Salesforce and AI: How Salesforce’s Einstein Transforms Sales

Salesforce is a comprehensive CRM solution that has long offered cutting-edge cloud technologies for customer relationship management, and in recent months, the platform has reached new heights with generative artificial intelligence and AI-powered features, made possible through Einstein.
To better understand how AI works in the Salesforce platform and how different business teams can take advantage of this technology, I did an in-depth study of Salesforce’s AI strategy and specific products and features. This guide covers these AI capabilities in detail.

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TABLE OF CONTENTS
ToggleFeatured Partners: Customer Relationship Management (CRM) SoftwareUnderstanding Salesforce AI’s CapabilitiesWhat Is Salesforce Einstein?7 Key Features of Salesforce Einstein7 Applications of Salesforce Einstein: Use CasesPros and Cons of Salesforce EinsteinHow to Get Started with Salesforce EinsteinFuture Trends and Innovations in Salesforce AIBottom Line: Salesforce AI Evolves with Generative AI Landscape

Understanding Salesforce AI’s Capabilities
Salesforce is a longstanding favorite in the customer relationship management (CRM) software world, providing users with one of the most comprehensive solutions for managing relationships across departments, verticals, and initiatives. With Salesforce, specific clouds are set up so your teams can manage marketing, sales, customer service, e-commerce, and more with purpose-built resources that focus on both customer experience and powerful data and analytics to support internal decision-making.
Salesforce’s generative artificial intelligence has quickly increased the platform’s native automation, workflow management, data analytics, and assistive capabilities when managing customers throughout their lifecycles. Nowhere is this more evident than with Salesforce Copilot, which assists internal users with their outreach and analysis taskwork while also creating a smoother user experience externally.
What Is Salesforce Einstein?
Salesforce Einstein is a set of purpose-built, native AI technology and features for the Salesforce CRM. It is integrated into individual Salesforce Cloud apps, including Sales Cloud, Marketing Cloud, Service Cloud, and Commerce Cloud, as well as more generally through assistive tools like Einstein Copilot.
Salesforce Einstein is multitenant and includes several automated machine learning features, which helps it to better unify an organization’s data with development, AI, and general AI CRM capabilities. It is designed to make intelligent decisions based on your organization’s data and requires no additional installation or knowledge to get started, so long as you select a compatible subscription plan.
Source: Salesforce.
For more information about generative AI providers, read our in-depth guide: Generative AI Companies: Top 20 Leaders
7 Key Features of Salesforce Einstein
Einstein 1 Platform
The Einstein 1 Platform is the application development platform and unified data and AI solution that powers most artificial intelligence features currently operating in Salesforce. Einstein, Salesforce’s CRM apps, and the Data Cloud are all part of Salesforce’s metadata framework, which is able to tap into data and application resources in tools like Tableau, Slack, Heroku, Google Workspace, Microsoft 365, and Mulesoft. With the Einstein 1 Platform, users can build custom apps and generative AI models and optimize data security and privacy.
Trust Layer
The Trust Layer is a collection of tools, guardrails, best practices, and other commitments from Salesforce to protect privacy and security for data being used in Salesforce AI products. Some of the features of the trust layer include:

Dynamic grounding
Data masking
Zero data retention
Toxicity detection
Secure data retrieval

Copilot & Conversational AI
Einstein Copilot is a CRM assistant that can help users across teams compose useful sales and marketing content, search for information about a recent deal or prospect, and much more. With the conversational AI components of Copilot, Salesforce users can also create intelligent external AI chatbots that can handle more complicated customer experience tasks and questions.
Generative AI
Based on the data you provide and the algorithmic framework of Einstein, users can use Copilot and other tools to generate new content with simple prompting. This content may be marketing or ad copy, email and campaign content, or even tailored analytics results that focus on a specific piece of client lifecycle research. Users can also incorporate their own models into Einstein for custom generative AI taskwork and initiatives.
Predictive AI & AI-Powered Analytics
In addition to creative, generative AI, Salesforce comes with advanced predictive AI features and AI-powered analytics that can guide users in strategic decision-making and planning.
For example, in the Sales AI suite of Sales Cloud, users can receive real-time selling data and information about the likelihood of a deal closing, as well as helpful hints for what this prospect may need to seal the deal. AI for Salesforce analytics is incorporated throughout Salesforce products and clouds, including Sales Cloud, Marketing Cloud, Tableau, and Lightning.
Prompt & Model Builders
These builder solutions from Salesforce AI help admins and other organizational leaders craft the prompting and modeling infrastructure that will work best for their teams. In Prompt Builder, reusable generative AI prompts are built, prompts are grounded and contextualized in your data and preferred AI models, and prompt templates can be designed for easier access and process standardization.
In Einstein 1 Studio, users can take advantage of a low-code AI builder to build their own copilots and custom actions. They can also build or smoothly introduce external, preexisting AI models into Salesforce through the Model Builder feature.
Coding Support
Though still in its early stages and only available to select groups of users, CodeGen is a new AI tool that makes programming and developer tasks operate conversationally and with low-code prompting. Users can develop new apps, improve existing apps, and do several other programming tasks in plain language. This is one of many emerging AI solutions that are working to democratize software and product development.

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7 Applications of Salesforce Einstein: Use Cases
Marketing Cloud
Marketing AI is a collection of AI features designed for Marketing Cloud. Users can take advantage of Data Cloud, using natural language prompting and generative AI to more intelligently segment audience data. They can also optimize marketing campaigns, using predictive AI to test various possible campaign options simultaneously.
At the same time, marketers can use generative AI to generate relevant marketing copy and then use Einstein-powered AI analytics to analyze how all of these different components are performing. Other unique AI features in Marketing AI include AI scoring for prospects and leads, key account identification, event triggers and automated offers, and automated planning and pacing for marketing initiatives.
Sales Cloud
Sales AI, found in Sales Cloud, is one of the largest AI solution sets available to Salesforce users. Copilot is included to assist with tasks like email drafting, call summaries, personalized close plans, and prospect and account research. Additional features include AI-driven deal insights, predictive sales and deal forecasting, conversation mining and call insights, and relationship graphs and insights.
Soon, there will also be a revenue-cloud-specific solution to help with contract management. Dedicated Trailhead courses are available to help users get started with these solutions.
Sales AI helps users develop personalized close plans for potential clients based on opportunity scoring and other data. Source: Salesforce.
Service Cloud
Customer Service AI provides AI-powered assistance and tools throughout the Salesforce Service Cloud. A unique feature of this toolset is Einstein Copilot for Service, which is designed to assist with questions and other messaging from both external customers and internal users.
This tool can source information from your knowledge base, make intelligent responses based on internal data, and route more complicated tasks — including approval workflows — as necessary. AI eases typical holes and challenges in customer experience, giving service reps conversation summaries and quick replies, next-best actions and case classifications for quicker responses. It also offers several different resources to build bots that can handle customer service interactions in multiple languages and contexts.
Commerce Cloud
Commerce AI is a tailored suite of AI solutions that helps Commerce Cloud users improve their product lifecycles, sales, and general e-commerce workflows. Similar to AI solutions in Service Cloud, Commerce AI addresses challenges for both customers and employees.
Commerce AI features include an AI shopping assistant, AI-powered product recommendations, commerce insights, and generative AI support for product page and product description creation.
Data Cloud
Data Cloud is an AI-supported data storage solution in Einstein 1 that works with data in different formats and from different sources — users can even BYOL (bring your own data lake) if they already have a big data storage solution that lives outside of Salesforce, which greatly simplifies typical CRM implementation tasks like data migration and integration.
Through its built-in vector database, users are provided with the resources to initiate AI-powered searches, automate prospecting and audience building tasks, and complete other smart tasks across all of Salesforce’s different cloud products. Data Cloud enables particularly granular data insights, offering users access to a visual dashboard, data streams, data lake objects, and identity resolutions and insights.
Einstein Copilot
Einstein Copilot, now in beta, is an AI copilot that works as a standalone Salesforce feature and also within several different Salesforce product clouds. This copilot can assist with questions that users may have about current leads or opportunities as well as with data sourcing, custom deal closing plans, customer service queries, custom messaging for marketing, and intelligent product recommendations based on customer segment data. In general, this tool can help different members of your team with Q&A about data on the platform, custom action and next-step suggestions, and more.
With Einstein Copilot, users can not only generate written content but can also get quick assistance with data analysis, including for product performance in the Commerce Cloud. Source: Salesforce.
Tableau Pulse
Tableau Pulse is a new AI feature set in Tableau, the Salesforce-owned data analytics platform, that helps users quickly source and digest analytical data about product, sales, marketing, and relationship management performance. With this data, users can more easily identify how certain metrics have changed over the past week while also looking at daily pulses to see how this data incrementally changes over time.
For users who are less experienced with analytics tools, plain-language prompting and results help to simplify the whole process; Tableau also offers Q&A enhancements and other support resources to help users ask the right questions about their data.
Tableau, which is part of Salesforce’s family of solutions, now includes AI-driven pulses that help users to easily identify project progress, pitfalls, and new opportunities. Source: Tableau from Salesforce.
Pros and Cons of Salesforce Einstein
If you’re trying to decide if Salesforce Einstein offers all of the AI and automation capabilities that you’re looking for in a CRM, consider how the following pros and cons stack up:

Pros
Cons

AI features across sales, marketing, and service use cases.
Not all Einstein features are optimized for mobile usage.

Enhanced analytics, automations, personalizations, and decision-making tools.
Some data limitations, especially if your own dataset is limited, erroneous, or biased.

No additional costs; just pay for the Salesforce apps you’re already using.
Some small business and low-tier subscription limitations.

How to Get Started with Salesforce Einstein
1. Subscribe to an AI-Enabled Salesforce Product or Plan
While most plans have some kind of basic AI running automations and other features in the background, the most advanced AI capabilities are typically available in higher-tier plans. The decision-makers in your organization should first determine the available budget and then wants versus needs; from there, you can select the subscription plan that balances these requirements with robust AI capabilities. It may also be wise to complete a demo with the Salesforce team so you can delineate your expectations and learn how to use the platform’s unique features more effectively.
In Sales Cloud, these two plans are the best options for users who want powerful AI support. It’s important to look at the features available in each Salesforce product’s pricing tiers before subscribing. Source: Salesforce.
2. Prepare and Optimize Your Data
While Salesforce is designed to work with the customer and lead data you put into the system without much fuss, there may be issues if your data contains inaccuracies, repetitions, missing information, or other issues. It’s a good idea to cleanse and QA your most important CRM data before you put it into Salesforce rather than after. This will also help you to get started with and scale AI operations more quickly.
3. Complete Relevant AI Trainings
Trailhead offers training and generative AI certification courses on a variety of Salesforce-specific and more general business technology topics. Interested users should sign up for their AI-specific course sets, which include information about how generative AI works and how AI should be used responsibly. Some other Trailhead courses specifically talk about how to use Salesforce AI features and tools most effectively.
Trailhead, an e-learning resource offered through Salesforce, offers dedicated coursework to help users gain the knowledge necessary to work with AI in their CRM. Source: Salesforce.
Future Trends and Innovations in Salesforce AI

New use cases for Einstein Copilot: Einstein was only generally released to the public in February 2024, but it already comes with many different use cases in the Marketing, Sales, Service, and Commerce Clouds. Salesforce has recently made announcements for more Copilot functionality in Tableau and platform analytics, as well as a greater emphasis on personal AI agents, so expect to see new Copilot use cases emerge in the coming months.
Increased developer resources: Einstein has recently provided more users with access to CodeGen for low-code, democratized programming. The company has also announced upcoming AI and app integration opportunities for MuleSoft, which will help to make app development a smoother and speedier process. As more and more users develop an interest in creating custom AI solutions and applications, Salesforce is likely to bring more low-code and no-code resources into its portfolio to serve this population.
More industry-specific features: Salesforce already offers some AI features that are specific to individual industries, but for the most part, its generative AI tools are divided based on more general clouds. Expect to see more purpose-built AI solutions for some of the company’s core industries that already have Salesforce bundles: automotive, communications, retail and consumer goods, energy and utilities, financial services, healthcare and life sciences, manufacturing, media, and the public sector.
More support for compliance, privacy, security, and ethical AI: AI tool users, as well as governments and other regulatory bodies, continue to demand more transparency and ethical AI from tech companies. Salesforce already has its Trust Layer and several other enterprise security and privacy features built into its systems, but more features are on the horizon. For example, an audit trail to simplify compliance is coming soon to the Einstein Trust Layer.
Greater emphasis on sustainability and net zero commitment: Many of the biggest companies around the globe, including Salesforce, have made net zero commitments to reduce emissions and pollution in the environment. Though few of these tools are actually in operation yet, several tech companies are using generative AI to support these sustainability efforts. Some of the programs and initiatives the organization is already working on include ESG disclosure authoring through Einstein, marginal abatement cost insights and visualizations, sustainability program visualizations, and improved emissions factors management.

Bottom Line: Salesforce AI Evolves with Generative AI Landscape
Even before the introduction of generative AI and advanced predictive AI, many aspects of Salesforce’s chatbots, analytics, and automations included some AI-powered characteristics. However, as the generative AI landscape continues to expand and mature, Salesforce is doing the work to keep up with these innovations, as is evidenced by its daily-to-weekly updates on new AI features in its products.
Whether you’re a brand new Salesforce user who’s looking for AI solutions that can help you get up and running or a Salesforce veteran who wants to simplify their current workflows in the platform, Salesforce continues to bolster its reputation for forward-thinking, AI-centric software that automates and streamlines AI customer relationship management and business operations.
For a full portrait of the AI vendors serving a wide array of business needs, read our in-depth guide: 150+ Top AI Companies 2024
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