UiPath CEO Dines Says Company ‘Survival’ Hinges On AI Success

‘It’s really about the survival of the company to adopt AI and succeed in AI,’ UiPath CEO and founder Daniel Dines says.

Daniel Dines, who returned as UiPath’s CEO in 2024, said he’s back at the right time to guide the company he co-founded through the rapid pace of innovation that defines the artificial intelligence era.

“We have to win it,” Dines told CRN in an interview. “It’s really about the survival of the company to adopt AI and succeed in AI.”

Dines, who co-founded the New York-based robotic process automation (RPA) vendor in 2005, has rebuilt UiPath into an AI-first company that positions itself as offering the best platform to bring together humans, robots and AI agents to automate manual tasks and increase productivity.

[RELATED: UiPath CEO Resigns; Company Names Former CEO, Chief Innovation Officer To Top Spot]

Dines and Ashim Gupta, UiPath’s chief financial officer and chief operating officer, offered some signs of progress in the company’s turnaround on Thursday’s earnings call for UiPath’s first fiscal quarter, ended April 30.

After a fourth fiscal quarter that Bank of America called “disappointing” in quarterly revenue growth and fiscal 2026 outlook, UiPath reported $357 million in revenue during the quarter, up 6 percent year over year and beating Wall Street expectations. Its annual recurring revenue of $1.7 billion marks an increase of 12 percent year over year–about in line with expectations–and includes net-new ARR of $27 million.

Dines and Gupta also called out investments in the partner program, with the CFO explaining to analysts that “it’s super important that our partners are high quality and properly incentivized because they are often very close to our key customers.”

In his interview with CRN, Dines laid out how the vendor is innovating its platform for the agentic era, the importance of solution providers and the competitive landscape looking ahead.

Here’s more of what Dines had to say on turning around his company, edited for length and clarity.

What do you want partners to know about the UiPath Platform for agentic automation?

We started as a company (focused on) what the user would do in the context of a business process looking at the task level.

We can actually emulate what they are doing as long as you can define (it) in rules.

If you want to process an invoice, you read an invoice and you enter into a form some data from that invoice. This is completely rule driven.

We built this platform that had all the components required to automate rule-based tasks. And now with the advent of LLMs (large language models), that gives us the power to emulate people on a more cognitive level. It’s a great opportunity for us to extend our technology.

If you want to approve a recommendation for a loan (for example) … this is very hard to express in rules. And the rules also might change.

Normally, there are people that are doing this type of activity. Now we (have) with the concept of agentic AI, of agents that can help people do some of the cognitive part of the process.

(when) approving a loan, an agent might call a tool to get that person’s credit score. And that tool is a robot.

Using APIs, it can go to credit score agencies, get the person’s score and so on. They might get the person’s history within the bank and so on.

There is a big need to actually orchestrate agents and robots and humans. … When a loan request comes, an agent can intervene, but nobody will trust the agent by itself.

You’ll have to put some humans in the loop.

We have extended our platform, in a way, from rule-based task level to more cognitive tasks and to end-to-end business processes, where you can coordinate between multiple tasks. Some tasks are done by agents, some by humans, some are done by robots. But above them is this orchestration.

How important are solution providers to UiPath’s strategy?

We have started UiPath almost as an indirect company. We work mostly with our partners, with our SI (system integrator) partners.

Not only for reselling, but they make a lot of money in implementing. Typically, in the RPA (robotic process automation) business, (partners see) a one-to-five (multiplier), $1 in license, $4or $5 will go (to them).

They are very interested in this platform. And we are seeing really great reception from large (partners) like Deloitte.

We also have small, dedicated partners that are very active.

It has always been a big strength for us to leverage the community of partners in order to promote our technology.

What’s next for UiPath Platform and your partner work?

Building AI–especially agentic AI–it’s a very different game from what they were used to.

They require massive re-education of their developers to make them ready for the era of AI. Creating an agent is more difficult than creating a script in a programming language because agentic is a non-deterministic technology. It’s very difficult to test.

Together, we have to discover what are the blueprints of large-scale deployments. On one side, we work to simplify the process of development. On the other side, they need to understand how to deploy at scale and how to educate their people, how to educate customers. It’s a joint effort.

Has economic uncertainty affected customer demand?

The macro can affect the length of the deal. Some customers might think twice about their budgets. We have not seen something remarkably different from the past.

But there is a pull from the customers in the interest around agentic. It’s a lot of PoCs (proofs of concept), pilots. But the interest is very real.

One of our big services partners … he said to me, ‘I wish I had hired 1,000 more developers to work on agentic.’ That is a big number. (It’s) because there is that pull from the market. And they even came with this concept to identify your robotic workforce, which means extending the capability of robots with agents.

What’s the competitive landscape like for UiPath in the agentic era?

It’s a huge market. Huge competition from established players, startups. There are horizontal players, vertical players.

What are our differentiators? First of all, we understand how to deploy technology that emulates people. Robots emulate people. Agents emulate people. They come with a set of specific security and governance.

We already have a platform to address it. Where you apply robots, and now you apply agents, it is normal to manage them in the same platform, so you have the same transparent security, roles, permissions, governance.

On our install base, clearly we have the incumbent advantage. Agents, like people, have to have access to multiple platforms. We are the Switzerland of major business platforms. That idea surfaced from discussions with many of our clients.

You can have a Salesforce agent, but that Salesforce agent mostly will work within the Salesforce data ecosystem. People are not going to move data from other business platforms into Salesforce. And the reverse is true.

In terms of integrating with different platforms, we have the best (platform) in the world.

And now with our orchestration on top, I feel we have a very compelling position.

The money will be more in the security, governance, orchestration than the calls to the agent itself.

This is why we also support open-source frameworks to build agents like LangChain, for instance.

On our platform, we want to democratize completely the way of creating agents. The power is in the orchestration, integrations in different systems and the whole picture.

What are other AI vendors missing in their products?

(Other) AI vendors fail to understand the need for trust from customers. They need to trust the technology. LLMs are inordinately not trustable.

Our belief is agents should make recommendations, humans approve and robots will carry out the action.

This type of approach really resonates with customers. There are companies that (say) … ‘let’s (do) a swarm of agents. Let’s have a master agent and you give it a goal, like process all my insurance claims and make it efficient.’

Even if it’s working, I think we are not ready yet to leave it running without even understanding what is going on.

I see it coming, really. But it’s going to be a gradual adoption.

Even if technology is ready, but people are not ready, they are not going to adopt it.

I’m a big believer in our approach, where we have the orchestration piece that is predictable, and the agents will do small tasks that are recommendations. They don’t approve loans, or they don’t make payments. People will make the approval, and robots will do the actual action, which is always 100 percent accurate and precise. I think this is the blueprint for now.

Is Microsoft a UiPath partner, competitor, both?

It’s one of our biggest partners … our cloud works on Azure, mostly. And they also compete with us on the automation part.

At the same time, Microsoft’s competition to us, it’s limited, mostly to personal productivity when you want to run a bot that works with you on your desktop. We focus a lot more on having our robots work autonomously.

You have an end-to-end business process. In order to automate it, you have to take as much as possible from people’s plate and move it to run autonomously in the cloud because if you have people having to do a lot of work on their desktops, you don’t achieve the same level of automation and the same KPI (key performance indicator), same precision.

We are the best in the world, clearly, to run autonomous roles that are required. In this loan application example, we reduce the role of a person to only to to read a loan summary, approve it, and then the robot works in the cloud, autonomously completing everything.

All the papers, going to the banking systems, making the wire into customers’ accounts. Everything will be done completely autonomously. This is very powerful.

Are customers starting to feel left behind if they haven’t started adopting AI?

We are in the early innings of deploying GenAI (generative AI) in the context of enterprises.

Many of them talk about use cases, PoCs, pilots. It reminds me of six, seven years ago, how RPA was deploying. It’s normal.

We work a lot to create use case references, customer references that help create replicable sales motions.

The industries where we are seeing the most activity–it’s clearly the financial service industry, health care, public sector.

As you approach one year of returning to the CEO role, what has changed in that time?

I’ve come back to the company at the right moment when the pace of innovation in AI is ridiculously fast, and we have to win it. It’s really about the survival of the company to adopt AI and succeed in AI.

I’m learning a lot day by day. The company is learning. We have transformed a lot of our work. We are an AI first company. We agent-ify everything within UiPath.

This is a big initiative. Everybody’s compensation will be tied to how well we agent-ify the company. It’s reasonable for customers to also see what you are doing internally. And we are learning. We are our customer zero.

It’s an exciting moment. I’m really happy that I am in this position.

To me, agentical automation is a bigger opportunity than RPA. And I hope that we will have even bigger revenue in a few years from agentic than from our core areas.

Convincing customers, partners–it’s a continuous flywheel.

I’ve seen from a few of our customers the desire to go very big. I was talking with one of our largest hospital chains in the U.S. And they think of completely reimagining share service in health care, almost starting with a white piece of paper.

It’s a fantastic opportunity for us and our partners.

How about outside of the AI moment, what else is fueling demand by UiPath customers?

We have an overarching platform.

Many people come with the only AI approach, only AI or API. But we have everything. We have document understanding. We have our RPA that can go to legacy systems that are still important. You still have agents.

I want our partners to understand the breadth of our platform and how capable it is to go and automate end-to-end processes.