Another year, and it’s clearer than ever that SaaS companies must embrace AI or risk being left behind. A year when many have moved beyond experimentation into true implementation, and with it, they’re seeing real results.

It’s a shift perhaps most prominent across the GTM function – impacting sales, marketing, and customer success org charts, tech stacks, and workflows. 

Across our events and media, we’ve heard directly from the founders and operators who are leading the way. We’ve heard how they’re testing, iterating, and innovating—and how they’re scaling faster as a result.

In this post I’ll take you through six practical AI go-to-market use cases and the real results they can drive for your business.

1. Tally – Outranking competitors in AI search

Shared by Nathan Latka at SaaStock USA, Tally is a great example of how smaller companies can beat giants by showing up in what Nathan calls “the new homepage of the internet”. That is, LLMs including ChatGPT, Claude, Gemini, Perplexity etc. 

Growing quickly, Tally has bootstrapped its way to $4M ARR, with just five people. A form builder, similar to Typeform and Jotform, Tally sees thousands of leads a month coming from ChatGPT. 

By using semantic keyword clusters that ChatGPT likes, such as ‘free form tool for construction workers in Kentucky,’ it outranked both Jotform, Typeform and even HubSpot. To do the same, you need to:

  • Focus on traditional SEO and get a domain rating above 50.
  • Create landing pages with keyword clusters your users search for.
  • Wait 60-90 days for the next LLM update (LLMs only index once, not in real-time).

2. Chili Piper – Using AI agents so reps can hit 160% of quotas

Back at SaaStock USA, Chili Piper Co-founder Alina Vandenberghe shared how  they incorporated AI agents into GTM workflows, in a change that led to the team generating 1400 SQLs with just two marketers.

These agents support sales and marketing across: 

  • Pipeline health 
  • Territory planning
  • Lead qualification
  • CRM upkeep

This frees sales reps up to focus their efforts where they add the most value, creating opportunities. 

“All of the things a typical SDR does are done by agents. Then they own that last mile to make sure that when they get out with a message to an account, it’s highly personal.”

And the results speak for themselves:

  • 17 outbound SDRs
  • 500 meetings booked
  • 160% of quota hit in Q1

To make this model work, sales leaders need to rethink what makes a great SDR for the AI era. According to Alina, the most important skills today relate to creativity, relationship building, and adaptability.

3. Mollie – Connecting customers and product development to reduce contact rate 3x

On The SaaS Revolution Show, Mollie CEO Koen Köppen shared how the fintech leader is using AI to boost customer experience and retention.

Rather than chasing hype, Mollie is embedding AI into processes that directly impact key metrics, and give their customers a better experience. 

“The biggest ability that we’ve internally seen of AI is really bridging the gap between customers and engineers.”

At Mollie, every customer interaction, whether phone, email, or chat, is analysed by AI. They aggregate that feedback to understand the problems being surfaced and direct it to the relevant teams. 

This process has reduced Mollie’s contact rate (% of customers that get in touch on a monthly basis) by 3x in two years. 

4. ElevenLabs – Balancing speed and innovation

ElevenLabs is one of the fastest-growing AI companies on the planet, scaling from $100M to $200M ARR in just ten months. GTM leader Jonathan Chemouny told us that their advantage comes from innovation and speed of execution.

“The biggest difference is everything we do, we move extremely fast. And sometimes it’s not perfect and we know that, but we move super fast.”

He recommends:

  • Avoiding the old GTM playbook. Instead of applying GTM tactics that worked at other SaaS companies, ElevenLabs will come up with new ideas every 4-6 months. 
  • Using your own tech. ElevenLabs uses its own AI audio tools when approaching targets to show the value of its platform up front. For instance, Jonathan cloned his voice and sent sales messages on LinkedIn. This ‘dogfooding’ approach is something we’ve also seen at SendSpark, Storyblok, and others. 
  • Testing distribution channels. As the market gets increasingly saturated, it’s important to try out different channels in different places. For example, ElevenLabs found prospects in some European countries were more likely to respond to Whatsapp messages than phone calls. 

5. HubSpot – Using personalisation to drive 300–500% more booked meetings

Speaking on the podcast, HubSpot’s Kieran Flanagan shared how AI now underpins their GTM engine through personalisation and early-stage engagement, in particular:

  • Personalisation workflows: HubSpot uses AI to tailor outreach and email campaigns based on fit and intent signals in their CRM. This has delivered between 300–500% more booked meetings.
  • Digital avatars: Using a partner called OneMind, HubSpot tested avatars for early-stage sales conversations. To Kieran’s surprise, users responded well and they saw average engagement times of eight minutes. Close rates have improved too.

Aware that not every company has HubSpot’s level of resource, Kieran shared what he’d do if he was building a startup GTM function today:

  • Start with personalisation.
  • Then look at support deflection. 
  • Then free sales teams for consultative selling via AI-powered call prep, deal summaries, and CRM automation

6. Postal – Growing revenue 5000% with AI-led pipeline generation

Like Chili Piper, Postal has achieved significant growth with a very lean sales team (one SDR and three full-time AEs) and the help of AI agents. 

CRO Patricia DuChene explained how AI agents now manages admin heavy tasks including: 

  • Lead sourcing
  • Account research
  • Intent detection
  • Initial qualification

Which means the sales team can focus their attention on “high-confidence” accounts – a model which has seen postal grow revenue by 5000% over the last three years.

Learn more about scaling GTM in the AI era

As we look ahead, it’s clear that every founder needs to consider how to embed AI into their GTM operating systems over the next 12 months.

Things are moving quickly but we’ve got ears to the ground and share actionable tactics from the leading AI and B2B software companies to help you scale your operations and build better with AI.

This article was originally published in the SaaStock Blueprint newsletter. Subscribe to get content like this, straight to your inbox.