The following is excerpted from the question-and-answer section of the transcript.
(Questions from industry analysts are provided in full, but answers are omitted - download the transcript to see the full question-and-answer session)
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: <_ALACRA_META_ABSTRACT>Yes. Absolutely. Matt's going to chime in here with some questions as well, but I wanted to set the stage.
After joining the company, first of all, give us an overview as to what your -- what are the key things you're working on? Every CFO
coming in has a mandate, right? What is kind of your mandate? And also as an adjunct to that, what does success look like for you
and Andrew and the team in the next four to five years ahead?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Excellent, excellent. As you went on this 10-month journey, many of us, when you go into a job, we have an expectation of what it
is. And then there are certain things that catch us as a surprise, positive, negative, whatever it is. So how would you characterize the
things that surprised you relative to what you expected anyway going into this job at this company?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: All right. Simon is going to say, I've heard this so many times, Kash. Just stop boring yourself, painting yourself into this corner being
the oldest guy in the room. But the first software application that I used, even before Microsoft Word and Excel because those didn't
exist, was AutoCAD LT, like back in college. So I never knew that that would be a public company that will be covering their stock
and having the CFO of the company --
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: And before this was tape drives. We had an air-conditioned room and only three of us could access it, and I was not the best
programmer, by the way. I kind of followed on, but that was my first exposure.
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SEPTEMBER 08, 2025 / 6:30PM, ADSK.OQ - Autodesk Inc at Goldman Sachs Communacopia & Technology
Conference
Let's talk about go-to-market since there's been a lot of changes. I think Autodesk went through its first big change, at least in recent
times in 2016, the subscription model transition. And when you came upon the scene, it was this transactional model.
So how has the go -- if you take a step back, how has the GTM function evolved at the company? And how do you see that evolving
as a result of the transaction model?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Can you share with us a little bit more detail on the optimization that [that world] have heard since you joined the company? It's
sort of like you got hired to do optimization in addition to a million other things, right? What does optimization mean in your lingo?
And can you apply that to a few business functions so we can kind of visualize and [size] what that means?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Simon, I'll loop you in on the transaction model piece. I just want to --
Unidentified Participant
He's got a PhD in the transaction model. I mean, (multiple speakers) but maybe just give us a mark-to-market on kind of where we
stand in terms of the rollout of the transaction model, the expected benefits? And if you're realizing any of those today, given that
we're still pretty early.
Simon Mays-Smith - Autodesk Inc - Vice President - Investor Relations
Yes. So on track, the way I describe it, whenever you're doing big implementations is you have a bunch of assumed one-standard
deviation things, and we talk to things about channel partner product during the transition just because they had a bunch of other
work. But we haven't had any three-standard deviation events, thank goodness, and that's a function of good execution of the
process.
The other thing to understand is that this isn't a single sort of one-off, one and done. It's a bunch of optimizations, to Janesh's
comments, both across revenue and across cost over time, some of which happened quickly. So for example, the 9% risk we had
earlier on this year and some of which happen over time.
So for example, we've talked about some of the lower-end customers channel shifting and coming directly through the eStore, that
happens over multiple different quarters. So you talk about it on sort of different duration.
And then the final bit is the sort of financial impact is that you have essentially the math impact of the pre-revenue costs shifting
from pre-revenue into sales and marketing that come through billings first and then it flows rapidly through the P&L over time. And
so we're past sort of the billings peak, and we are approaching the peak of the revenue peak, and then it will start dissipating as we
go into next year.
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Okay. Great. And then, Janesh, maybe just stepping back a little bit. You've seen a lot of momentum in the construction segment,
right? So can you tell us a little about what's driving this ongoing momentum and where you see the next potential leg of growth
for the AEC category?
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SEPTEMBER 08, 2025 / 6:30PM, ADSK.OQ - Autodesk Inc at Goldman Sachs Communacopia & Technology
Conference
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Yes. I want to drill into the ACC product specifically. So I mean, I know you have thoughts here around kind of the broader competitive
landscape, but just give us kind of a broader understanding of kind of where you think Autodesk fits into the kind of construction
management category and sort of maybe the competitive win rates you're observing against some of the other players out there in
the market?
Simon Mays-Smith - Autodesk Inc - Vice President - Investor Relations
The opportunity is the same as it's always been, which is the single most important strategic priority for our customers is to wrangle
the data. So if you speak to Bill Okland of Okland Construction, he's saying, look, I've got to get control of my data, which is partly
around putting it into the cloud, but then it's building value on it.
And the reason they want to build value on it is so that they can work remotely because of the pandemic, so they can manage supply
chain shocks that they can apply AI to it. Pretty much everything that's turning up in their everyday life is driving more cloud and
more data wrangling.
So more prosaically, if you speak to the construction customers, what they'll tell you is that 70% of the problems that turn up on a
construction side because the decision was taken in the design and preconstruction. So that's why they want to connect it upstream
as well.
And then they also want to connect it downstream once they hand over to the customers. So we've got a data center that's got a
lifespan of over long 20, 30 years or however long it is. And optimizing that, the construction customers want to have an ongoing
relationship. They're having a digital twin that allows them then to have an ongoing relationship on the operations and maintenance
side and to extend the relationship downstream. But the core of it is wrangling data.
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Yes. Let's talk about AI from a product perspective and then maybe from a monetization perspective. So I think like Autodesk has
effectively sort of two approaches, right? I think like right now, you're infusing AI in some of these kind of core more road functions
solutions like auto constraints, but then you have a big grandiose vision around things like Project Bernini. So maybe unpack that
opportunity that you see from a product roadmap.
Simon Mays-Smith - Autodesk Inc - Vice President - Investor Relations
Yes, the same thing, but it's the fact that AI is a continuum, not a fixed point, so a continuum from feature automation, which is part
of a workflow; to workflow automation, which is the traditional silos you think about in design software; to system automation,
which is essentially cross silo or end-to-end when we talk about. And so that's some of the conceptual design stuff being able to
make influence on the construction phase that I was just talking about.
As you move up that stack, two important things happened. Firstly, the model sizes get bigger from a relatively small model for
feature automation to work for automation to system automation. The reason that's important, the model size, is that for feature
automation with a small model, you can deliver that and have the compute happen on the desktop and that means you can deliver
feature automation value in the way you would with a traditional product, which is delivered as incremental value to a subscription
product and the value captured in price, and we're doing that today already.
But as you move up to bigger models, you can't do it with a traditional subscription product because you're delivering a lot more
value and you need to capture that value, but you're also delivering more variable costs through more compute, and you can't put
that through a fixed subscription price point. So as you move up that stack, you will shift to more consumption-type model to capture
that value and cost, first thing.
And the second thing is as you move up that stack, the breadth and depth will move beyond the capabilities of the human brain to
be able to do it. And so what that means is that you will move from human-led processes to machine-led processes. So because a
human brand cannot make those connections between a block of land and what's going on in construction, and a machine can.
The reason that's important is that we will be able to deliver significantly more and greater dollar value or value to our customers.
There's one vector of opportunity for ourselves. And also, there's a second vector of time, which is the machines don't have to sleep
when humans do. And so you have machine working 24 hours a day, 365 days a year.
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SEPTEMBER 08, 2025 / 6:30PM, ADSK.OQ - Autodesk Inc at Goldman Sachs Communacopia & Technology
Conference
So yes, except for junior analysts, yes, I used to be one of those, so I know how that feels. And so there are two vectors of monetization
opportunities. So for everyone sort of [worrying around whether hair on fire], worrying about seat-based models, what you are not
thinking about is that machine, incremental machine consumption, which has two significant vectors of monetization.
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Interesting. So have you thought about, maybe it's still early, how you price the consumption credits? And do you start off with a
limited number of credits that are part of a free pack and then there is an upside trigger? Have you given thought to how you could
get economic realization from --
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Sigma is not exactly in aerospace, but design. They have taken the approach of investing aggressively to push [Make], Sigma Make,
which requires a lot of GPU cycles. And we all had to take a big step down. Not anything surprising because it's all contemplated
and premeditated, obviously.
But the pace of margin compressions they had to endure to generate new revenue streams from [MIG] was quite significant. How
do you guys think about -- since you have your own model, is it a little bit more efficient from a GPU consumption standpoint? Or
what are the puts and takes of going for this? Are there sacrifices that need to be made before you can start to see the benefits?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Particularly on the AI side?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Not that I intended to ask this, but as I've listened to you talk about that, this concept of a world model, where the inputs are actually
video and images as opposed to a text-based model, which is the world that we live in, how are you training Bernini? An open-ended
question.
Simon Mays-Smith - Autodesk Inc - Vice President - Investor Relations
So I mean, based on data that we have access to --
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Pretty sophisticated engine. It's not like --
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SEPTEMBER 08, 2025 / 6:30PM, ADSK.OQ - Autodesk Inc at Goldman Sachs Communacopia & Technology
Conference
Simon Mays-Smith - Autodesk Inc - Vice President - Investor Relations
Correct. And that's again -- so we use a simple analogy. The vast majority of AI engines, if you ask them to produce a water jug, will
produce you a beautiful-looking water jug. But if you rotate and look through the top, they won't have a hole in the middle to hold
water because they have no concept of depth.
Now there's a bunch of other things around how you -- the geometry is also not (inaudible) as well, which our customers care about
and a bunch of other stuff. But in simple terms, and having that concept of depth is a key differentiator.
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: How much of the other models do you have to use like an OpenAI or an Anthropic versus your own proprietary Bernini model?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: And how close are we to Bernini being available in its full form and functionality? So capability --
Simon Mays-Smith - Autodesk Inc - Vice President - Investor Relations
I mean, you'll see more at Autodesk University next week.
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SEPTEMBER 08, 2025 / 6:30PM, ADSK.OQ - Autodesk Inc at Goldman Sachs Communacopia & Technology
Conference
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Great. And then any questions from clients?
Unidentified Participant
(inaudible - microphone inaccessible)
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: Yes, the final question. I think we have time Yes, go ahead.
Unidentified Participant
You spoke a lot about the advantage of your 3D data, something which your competitors seemingly are lucky enough, you guys to
have. Could you talk a little bit more about the challenges of using that data within your AI stack? And more importantly, are any of
your competitors even bothering to try to catch up given the low ROIs that you were talking about that they might be -- they might
earn from that?
Question: Kash Rangan - Goldman Sachs Group Inc - Analyst
: On that note, we think we're a little bit ahead of -- actually behind time. But thank you so much. We wish you well on this transformation
journey and also looking forward to seeing what's ahead with Bernini and the word model in your own word and what it looks like.
Thanks for coming once again. Thanks for your attention as well. Let's have a great conference.
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