Atlassian CEO：AI 会创造更多软件，而非更少
Atlassian CEO: AI Will Create More Software, Not Less
Atlassian 联合创始人兼 CEO Mike Cannon-Brookes 认为，AI 让软件开发更便宜、更快，反而会促使企业创建更多应用、工作流和智能体，从而更需要连接与管理它们。他透露使用其 AI 解决方案的客户增速是未使用者的两倍以上，并称 AI 对 Atlassian 是巨大顺风。
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Oct 13th, 2026
Atlassian CEO: AI Will Create More Software, Not Less
Atlassian Co-Founder & CEO Mike Cannon-Brookes thinks rather than killing enterprise software, making software cheaper and faster to build, will lead organizations to create more applications, workflows and agents, increasing the need to connect and manage them. He speaks with Haslinda Amin on "Insight with Haslinda Amin."
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0:00
Let's talk about that. That happened, you actually used $250,000,000 of your own money to buy
0:07
back your shares. What do you think Wall Street actually misunderstood about the whole situation, how
0:13
vulnerable Jira and Confluence really are.
0:19
Yeah. Hi, Haslinda. Thank you very much for having me. Look. I mean, Atlassian is a
0:24
business. We're doing extremely well. We've accelerated for a number of quarters in a row. Our
0:29
AI driven platform is really being taken up by customers all around the world. I'm I'm
0:34
here in Singapore visiting quite a number of customers across the region. And our our solutions,
0:41
our products, our platform help companies to really adopt AI in terms of how it comes
0:46
out into their teams, into their knowledge workers, and how it actually becomes a part of
0:50
their business processes and the ways that they work. Our customers that use our AI solutions
0:56
grow at more than twice the rate of those that don't. So I think we're justifying
1:01
that, you know, AI is a huge tailwind for Atlassian. I say it all the time.
1:04
It's it's one of the best things to ever happen to our to our company is
1:06
these new technologies and tools we have to solve the same problems for our our customers'
1:12
teams in in ever better ways.
1:18
Well, the thing is, Right, Mike? I mean, if an AI agent like Claude can read
1:23
enterprise repositories and also build custom workflows, why should companies be paying you millions and millions
1:29
of dollars?
1:32
Sure. Look. There's a lot of agentic harnesses that are very, very good. We use a
1:37
lot of them ourselves in order to help us, build and improve our software applications. Fundamentally,
1:43
what Atlassian does is helps teams of people, collaborate in organizations all around the world. So
1:48
in service teams, in business teams, strategy and leadership teams, and, of course, in technology teams,
1:55
those teams of people use many, many different applications and put them together. What, we have
2:00
in the teamwork graph, a big part of our platform, which is the context graph of
2:05
enterprise knowledge, is how we take all of the history of decisions and documents and code
2:11
and information in the company and put it together into a context graph so that we
2:15
can give better answers to a Claude or any agentic harness that's being used. So we
2:20
actually have a a deep partnership with Anthropic, a big partnership with OpenAI, with Google, bringing
2:25
that that enterprise knowledge of those processes, the history of decision making out. I I would
2:31
say if your AI can't understand why you made a decision in a team or in
2:35
a group in your company in 2019, you can't make the best decisions in 2026 or
2:42
- Your agents certainly can't understand that. And so we really help companies to take that
2:47
information from across their company, connect it into the teamwork graph, and then provide it to
2:52
all those agentic harnesses while at the same time having a, human experience of how agents
2:57
and, and people will, will work together.
3:00
Right. Mike, you're navigating one of the most challenging times for the company. I mean, you
3:09
recently cut about 1,600 of your workforce. That's about 10%. What's that tipping point that led
3:17
you to make that decision?
3:21
Look. Obviously, those are always very, challenging decisions. Part of the part of the job is
3:26
navigating the times and making, you know, making the right decisions. In that case, you know,
3:31
we needed to rapidly change our skill mix as a company. We're very clear at the
3:35
time. The AI part of our business is doing very well and growing very fast. The
3:41
enterprise sales part of our business, so dealing with the world's largest companies like Bloomberg is
3:46
a fantastic fantastic customer. Many other very, very large customers around the world growing very fast.
3:52
And so we needed to change the skill mix inside the company to invest even more
3:57
heavily in those areas that are doing really well in terms of AI and in terms
4:00
of the skill mix. That is a part. We're still growing as a company incredibly strongly.
4:06
Again, we grew 28, 29% revenue last quarter on a 1,800,000,000 quarterly, know, quarterly revenue rate.
4:14
So even at the scale we're at, we're actually accelerating as a company and continue to
4:19
do so due to the the AI tailwinds that we have in terms of how we're
4:22
helping companies and their teams be more effective across all of their their business processes.
4:33
Mike, I wanna take a look at the tech space as a whole, IPO in particular.
4:37
We had farmers recently ditching its $44,000,000,000 IPO plan. What's your reading on it? I mean,
4:43
you've been quite vocal know, the poor quality of tech IPOs.
4:50
Look. I don't know all the details of that. I tend to to stick to my
4:54
line and and the things that, I focus on, and, obviously, we're we're here dealing with
4:57
customers as a good example. I do think, companies that have a really deep technological foundation
5:00
customers as a good example. I do think, companies that have a really deep technological foundation
5:02
are able to navigate these, these times and these changes. Certainly, at Atlassian, we spent a
5:09
lot of time, focusing very deeply on our technological foundations over the last two years. Right?
5:14
The last three or four years now of the AI era, the the the approach we've
5:20
taken is we have to create our way through it. Right? We're going to have to
5:23
create new technologies. We're gonna have to leverage all of these technologies to actually build new
5:28
value for customers with all of these amazing tools that we that we have access to
5:34
in terms of the AI and the and the models and how we bring that to
5:37
customer value. So I would say it's about having a deep technology core, at least for
5:42
us. Other companies can can do their, their own thing.
5:51
It is pretty interesting that the fund managers at home actually balked at the valuation of
5:56
$44,000,000,000. Is this a healthy development? I mean, people are beginning to question the AI space
6:03
and the tech space and the amount of money that's been, you know, plowing into that
6:08
space.
6:12
Again, I can only comment on those fund managers from the point of view of Atlassian.
6:16
We have a lot of great Australian shareholders and Australian investors. Really fabulous to see their
6:22
their support throughout the year as, you know, we've gone through interesting market times, let's just
6:28
say, as a business ourselves. But at the same time, you know, really strongly, and it's
6:32
it's wonderful to see the understanding of the products that we've built among both the Australian
6:37
fund management community. And, obviously, we're we're listed in The US. Or across The US investors.
6:42
I spent a lot of time with European investors a month or two ago. I think
6:46
the attitude to really deep technologically driven, software companies in the AI era has changed because
6:53
the economics of software is still, still a fantastic business. All of this lets us deliver
6:58
customer value ever faster. And, again, we're accelerating as a business for that reason is because
7:03
of our investment in technology and, delivering for our customers, and it's really great to see
7:09
all the different, investment community around the world valuing that.
7:16
Right. That takes us quite nicely into what type and what's not. I mean, there have
7:22
been calls, you know, for us to slow down AI development. What's your take on that?
7:30
Look. From our point of view, we love model progress. As I would say at Allianz,
7:35
our job is to take model progress and harness it for our customers. Right? So we
7:39
are building in the in the software layer. We're building solutions for customers that take that
7:46
AI model progress and harness it for the value of the customer, solving the problems that
7:52
the customers have. So it's our job to blend different models over time. We have more
7:59
than 75 different models in production, to give the customers their own set of choices and
8:04
different, different values. In terms of us, model progress is a is a really great thing
8:09
because we can solve ever more problems. And as the models move forward, it's not just
8:14
the latest models. The more mature models, let's just say, in price is a really great
8:20
thing for us at the same time because as the world... The technology world shows up
8:24
to cost optimize older models, we can deliver ever increasing value, at at great prices for
8:31
our customers, which is really important, obviously, as the AI cost, AI capital management is a
8:36
concern for all customers. What the Teamwork Graph and the Atlassian platform does is literally lets
8:41
you reduce your token usage as it's, proportionally as it increases. So, some very significant savings
8:48
for our customers that are using the Teamwork Graph to access their knowledge from any of
8:51
those, AI harnesses that are out there.
8:59
Mike, talk to us about your expansion plans. We know that you have quite a big
9:04
operation here in India.
9:08
We do. Yes. Couple of thousand staff now in India. Just past 40 staff here in
9:13
Singapore and and hiring very strongly across the region. So, both Southeast Asia and then into
9:19
to Continental Asia and North Asia, all, big and very fast growing markets for us. Singapore,
9:25
where I am at the moment, happens to be one of our fastest growing markets in
9:28
the region. India is, one of our three big, offices. Again, staff are allowed to work
9:35
from many, many different countries. I think we have staff in probably 18 or 19 countries
9:38
around the world at the moment, and 26 out of the 27 states in India. We
9:44
have a big office in in Bangalore, but it's been a it's been a real success
9:47
story of Australian Indian cooperation. Obviously, the two countries work really closely together. We've had we've
9:54
had great success there growing in the Indian region. And, again, I would say we're there
9:59
for the talent. It's incredibly deep talent base. We do fundamental engineering, foundational development, a lot
10:00
for the talent. It's incredibly deep talent base. We do fundamental engineering, foundational development, a lot
10:05
things I've just spoken about are built out of the Indian office in collaboration with Australia
10:10
and with America. So we really do run a a twenty four seven engineering operation around
10:15
the world dealing with both the global customer base, but also finding the best talent wherever
10:20
we can find it. And India has has a lot of fantastic technical talent, so it's
10:23
been it's been a real success story for us. There, I was there just just last
10:27
month.
10:33
Mike, I wanna talk about the AI models. Increasingly, The US is asking the world to
10:38
choose within... You know, between their models and the Chinese models. You've come out to say
10:43
that perhaps, you know, enterprises will become more comfortable in using those AI models, likes of
10:48
DeepSeek. Pretty controversial statement to make at this point in time. What really are your thoughts
10:54
on it?
10:57
Look. I think we we do believe in customer choice. So I think customers are seeing
11:04
the value in AI. They're moving well beyond sort of prototypes and pilot programs to really
11:09
deeply embedding it into their business processes. We see that every single day. As they do
11:14
so, they have a new cost management exercise, right, in their business workflow teams, in their
11:20
technology teams. How do they manage the AI costs that are rising? Some have very strong
11:26
views on, where the models have come from. Others are more flexible, take it as a
11:31
vendor choice to blend different models. You always have care about data governance, permissioning, data sovereignty,
11:38
where things are running. That's absolutely a part of the concern. I think open wide models
11:42
broadly across the world are really picking up steam. We have a number of fine tuned
11:47
NeMotron models we use for specific things internally, is the NVIDIA model. We have a deep
11:51
partnership with NVIDIA, that's going really well. And so I think open wide models broadly are
11:56
growing. I think we have a question around where those models come from, and customer preferences
12:02
of that. We we see it shifting, slowly as it becomes a cost equation, and the
12:08
content of the open weight models is more understood. So, I think, look, we'll continue to
12:12
be customer led about that. I think for us, model progress, model competition is a great
12:19
thing because we can deliver better solutions for our customers at a better price, and and
12:24
more magical AI outcomes across the Atlassian platform. So we're just really excited by all the
12:29
model progress and competition that's happening to, increase quality and and bring prices down of, of
12:35
every token.
12:40
But, Mike, it is about compliance. It is about national security. What do you tell governments
12:47
and, you know, enterprise clients who are keeping away from the Chinese models because of these
12:53
concerns?
12:56
Look. I think it's totally their choice. There's nothing wrong with that as a choice. If
13:02
they understand the trade offs they're making, like any business decision, they're making a trade off
13:05
around costs, risks, absolutely compliance, data sovereignty, understanding the, where your data is being used as
13:15
a company, meeting all of the governance and compliance regulations of your country or your industry,
13:20
always incredibly important and top of mind for customers. Atlassian's job with those platforms is to
13:25
support all of those compliance res... Requirements, whether that's sovereignty and data residency in Europe. We
13:32
just shipped inference residency, for example, last week in our conference in Amsterdam. So the inference
13:37
on all of those latest frontier models for European customers now being rolled out to be
13:42
done in Europe, not being done in The US even if that data was living in
13:47
Europe. So I always think it's it's really important for customer choice to be there. I
13:51
think over time, the model blending is becoming more important... More and more important. You're seeing
13:56
a lot of models that are taking an open wide model, adjusting it, changing it, tuning
14:02
it, and rolling it out. So we have to be very careful about the stack of
14:04
technologies we have. Just as we do, I would say, in any any other areas. Right?
14:08
Where does your operating system come from and how has it been contributed to? Is it
14:12
open source or not open source, etcetera? So I think customers are making some very smart
14:16
choices. They're being very thoughtful. Having had some conversation with Singapore government here, exactly the same
14:22
thing. People are thinking ahead and trying to make really thoughtful choices. So I think it's
14:26
exciting to see how it will all, how it will all develop.
14:34
Definitely, it'll be exciting to see, interesting to see. Still, it is an AI race, an
14:39
AI war between The US and China. If you were to hazard a guess, who's likely
14:45
to win this race, and what would define success?
14:53
Look. I think, you know, coming from Australia, the global competition for building better models, the
15:00
Look. I think, you know, coming from Australia, the global competition for building better models, the
15:01
exchange of techniques, and the ability to push model progress forward is going to be a
15:07
competition for a fair while. We do have some European models. We have other people in
15:11
new places, constant innovations in in model building techniques, how they're trained, how they're optimized, how
15:20
they're distilled. A lot of things are happening at a pretty rapid pace. I think it's
15:25
probably, if you look back at the last two years, pretty naive to choose winners. I
15:31
don't think from a business perspective that needs to be the case. There are many ways
15:35
to harness the the collective of model progress. Most customers we have, certainly of a large
15:42
scale, have multiple models running internally. They're not choosing just one. They are choosing multiple models
15:49
often for different purposes. So I think we'll live in a multimodal world. There'd be many,
15:53
many models running inside most businesses, different cost profiles, different opportunities. Obviously, they need to think
15:58
about all the data and compliance of their own business needs. They'll have a handful of
16:03
harnesses, and I think they'll have probably a couple of large scale context graph provided to
16:07
all those harnesses and to all those models. So, again, I would say to any business
16:11
out there, just be excited by model progress and make sure you're being very thoughtful about
16:14
how you can harness that progress to get the best out of your processes and your
16:18
business.
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