Technology · AI · GTM
Where deep tech
meets business.

I work at the intersection of technology and go-to-market — helping companies navigate complex software decisions and thinking out loud about how AI is reshaping the way B2B teams operate.

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Atro Ranta-aho
10+
Years in
B2B tech
5
Sales teams
built from zero
15+
Industries
covered
3
Continents
lived and worked

The best people in technical sales aren't the smoothest talkers — they're the ones who actually understand the technology, can simplify it, and take a consultative approach with their customers. This is how value is added.

I have a Master's Degree in Mechanical Engineering from Aalto University. Spent my early career at Metso managing global supply chains and leading a global team sourcing parts across three continents. I then found the world of software sales and joined Sievo — a B2B SaaS company focused on Procurement Analytics. At Sievo, I built our US presence from scratch to 1/3 of the ARR and later led the company's global Account Management organization. After Sievo, a stint at CybExer Technologies, learning the world of cyber security, building CybExer's SaaS sales from the ground up.

I currently work at Qt Group, where I lead global sales for Software Quality Solutions — working with engineering leaders and decision-makers across industries, mostly on embedded software projects.

My work has taken me to live and work in three continents, and I've been managing multi-national teams located across the world for 12+ years.

"Most companies are either ignoring AI or overclaiming it. The interesting work is in the middle."

I think AI is the most consequential thing happening in technology right now — and that most of what gets said about it is wrong in both directions. That gap is what I find interesting: not the version from the stage at conferences, but the practical, day-to-day reality of what actually shifts starting now.

I come at that from two directions. One is commercial: what AI does to how B2B teams sell, qualify and decide. The other is Physical AI — what happens when the models move off the screen and into cars, robots and machines that have to be safe as well as clever.

The shift isn't about tools. It's about workflow and people. Teams that redesign how they work around AI will outperform the ones that just add AI on top of the old way. The gap between those two groups is already opening up.. and it will not close.

I've spent the last couple of years studying this closely — what the leading teams are actually doing, where the real productivity gains show up, and what separates genuine transformation from expensive experimentation. Some of it I've built myself, mostly to find out where the limits actually are.

Some of what I've learned and created, I will share with you here.

GTC Berlin: AI is moving into the physical world

The car became a consumer electronic — notes from a week in Shanghai

I spent an intensive week in Shanghai recently, supporting our local team and meeting current and future customers. I've been coming to China for more than ten years now and it still rearranges my assumptions every time — in some ways it feels like a trip into the future and the past simultaneously.

The thing that stuck with me this time wasn't in a customer meeting. It was in the back of a Didi.

Several of the taxis I rode in had a transparent chassis system — 透明底盘, the composited under-vehicle view that lets a driver effectively see through the floor when parking or navigating a tight space. In Europe I had filed that away as a premium feature, something you find near the top of an options list. In Shanghai it was in ordinary working taxis with serious mileage on them.

Feature parity arrived quietly

The numbers behind that are the part worth sitting with. More than 70% of new cars sold in China now ship with L2 or higher ADAS. Cars priced around ¥196,000 — roughly €25,000 — come with systems I would have called premium two years ago.

The easy read is that features got cheap. I think that misses it. What actually happened is that the car changed category.

The replacement cycle tells the real story

Chinese industry data puts the average age of a used new-energy vehicle at around 3.4 years, against roughly 8.6 years for a used petrol car. Somewhere near 90% of NEVs get replaced inside five years, while about 70% of petrol cars stay with their owner longer than that.

Those aren't the numbers of a durable asset. They're the numbers of a device. People are buying cars on something much closer to a phone cycle, and everything downstream of that assumption changes — how the thing is sold, how it's serviced, and above all what the software is expected to do after the sale.

The retail side made the same point visibly for a while. NIO opened its Shanghai flagship inside the HKRI Taikoo Hui mall in 2017, complete with a library and an art gallery, and for several years the mall showroom was the signature of the new Chinese brands. That particular experiment is now receding — EV brands have been pulling out of mall space, with robotics and sportswear brands moving into the units. The storefront was a phase. The buying behaviour it was designed around stayed.

What that does to software expectations

This is where it gets directly relevant to anything I work on. In the customer conversations, the expectation that came up repeatedly was constant updates. Not "does the software work" — that's assumed. The bar is whether the experience still feels new and relevant a year in. If the car is a device on a three-year cycle, the UX has to keep earning its place for those three years, and a release cadence measured in model years doesn't survive contact with that expectation.

The regulatory posture follows the same logic. Local OEMs have adopted the Western frameworks — ASPICE, AUTOSAR — selectively rather than wholesale, optimising for speed over ceremony. It's a genuine trade rather than an oversight, and it carries genuine risk; the interesting question is not whether it's correct but how long the gap between the two approaches stays survivable for the slower side.

The uncomfortable part

If your development assumptions are built around a fifteen-year vehicle life and a multi-year release cadence, you may be building very carefully for a product category your competitor has already left.

What I can't tell you is whether a three-year replacement cycle is a market that stays that way, or an artefact of how people treat any new technology before it settles down. Ask me again after the next trip.

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