From managing work to doing the work - how workforce management firm monday.com is putting AI into practice internally and externally

The vision of monday,com has changed - from managing work to doing the work. That's very significant, argues co-founder and co-CEO Eran Zinman. It’s also now inherent in everything that’s done at the workforce management firm, he pitches:

We're amplifying and changing our company 'North Star', and this is a big deal. For years, since we started the company, our mission was to manage the core work for our customers. And with AI, this vision is amplified. Our vision now with AI is to manage to do the core work for our customers, not just manage work but actually doing the work for our customers. 

Definitely, AI is a transformative technology. It changes almost anything for our customers, the way they perceive value they can get from software. It changes how companies go to market. It changes how company scales. It touches almost any aspect of our customers and ourselves as a company. And we at monday, we embrace that, and we want to go all in on AI. 

Ah yes, AI - it is 2025 after all. That is also having a major impact on the firm internally. Fears around the job loss impact of AI adoption remain hugely current. Recently Salesforce CEO Marc Benioff attracted a lot of attention by casually mentioning in an interview that he’s been able to reduce the Customer Support team headcount by thousands, although in reality a large number of the supposed losses were redeployments. Salesforce would look like a different company by the end of this year, he predicted. 

There’s a similar scenario at play at monday,com where headcount growth is due to slow down over the coming years as AI settles in across business functions. Zinman explains:

In 2026, we plan to scale our head count by only 20% after 30% in 2025. And we do that by leveraging AI and just increasing efficiency overall. Basically, we're leveraging AI internally to make our Sales team more efficient, to make our Customer Support more efficient and to make our R&D more efficient. And I think that going forward, '27, '28, we'll be able to scale the company even more while increasing their headcount in even a less significant way in 2026.

This is a result of putting into practice a basic guideline against which the firm operates, he says:

We see one of the main guidelines is the fact that companies now have the ability to have almost infinite workforce…We feel that with AI, you can do so much more with the same headcount and even the existing headcount can become much more efficient. This is one of the big bets and guidelines that guide us through this journey and the roadmap that we're going to have.

A second guideline is that software becomes more accessible, not just for IT people but across the various functional silos in an organizaton. Zinman argues:

You no longer have to be a tech person or to know how to code in order to build software. And in a way, this is our vision on steroids. We always aim to have the most flexible software for our customers. And with this vibe code in motion, we can give them even more freedom to our customers. And again, like the first one, the second principle, we're going all in…We’re going to leverage live coding with our existing platform…those two things come together and offer a solution that's not only customizable and flexible, but also is enterprise ready and ready to scale.

AI adoption

Against this backdrop of the bleeding edge, Zinman makes a startling admission:

We feel with AI, technology is moving very fast. But when it comes to actually adopting the technology, I think ourselves and also our customers are way behind.

That dose of realism aside, he goes on to state that the thirst customer have for AI is leading to adoption that is “off the charts”. Citing the traction behind the AI features in the product set to date, he says:

Up to date, there's already over 67 million AI actions on our platform. In addition to that, in the past 9 months, we've been very busy, the busiest we've ever been as a company, working very hard to create new products and add add-ons to our existing products. We launched magic[a natural language interface for creating workflows] and sidekick [a context-aware digital assistant that understands a user’s company, role, and responsibilities], [with] already 45,000 actions in monday sidekick alone. We launched monday vibe, which is essentially a vibe coding platform on top of our platform. Already 7,000 apps were built in just two months. And with monday magic, which helps you build solutions, 2,000 solutions were built in less than three months.

While other vendors make a point of ‘eating their own dog food’, over at monday.com it’s caviar that’s on the menu and being wolfed down, according to Casey George, Chief Revenue Officer. Picking up on the transformational nature of AI in the product set, he touches on the emerging role of agents:

When you have 250,000 customers and you want to deliver a great experience, you cannot do that entirely with humans. We know today that when we touch customers, we'll call them high touch, the churn rate is almost nothing. So if we could give that same experience at scale across the 250,000-plus customers, just think of how happy our customer set would be. And so we're doing that. We're leveraging AI to do this.

As to how that works in practice, he goes on:

We know the more customers we can get to in a very quality way, the better our conversion is going to be. So what we launched a couple of months ago, and candidly one of the greatest opportunities we have as a company to scale, is we launched an AI agent to go sell to these customers to qualify these opportunities to bring in the right resources, surmise the opportunity, get it into our CRM and get everything scheduled.

They did this in a matter of minutes, he says, citing 1,000 calls, 250 meetings booked and 180 leads generated:

We have hundreds of thousands of leads come in every year. If you think about that, I would need 10,000 people to support that volume, and that's just not efficient, right? So my objective is to give a quality experience to every lead. Whether we think it's a quality lead or not, we want to give the same experience to every one of those leads.

The number one indicator of your ability to convert a lead to a sale is your response time. So if I can respond to every one of those opportunities that come into us in a very high-quality way, in a very responsive way with SLAs, with a quality message, a consistent experience, my opportunity to convert goes through the roof.

AI is going to give monday,com that capability, he asserts:

We've launched our agents to do just that because now I have unlimited capacity. Literally, any hour of the day, as many calls as you want in parallel, delivering an expert response to their questions and engaging and building out an opportunity profile in seconds delivered to the rep in a very warm way where they can engage with the customer on a customer - that feels like monday cares, right? They care because they call me back in two minutes. They had all the answers and they scheduled everything just as I wanted it. So for me, this is obviously a significant opportunity that we're going to leverage going forward.

My take

A confident articulation of AI strategy with clearly a lot to gain from executing on it effectively.

The firm does appear to have the right direction of travel  - its most recent quarterly profit came in at $57.3 million, up from $33.7 million a year earlier, while revenue was up 32% year-on-year to $268 million. For the full fiscal 24 year, revenue was up 33% on the previous year, with net income of $183.3 million.

The big question for monday,com, as it is for so many of its peers, is whether customers will apply the same context and sophistication to its approach to AI and work as it professes to do, rather than using the tech as a blunt instrument to beat out cost efficiencies against the backdrop of continued macro-economic turbulence.

One to keep an eye on.

Onwards.