people actually running the teams, not just for developers.
The eesel AI interface for setting custom rules and guardrails, demonstrating user-friendly control over AI behavior for various Salesforce AI use cases.:Pricing: Per-seat lock-in vs. predictable value
Salesforce AI: Sales and Service Cloud Einstein are usually included in pricey Salesforce editions or sold as a per-user, per-month add-on (often around $50 per user). This per-seat model means your costs go up every time you hire someone, whether they use the AI a little or a lot.
eesel AI: eesel AI has transparent, interaction-based pricing. You pay for the number of AI actions and replies, not the number of people on your team. This model is much more predictable and doesn’t penalize you for growing. Monthly plans are available without long-term contracts, so you can adjust as your needs change.
| Plan | Monthly Price (Billed Annually) | AI Interactions/mo | Key Features |
|---|---|---|---|
| Team | $239 | Up to 1,000 | Train on docs, Copilot for agents, Slack integration. |
| Business | $639 | Up to 3,000 | Everything in Team + train on past tickets, custom AI Actions, simulation. |
| Custom | Contact Sales | Unlimited | Advanced integrations, multi-agent orchestration, custom security. |
Choose the right AI for your Salesforce AI use cases
So, what’s the bottom line? Salesforce AI has some powerful, deeply connected features that make a lot of sense for businesses that are all-in on its ecosystem. The Salesforce AI use cases we’ve talked about are built to get the most out of the data you already have in the CRM.
However, for the many companies out there that need to move fast, stay flexible, and use the tools they already love, a platform-agnostic solution is often a much better fit. An alternative like eesel AI shines because it plugs into your existing tools, like Zendesk, Slack, and Confluence, without making you go through a painful migration. You can get it running in minutes, control it through a simple interface, and pay for it with a model that actually makes sense.
The goal isn’t just to "do AI", it’s to solve real problems for your business without creating new ones.
Ready to implement these Salesforce AI use cases today?
Don’t wait months for a complicated project to get off the ground. With eesel AI, you can connect your knowledge sources and automate your first support query in less than 5 minutes.
Frequently asked questions
The guide categorizes Salesforce AI into Predictive AI, which forecasts outcomes like lead conversion, and Generative AI, which creates content such as emails and case summaries. Both types are designed to leverage existing Salesforce CRM data.
For customer service, Salesforce AI can automate responses to support tickets, summarize lengthy case threads for agents, and assist in generating or suggesting relevant articles for a knowledge base. The aim is to accelerate issue resolution and ensure consistent messaging.
Sales and marketing teams can utilize Salesforce AI for generating personalized sales outreach emails and follow-ups. Additionally, it offers AI-powered insights for lead and opportunity scoring to help prioritize sales efforts.
Implementing Salesforce AI use cases typically involves a significant, often months-long project that requires certified consultants, developer hours, and extensive planning. It is generally not designed for quick, self-serve deployment.
Yes, Salesforce AI use cases are most effective when utilizing data stored within the Salesforce CRM and Data Cloud. Integrating with external knowledge sources or applications usually requires complex and often costly custom integration projects.
Salesforce AI features, such as Einstein, are typically included in higher-tier Salesforce editions or offered as a per-user, per-month add-on. This per-seat model means that costs often increase with every new team member, regardless of their AI usage.
