How AI Will Change the CRM Industry

10 min. read

ChatSpot, Zia, Freddy, Einstein… whether you use HubSpot, Zoho, Freshworks, or Salesforce, one of those names will sound familiar. In the space of just a few months, almost every major CRM has launched (or is about to) an AI chat copilot. That’s because those names — as exotic as they may appear — are a statement of fact on how AI will change the CRM industry and how users interact with them. CRMs are huge and painfully hard tools to use by themselves. But a well-configured AI tool can be a real game-changer, enabling users to search and perform complex tasks, all in a simple conversational interface. In this piece, we will define and review AI use cases for CRMs and compare the main existing AI copilots.

What kind of use cases can AI achieve in CRMs?

There are two reasons why defining the questions users want to ask is essential for developing a powerful AI tool:

  • The more value-loaded the use cases are, the more people will stick to using the AI chatbot. The pitfall in unfinished AI copilots is not providing sufficient responses or accomplishing enough tasks, making the copilot almost superfluous.
  • The second reason is technical: APIs are vital for retrieving and passing the data to the LLM, which will crunch them and build its answer. Use cases are the goals that will help identify the endpoints involved in achieving the operation, and build the prompts to provide the best outcomes.

The following use cases are based on what most CRM APIs can deliver.

Summarize interactions with a prospect


“I have a meeting with Sarah from Paperwrite in 5 minutes. Can you help me prepare it and summarize all the interactions we had with her?”

Why it brings value:

AI helps users summarize all the emails, messages, and notes of a lead, giving them an overall view. Before a meeting, for example, the AI copilot can remind users of the issue at hand and the latest interactions, saving them from scrolling through the lead’s page and having to interpret little pieces of information.

What’s more:

Linked with sentiment analysis, artificial intelligence can analyze the tone of the messages to enrich the lead scoring. It can also highlight pain points and possible dealbreakers to help users think ahead.

Create, manage, and resolve tickets


“Can you create a ticket from my last email with Anita Smalls, and assign it to James Dunn?”

Why it brings value:

The time spent creating, writing and assigning a ticket can be significantly reduced with an AI copilot capable of extracting and summarizing the right info from the right message. Support and product teams can produce tickets faster, freeing up valuable time to concentrate on customer care and product design.

What’s more:

Is there a recurring type of ticket? AI knows it, helping users better understand sticking points and addressing them faster.

Manage contacts, companies, and deals


“Create a list of closed deals over $1,000 with companies in the hospitality industry.”

Why it brings value:

Using only the CRM’s UI to keep a clear view of contacts, companies, or deals can be a hassle. The number of properties is often in the hundreds, and scrolling through them takes time. Asking for them in a conversational way, with a prompt that includes the properties makes the task seamless.

What’s more:

AI takes an even deeper look at the selection, helping users gain greater insights. From this prompt example, an AI copilot can additionally give the average number of employees for those companies or the time it took to close those deals.

Generate notes, emails, messages and more


“Can you draft me a note about my last meeting with Sarah from Paperwrite?”

Why it brings value:

The new abilities provided by LLMs mean that users can share the audio of a meeting to get a draft of the salient points. This helps users focus more on the meeting, without having to take notes. The AI copilot can also browse emails to adopt the user’s style and draft messages from prompts.

What’s more:

To help users craft the perfect message, the copilot can also provide advice based on past exchanges, the sentiment of the prospect’s responses, and more: ie. the tone could be reassuring, ease a paint point, or mention something that resonates with the prospect to urge them to respond quicker.

Generate reports and uncover insights


“How long did it take this month to close deals for companies in the hospitality industry? And how does this compare with last month?”

Why it brings value:

Retrieving data on a CRM can be challenging. Getting access to the right info can take time, with tools requiring some learning. Artificial intelligence can interpret the prompt and retrieve the data itself. In this case, it knows to look at deal creation date and closing date.

What’s more:

In addition to the “whats”, AI helps users understand the “whys”. With respect to the above example, users can ask the copilot to identify those deals that took the longest to close, thereby gaining insight into how to improve deal-closing delays.

Comparing the Top 3 CRMs’ AI Tools

How do the main CRM tools compare? We took a look at each of them to help you understand what use cases they can achieve.

Einstein by Salesforce CRM

Source - Salesforce

Salesforce Einstein’s first launch dates from 2018. They progressively added features like voice and visual recognition before rebranding it completely in 2023 as Einstein GPT. With 6 different modules — Sales GPT, Service GPT, Marketing GPT, Commerce GPT, Slack GPT, and Tableau GPT — Einstein now addresses every profile using Salesforce.


  • Einstein is available inside the app,
  • Highly customizable, users can create their own prompts,
  • Complete suite, with Slack and Tableau integrations.


  • There is still a steep learning curve to create prompts: users have to ask a third party if a use case isn’t available.

ChatSpot by HubSpot CRM

Blobr screenshot.

Hubspot’s ChatSpot uses the Hubspot account data to provide answers about contacts, companies, and deals. It also helps write blog posts and generate images. ChatSpot is not yet available in the Hubspot interface but on a side application.


  • A complete set of tools with greater scope than the CRM, including SEO, content, and image generators,
  • Lots of use cases and templates, helping the user navigate and understand the AI copilot possibilities and limits,
  • A quickly evolving tool, with product updates almost every week.


  • Not yet hosted on the main application,
  • Some use cases provide limited value or do not perform well.

Zia by Zoho CRM

Source - Zoho

Like Einstein, Zoho’s Zia was launched a while back, with features like sentiment analysis. It now includes a chatbot for the user’s customers and a sales assistant. Zia is implemented in various ways inside Zoho’s system. It can generate reports, ready-to-send answers, and predictive lead scoring. In 2023, Zia was linked to the OpenAI API to generate content and images.


  • Cross-platform AI system that takes the form of a chat or snippets in the interface,
  • Wide array of use cases, from sentiment analysis, report generation, and support chatbot to internal copilot,
  • Can connect to numerous types of databases and tools.


  • Some users have pointed to limited capacities of interpretation for complex queries, and limited customization.

Why every CRM should feature an AI Copilot?

We reviewed the main use cases and what the top 3 CRMs are doing AI-wise. The question is: how does AI make business sense for every CRM?

Increased stickiness for new users

Remember the first time you used a CRM, and how you felt. 9 times out of 10, a negative feeling comes to mind. This is not because CRM UIs are poorly designed, it’s just that putting so many features in one interface inevitably leads to a clogged result.

Making CRMs work through a conversational interface helps new users quickly grasp just how powerful your CRM is. They will not feel overwhelmed if they can accomplish powerful tasks seamlessly. And, fortunately, since using CRMs significantly increases revenues, once your users understand how it works, churn will almost become a non-issue.

AI helps your new users get there faster.

Eased daily usage

But AI doesn’t just help with onboarding. According to HubSpot, 32% of sales representatives spent more than an hour every day on data entry.

Thanks to artificial intelligence, such time-consuming activities can be significantly reduced. Some of the use cases above show how it helps produce notes, emails and messages quicker while simultaneously easing the process of updating a lead’s status.

A powerful marketing argument

Arguably, having to convince a prospect to switch to your CRM software is quite difficult. Of course, you can always simplify the process of data migration, but ultimately killer features will be what tip the balance.

A strong AI assistant is that killer feature. Imagine pitching your prospect with something like this:

“I know that delivering that particular task takes 32 minutes on CRM X. With our AI feature, you only have to prompt it, saving you 30 minutes.”

This also works for small companies looking for their first CRM, namely, for people who already have their hands full launching a business. You have a strong argument: AI will help them deliver basic use cases in a shorter timeframe, which in turn highlights a softer learning curve and net advantage over competitors.

Because not all CRMs have the strike force of Salesforce, HubSpot, Zoho, or Pipedrive, Blobr is here to help you design and launch your AI copilot. Harnessing the power of your API, we can help you offer your users AI-powered features in your CRM system, deliver all the mentioned use cases, and many more in line with your requirements.

Ready to give Blobr a try?

Connect your tools now, and start chatting with your data.

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