How Early-Stage Companies Are Rethinking CRMs in the Age of AI

AI-first CRMs are poised to disrupt traditional workflows and revolutionize user expectations. First up: no more data entry.

At Stage 2 Capital, we spend every day thinking about how go-to-market can be done better. With 50+ portfolio companies in our network, we’re constantly scanning for ways AI can accelerate execution. Over the past year, we’ve noticed a major shift: what started as hesitation (“Let’s wait and see”) has turned into urgency (“I know I should be using AI, I just don’t know where to start”).

One of the biggest questions we hear from early-stage founders is:

“Do I really need to start with an enterprise CRM, like Salesforce or HubSpot, or is there a new path forward?”

For years, these systems have been the default answer. But they come with baggage: expensive licenses, heavy setup, and the eternal struggle of getting salespeople to input data. The result? Leaders spend more time chasing updates than actually learning from the CRM.

This is where Day AI comes in.

The Case for a Native AI CRM

Unlike the well-known enterprise CRMs, Day AI doesn’t require teams to do a lot of data entry. Instead, it listens, captures, and surfaces insights from the interactions sales teams are already having — email, meetings, and calls. Instead of requiring structure before delivering value, Day AI builds structure around a team’s day-to-day work.

When we first invested in Day AI, we saw the potential for something fundamentally different: a CRM that works for humans, not the other way around. And now that early customers are using it in production, the results are compelling.

A Founder-Led Sales Team’s Breakthrough

Finch is a company that handles pre-litigation for law firms, using AI-powered software. One of its promises is to handle administrative work so law firms can serve more clients. So it makes sense that Finch would also avoid administrative work wherever possible.

Bennett Northcutt is on the strategy and operations team at Finch. “I came in tasked with building out our go-to-market operations,” he said.

The team already had a CRM but it wasn’t doing what they needed and it was hard to manage.

“We were going to a lot of conferences so we wanted to be able to easily manage lists of attendees, including who was already in the CRM, who we’ve reached out to, the opportunities that exist,” Bennett said. “And it was just kind of convoluted. We would look at it and scratch our heads wondering, ‘am I looking at a list of companies? Is this a list of objects?’ The CRM had a certain way of organizing everything and we were supposed to figure out how to make it work for us. But it just never felt quite right.”

“I assumed we would go with either HubSpot or Salesforce. Right? Everybody uses one of those.”

Bennett’s CEO encouraged him to give Day AI a try before investing the dollars and the time that an enterprise CRM implementation requires.

Within hours, their pipeline number appeared automatically — no spreadsheets, no weeks of setup, no painful migration.

“It was amazing that it just sort of appeared,” Bennett said. “We hooked up Day AI, and all of a sudden we had pipeline visibility without anyone having to manually update a thing.”

Ease of Use That Meets the Team Where They Are

Another big difference from enterprise CRMs was that Bennett and his team found there was virtually no learning curve. “It was obvious how to use it because there wasn't any action we needed to take,” he said. “We just connected it to our systems, and then everything appeared, and it was readily available. And we can always query using the chat functionality, which is very nice.”

Like many young companies, Finch’s sales data was spread across various email inboxes, including the CEO’s.

“It would have been a huge administrative burden to get data from all of the conversations that had been happening out of people’s inboxes and into a CRM,” said Bennett. “It was amazing we didn’t have to do that.”

Today, Finch is using Day AI primarily to manage pipeline. For example, Bennett can submit a query: “Is there anything outstanding for any opportunity in discovery that has fallen through the cracks?” Day AI then recommends actions like, “Make sure to follow up with Charles.”

Day AI has saved Finch’s sales team countless hours of admin work, but this wasn’t just about convenience; it was a strategic choice. Bennett explained that Finch as a company believes in taking asymmetric risks if those risks could yield a unique competitive advantage. Bennett and his team felt that the time and cost they would save by not using a legacy CRM would give them a leg up over their competitors.

By adopting Day AI, Bennett’s team gained:

• Instant pipeline visibility without manual input.

• Proactive follow-up reminders to prevent deals from slipping.

• Automatic meeting context via call recordings and notes.

• Daily sales briefings that kept the team focused on action, not admin.

And Day AI did all of this straight “out of the box.”

Why This Matters for Early-Stage Companies

At the earliest stages, sales is often founder-led. Time spent updating fields in Salesforce or HubSpot is time not spent selling. Day AI flips that equation:

• For founders: It keeps focus on customer conversations while building the pipeline automatically.

• For sales leaders: It removes the administrative tax that often drags down adoption of traditional CRMs.

• For companies: It represents an “asymmetric risk” — the chance to gain competitive edge by using a tool that competitors stuck on legacy systems don’t have.

Or as Bennett put it: “Day AI would be my number one recommendation. Let it handle your pipeline — you focus on selling.”

The Bigger Picture

AI isn’t just automating tasks; it’s reshaping workflows. CRM may be one of the best examples of this shift; but that doesn't mean it's right for every company.

For example, with a traditional enterprise CRM, the user begins the day reviewing opportunities and thinking about how to prioritize the workday. With an AI-native CRM, all of the context gathering and prioritization is handled by the agent. It creates a brief and delivers recommendations with pre-written email drafts to the prospect.

This is a fundamental change in workflow. It will be interesting to see how quickly user expectations adapt to this shift — and to what extent enterprise CRMs come to support them.

Is an AI-First CRM Right for You?

Questions to Ask

Team Size and Complexity

• Do you have a large team supporting multiple verticals that requires the depth of a traditional CRM, including sophisticated pipelines and custom reporting?

• Do you have a smaller or more junior team that would benefit most from the prioritization, speed, and automation of an AI-native CRM?

Business Requirements

• Do you and your company’s finance team need enterprise-level infrastructure and integrations today?

• Would you rather have an agile tool with fewer but quickly iterating features? (Many AI-native CRMs may not have all of the integrations out of the box, but they can grow with your company.)

• What kind of reporting will you need for board meetings, fundraising, or forecasting?

Existing Workflows and Processes

• Will your team actually use an enterprise CRM daily and see the value in it, or will it become shelfware?

• Is your customer data already housed within a CRM or is it distributed across email, product, and various spreadsheets?

• Do you have the time and resources to train your team to fully utilize new tools?