Will AI Agents Kill Customer Service Jobs? | Alexander Matthey (Parloa)

"Can you be a software engineer in the future without using agents to help you be productive? I don't think that's a chance."

Jun 27, 2025

I sat down with Alexander Matthey, co-founder and CTO of Parloa, where he's building the AI agents that promise to revolutionize how businesses interact with their customers. But unlike the doomsday prophets predicting mass unemployment, Matthey paints a more nuanced picture of what's coming.

We dive deep into the transformation of customer service, the survival strategies for BPOs, and why building the "Ferrari" of AI platforms matters more than ever.

The Speed Game Has Changed Forever

Starting a company in AI isn't like starting one in fintech or beauty tech. Matthey learned this the hard way after his experiences at Adyen and Glossybox.

"I think the biggest differentiator is, I think I was always obsessed with speed and I was also obsessed with focus. However, currently the industry is moving very fast as well and also there's so much noise and so much things that can disturb you so much more than in FinTech and so much more than in Beauty."

The challenge isn't just moving fast—it's maintaining focus while the entire industry shifts beneath your feet. Where founders once competed against each other's clock speed, they now race against the market's relentless pace of innovation.

The Radical Vision: People Will Actually Want to Talk to Customer Service

Here's where Matthey drops his most controversial take. Parloa isn't just automating customer service—they're reimagining it entirely.

"We believe that in the future people will want to talk to somebody at customers. And that's what Parloa is building towards... People will not just reach out when they have a problem like it is with customer service right now, but they will prefer to talk to their personalized AI agent going forward."

No more opening hours. No more language barriers. No more waiting on hold while terrible music plays. Instead, imagine having a personal AI agent that knows your entire history and can handle complex requests across multiple channels and languages.

Customer Service Agents: Evolution, Not Extinction

But what happens to the millions of customer service representatives worldwide? Matthey doesn't sugarcoat the transformation, but he also doesn't predict their demise.

"I think the job of a customer service agent will not completely go away, but it will become much more specialized on very complex use cases, on very specific use cases. So therefore it will also be more fun."

The mundane password resets and tracking inquiries? Those are gone. What remains are the complex negotiations, the emotional support calls, and the edge cases that require human judgment and empathy. It's a fundamental shift in the role, not an elimination of it.

Why Enterprises Shouldn't Build Their Own AI Agents

With AI democratizing software development, why wouldn't large enterprises just build their own customer service agents? Matthey has a clear answer, drawn from his Adyen playbook.

"I think you want to control what's really important for your business. And I don't believe that the development resources of many large customers, many large enterprises are best used to build an agentic OS, to think about how to build simulations, evaluations for agents, how to build guardrails across different regions."

The complexity goes far beyond just connecting to an LLM. It's about versioning agents, managing hierarchical tenant systems, ensuring compliance across regions, and building evaluation frameworks. These aren't core competencies for airlines, insurers, or retailers—and they shouldn't be.

The Ferrari Strategy: Why Execution Beats Everything

In a world where everyone claims to have the same features, how do you differentiate? Matthey's answer cuts through the noise with a perfect analogy.

"It's the same with, I don't know, like a Ferrari. Can somebody else build a Ferrari? Yes. It's also only steel and the motor and the engine and some leather and stitching. Is somebody else capable of doing it? Well, that's the problem. So you need to get the right team together and you need to focus on really building that Ferrari."

This isn't about having unique features—it's about executing better than anyone else. Just as Adyen succeeded not through proprietary technology but through superior execution, Parloa aims to win by building better, faster, and with more focus than competitors.

The Jerry Maguire Moment: Building Modular from Day One

When pressed on how someone could beat Parloa at their own game, Matthey reveals a crucial insight that many AI startups miss.

"There is a strong lever into the industry, especially the enterprise industry, if you from the very start think about how to make it a modular system, to be honest. So that you do not only rely on one very specific agent SDK, one specific LLM, one specific STT or TTS provider."

Large enterprises have existing contracts, approved vendors, and specific compliance requirements. A one-size-fits-all solution won't work. Building modularity from the start—allowing customers to plug in their preferred LLMs or use their existing cloud credits—becomes a massive competitive advantage.

The Future of AI Agents: More Than Just Chat

Looking ahead, Matthey sees AI agents handling increasingly complex tasks, moving far beyond simple query resolution.

"What you see right now is that, I don't know, like the first use cases are intent recognition, or the first use cases are, you know, take over a few of the higher volume use cases, where I think that will grow over time and over time towards, you know, also being able to receive payments or also being able to not just help cancel a booking or refund the booking, but actually plan a whole trip."

The limitation isn't the AI—it's often the enterprise systems that need to expose their capabilities through APIs. As these barriers fall, agents will orchestrate complex, multi-step processes that today require multiple human touchpoints.

BPOs at a Crossroads: Adapt or Perish

For Business Process Outsourcers, the message is stark but not hopeless.

"I think the BPO's that actually start driving this change will have a chance, a good chance of being successful in the future as well... However, if they don't change, they will be out of business relatively soon."

The opportunity lies in becoming the bridge between AI capabilities and non-digital native industries. Airlines, insurers, and energy companies need partners who understand both their legacy systems and the new AI paradigm. BPOs that position themselves as transformation partners rather than just labor arbitrage will thrive.

The U.S. Expansion: Bringing European Execution to American Speed

Parloa's U.S. expansion follows a familiar playbook—one Matthey helped write at Adyen.

"We want to be a US company, there is some value in being global as well. If you're looking at the largest companies in the world, they are all global as well, and they will want to run their agents globally."

But this isn't just about planting a flag. It's about absorbing the American approach to innovation—the willingness to think "out of the box" that Matthey admires from the Ford vs. Ferrari story. By combining European execution discipline with American innovation speed, Parloa aims to serve global enterprises that need both.

Why AI Actually Deserves the Hype (With Caveats)

In an industry full of hype cycles, Matthey makes a bold claim about AI's staying power.

"Agentic AI is one of the first things that deserve the hype for very long time... I do strongly believe that agentic AI will actually have an impact on many angles of our society, will change jobs, will change how education works, will change how communication goes."

But he tempers this enthusiasm with realism about implementation challenges.

"People underestimate the nitty-gritty details that are necessary in order to bring things in production into scale at a high accuracy."

The technology works in demos. Making it work at enterprise scale with 99.9% reliability? That's where the real work begins.

The Engineering Evolution: Smaller Teams, Bigger Impact

The transformation isn't limited to customer service—it's reshaping engineering itself.

"Engineering productivity will grow dramatically going forward... I do believe we need to get to very performant delivery with a way smaller team than in the past."

But this doesn't mean engineers become obsolete. Instead, those who refuse to adapt will find themselves left behind.

"Can you be a software engineer in the future without using agents to help you be productive? I don't think that's a chance. Like if you in two years try to get a job and said like I don't do that vibe coding thing like I'm still more productive than all of these hundreds of agents—that will not work."

The Path Forward: Value-Based Pricing and Outcome Focus

Perhaps the most fundamental shift Matthey predicts is in how AI services are priced and valued.

"Going forward, yeah, I think it would be nice to be able to pay agents for the tasks that they have successfully achieved and actually deliver value. So that is our long-term goal."

Moving from time-based or consumption-based pricing to outcome-based models aligns incentives between providers and customers. It's a shift that mirrors the broader transformation in customer service—from measuring minutes to measuring satisfaction and resolution.

Key Takeaways

Alexander Matthey's vision for AI-powered customer service is both revolutionary and evolutionary. While the technology promises radical improvements in customer experience, the path forward requires careful execution, deep enterprise understanding, and a willingness to tackle the unglamorous work of integration and reliability.

For customer service professionals, the message is clear: adapt and specialize. For BPOs: transform or die. For enterprises: focus on what makes you unique and let specialists handle the AI infrastructure. And for entrepreneurs: remember that in a world where everyone can claim the same features, execution is everything.

The future of customer service isn't about replacing humans—it's about augmenting them and creating experiences that customers actually want to engage with. That's a future worth building toward.

What do you think about Alexander’s approach to building at Parloa? thoughts on AI GTM strategies? Join the conversation below.

Companies mentioned:

Parloa
Adyen
Glossybox
OpenAI
Anthropic
Google/AWS/Microsoft
Ferrari
Ford
CBRE

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