What happens when two enterprise technology giants combine observability, automation, and AI to tackle one of the biggest challenges facing modern IT teams?
Recording live from the showfloor at Dynatrace Perform in Las Vegas, I caught up with Pablo Stern, EVP and GM of Technology Workflows at ServiceNow, to discuss how the company's expanding strategic partnership with Dynatrace is helping organizations move closer to autonomous IT operations.
For years, IT teams have been trapped in a cycle of alerts, escalations, war rooms, and lengthy root-cause investigations. But as AI matures and observability platforms become increasingly intelligent, a new model is emerging. One where systems can identify issues, understand their impact, recommend actions, and eventually resolve problems with minimal human intervention.
Pablo explains why the journey toward autonomous operations is less about replacing people and more about removing friction. We explore how ServiceNow workflows and Dynatrace observability work together to shorten the path from detection to resolution, helping organizations reduce downtime, improve service reliability, and create better experiences for both employees and customers.
The conversation also examines the realities behind concepts such as self-healing systems, intelligent automation, and agentic AI. Rather than focusing on futuristic promises, Pablo shares a practical view of how enterprises can build trust in automation one step at a time, starting with insights, progressing to guided actions, and eventually enabling autonomous outcomes where appropriate.
We also discuss why change management remains one of the biggest causes of outages, how AI can help organizations understand potential risks before changes are deployed, and why the next generation of IT operations will rely on stronger collaboration between platforms, people, and processes.
From customer expectations and operational resilience to the future role of IT teams, this episode offers a thoughtful look at how enterprise technology is evolving beyond monitoring and ticket management into something far more proactive and intelligent.
So as organizations push toward higher availability, faster resolution times, and increasingly complex digital environments, are we finally approaching a future where IT operations become truly autonomous?
00:00:00 --> 00:00:02 A huge thank you to Denodo for supporting the
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00:00:36 --> 00:00:43 .com. I'm coming to you live from Dynatrace Perform
00:00:43 --> 00:00:46 here in Las Vegas where the conversations on
00:00:46 --> 00:00:49 the show floor, they are moving fast and the
00:00:49 --> 00:00:52 expectations around AI automation and resilience
00:00:53 --> 00:00:56 They feel higher than ever. And this is where
00:00:56 --> 00:00:59 enterprise leaders, engineers and platform teams
00:00:59 --> 00:01:02 are all asking those hard questions about how
00:01:02 --> 00:01:06 IT actually needs to work in a world where downtime
00:01:06 --> 00:01:09 is no longer tolerated, all at the same time
00:01:09 --> 00:01:13 while complexity keeps piling up. So today we're
00:01:13 --> 00:01:14 going to go right into the heart of this challenge
00:01:14 --> 00:01:17 and I'm going to be joined by Pablo Stern. He's
00:01:17 --> 00:01:22 the EVP and GM of technology workflows at ServiceNow.
00:01:22 --> 00:01:25 We're recording today here at Dynatrace Perform
00:01:25 --> 00:01:28 just a couple of hours after he stepped off the
00:01:28 --> 00:01:31 main stage to talk about ServiceNow's deepening
00:01:31 --> 00:01:35 partnership with Dynatrace. So today we'll talk
00:01:35 --> 00:01:37 about that multi -year collaboration that was
00:01:37 --> 00:01:40 announced last year, what that means for enterprise
00:01:40 --> 00:01:43 IT teams and look beyond the headlines. Talk
00:01:43 --> 00:01:46 about observability and workflows, how they can
00:01:46 --> 00:01:49 come together to shorten the path from alert
00:01:49 --> 00:01:54 to action. and explore why autonomous IT operations
00:01:54 --> 00:01:58 have been so hard to move from theory into practice
00:01:58 --> 00:02:02 and where human judgment still matters as automation
00:02:02 --> 00:02:05 continues to scale. So, if you are responsible
00:02:05 --> 00:02:08 for IT operations, service management, security,
00:02:09 --> 00:02:12 reliability or business impact, which I hope
00:02:12 --> 00:02:14 would be most of you listening out there, today's
00:02:14 --> 00:02:17 conversation will help connect the dots between
00:02:17 --> 00:02:22 those AI ambitions and operational reality. So
00:02:22 --> 00:02:24 buckle up and hold on tight because I'm going
00:02:24 --> 00:02:26 to beam your ears all the way to the show floor
00:02:26 --> 00:02:29 conversation here in Las Vegas and hear directly
00:02:29 --> 00:02:32 from Pablo and why this partnership between ServiceNow
00:02:32 --> 00:02:36 and Dynatrace is focused on outcomes rather than
00:02:36 --> 00:02:41 hype So let's get him on now I think we're all
00:02:41 --> 00:02:43 welcome to the show. Can you tell everyone listening
00:02:43 --> 00:02:45 just a little about who you are and what you
00:02:45 --> 00:02:48 do? So, my name's Pablo Cern. I'm the EVP and
00:02:48 --> 00:02:52 GM of technology workloads at ServiceNow. And
00:02:52 --> 00:02:56 at ServiceNow, our mission really is to enable
00:02:56 --> 00:03:00 AI, make it work for people. And in my role,
00:03:01 --> 00:03:05 I really focus on two core archetype personas,
00:03:05 --> 00:03:09 the CIO and the CSO. And what my team does is,
00:03:09 --> 00:03:13 We build technology for CIO in their organization
00:03:13 --> 00:03:16 and for the CISO in their organization. So security,
00:03:16 --> 00:03:20 risk products, products for like service desk,
00:03:20 --> 00:03:23 the command center, asset teams and others, like
00:03:23 --> 00:03:25 we ultimately build them. We try to bring them
00:03:25 --> 00:03:28 all together. And we're recording this at Dye
00:03:28 --> 00:03:30 and the Trace perform in Vegas. You were on stage
00:03:30 --> 00:03:33 this morning talking about your partnership or
00:03:33 --> 00:03:35 ServiceNow's partnership with Dye and the Trace,
00:03:35 --> 00:03:38 which started last year, deepened your strategic
00:03:38 --> 00:03:42 collaboration to advanced autonomous IT operations.
00:03:42 --> 00:03:44 But for listeners who might not have followed
00:03:44 --> 00:03:46 that announcement closely, because it was right
00:03:46 --> 00:03:48 in the heart of event season, so much going on.
00:03:48 --> 00:03:51 Tell me a little bit more about it. What problem
00:03:51 --> 00:03:54 were ServiceNow and Dynatrace hoping to solve
00:03:54 --> 00:03:57 together in enterprise IT that made a deeper
00:03:57 --> 00:03:59 multi -year partnership so necessary? Tell me
00:03:59 --> 00:04:02 about it. It's a great question. I've been at
00:04:02 --> 00:04:05 ServiceNow for almost 10 years and we've been
00:04:05 --> 00:04:08 partnering with Dynatrace basically since I joined.
00:04:09 --> 00:04:12 So this is a long standing partnership and I
00:04:12 --> 00:04:14 will always start by saying the partnerships
00:04:14 --> 00:04:17 that matter always start with the customer. So
00:04:17 --> 00:04:19 the starting point for me on anything is, can
00:04:19 --> 00:04:21 we solve a joint customer problem? Can we deliver
00:04:21 --> 00:04:24 on that promise? And if we can, and if our customers
00:04:24 --> 00:04:27 are asking for it, let's go focus on it. And
00:04:27 --> 00:04:30 so, you know, we've had a strong partnership,
00:04:30 --> 00:04:34 a lot of joint customers integrating with our
00:04:34 --> 00:04:37 ServiceNow ITOM, AIOps capabilities, and the
00:04:37 --> 00:04:41 Dynatrace platform for a long time now. But I
00:04:41 --> 00:04:43 think one of the things that's changing in the
00:04:43 --> 00:04:47 last few years as the technology landscape is
00:04:47 --> 00:04:49 really shifting and the underpinnings of how
00:04:49 --> 00:04:51 we deliver technology is really transforming.
00:04:52 --> 00:04:55 There's a brand new opportunity to deliver value
00:04:55 --> 00:04:58 to customers. And what we've seen in the last
00:04:58 --> 00:05:00 few years is a lot of the building blocks have
00:05:00 --> 00:05:04 been coming to bear in a technology market. And
00:05:04 --> 00:05:07 for us at ServiceNow, and especially as we think
00:05:07 --> 00:05:10 about outcomes with our joint customers in Dynatrace,
00:05:11 --> 00:05:13 we see that these building blocks can actually
00:05:13 --> 00:05:15 enable our customers to do things that they could
00:05:15 --> 00:05:19 never do in the past. And so this idea of an
00:05:19 --> 00:05:21 autonomous future, autonomous IT, autonomous
00:05:21 --> 00:05:25 operations is really driven on a very simple
00:05:25 --> 00:05:28 notion for me, which is if you think about the
00:05:28 --> 00:05:32 evolution of AI in the last few years, we went
00:05:32 --> 00:05:36 from a world where AI was really accelerating
00:05:36 --> 00:05:39 insight. You could summarize something, you could
00:05:39 --> 00:05:42 create a poem, you could draft a knowledge article,
00:05:42 --> 00:05:48 you could take mountains of data and get to some
00:05:48 --> 00:05:51 key insights. And that was a necessary building
00:05:51 --> 00:05:54 block. And then over the past couple of years,
00:05:54 --> 00:05:57 we started then layering action on top of that.
00:05:57 --> 00:06:00 Driving workflows, being able to do tasks. I'm
00:06:00 --> 00:06:03 going to post that knowledge article, or I'm
00:06:03 --> 00:06:07 going to write a communication. And that was
00:06:07 --> 00:06:09 a second step in the journey. And what really
00:06:09 --> 00:06:12 excites me as we think about where we're going
00:06:12 --> 00:06:15 with Dynatrace is the next step is you take those
00:06:15 --> 00:06:17 building blocks, you take all the data that exists,
00:06:17 --> 00:06:19 you can derive data from, you take these playbooks
00:06:19 --> 00:06:21 and these actions that you could then drive the
00:06:21 --> 00:06:23 deterministic view of what's happening in environments,
00:06:24 --> 00:06:26 and you connect those. And then you start enabling
00:06:26 --> 00:06:30 the technology to be able to autonomously drive
00:06:30 --> 00:06:32 end -to -end action. So you're no longer going
00:06:32 --> 00:06:34 from like a single task, you're actually driving
00:06:34 --> 00:06:37 system level actions. And the only way that you
00:06:37 --> 00:06:40 can actually do that is by connecting the ecosystem
00:06:40 --> 00:06:44 of different technologies. And we have so many
00:06:44 --> 00:06:46 joint customers that really want those outcomes.
00:06:46 --> 00:06:49 They're looking for, how can we get to a world
00:06:49 --> 00:06:53 with no outages? How can we reduce our time to
00:06:53 --> 00:06:55 resolve issues? How can we get better adherence
00:06:55 --> 00:06:59 to our SLAs? Those are common asks of our customers.
00:06:59 --> 00:07:01 And we know that together we can actually build
00:07:01 --> 00:07:04 that for customers. I think when many listeners
00:07:04 --> 00:07:07 and many organizations, they often talk about
00:07:07 --> 00:07:10 autonomous IT operations, but struggle to move
00:07:10 --> 00:07:13 beyond theory. So in practical terms, how does
00:07:13 --> 00:07:17 combining Dynatrace, observability, and ServiceNow
00:07:17 --> 00:07:19 workflows, how does that change how incidents
00:07:19 --> 00:07:22 are detected, understood, and ultimately received
00:07:22 --> 00:07:25 every single day? Tell me more about that. I
00:07:25 --> 00:07:27 think that there's, as I mentioned, like a few
00:07:27 --> 00:07:30 building blocks that even if you take AI out
00:07:30 --> 00:07:33 of the picture, are necessary. And those are
00:07:33 --> 00:07:36 actions that our customers are taking today and
00:07:36 --> 00:07:39 are going to build and have a virtuous cycle
00:07:39 --> 00:07:42 as we start gentifying. So as an example, in
00:07:42 --> 00:07:45 the ServiceNow world, having prescriptive workflows,
00:07:46 --> 00:07:48 which are going to be very neat to an organization,
00:07:49 --> 00:07:51 will help you drive relief, will help you get
00:07:51 --> 00:07:54 to resolution faster. So it could be about who
00:07:54 --> 00:07:56 do you page how do you get to them and making
00:07:56 --> 00:07:57 sure the right people are on the call it could
00:07:57 --> 00:08:02 be about failing something over or removing storage
00:08:02 --> 00:08:05 like full space on your disk there are a lot
00:08:05 --> 00:08:08 of different actions that can be taken now if
00:08:08 --> 00:08:10 you if you take those building blocks and then
00:08:10 --> 00:08:14 you go on the dyna trace platform from an ai
00:08:14 --> 00:08:17 -powered observability perspective and then you
00:08:17 --> 00:08:20 can actually deterministically say this is what's
00:08:20 --> 00:08:23 happening in an environment, like go really understand
00:08:23 --> 00:08:25 what is happening that gives you confidence and
00:08:25 --> 00:08:28 trust. You can then start connecting these two
00:08:28 --> 00:08:31 use cases and trusting a machine to take them.
00:08:31 --> 00:08:33 And I think that that is the unlock that we're
00:08:33 --> 00:08:37 working towards, which is nobody out of the gate
00:08:37 --> 00:08:40 is gonna say, I'm gonna trust a machine to fail
00:08:40 --> 00:08:44 over my P1 production system to something else
00:08:44 --> 00:08:46 if it has some inkling that there's a problem.
00:08:47 --> 00:08:51 it'll probably take the insight and it'd be happy
00:08:51 --> 00:08:53 to then run a deterministic playbook if somebody
00:08:53 --> 00:08:57 was willing to go and approve that change. But
00:08:57 --> 00:08:59 those different pieces over time, I think will
00:08:59 --> 00:09:02 become more automated. And the connective tissue
00:09:02 --> 00:09:06 for me is today the world often in the standard
00:09:06 --> 00:09:09 of practice is not fully digitized and 10. So
00:09:09 --> 00:09:12 there's your plane telephone across multiple
00:09:12 --> 00:09:14 people, their manual steps, there's tribal knowledge.
00:09:15 --> 00:09:17 All those pieces create friction that an agentic
00:09:17 --> 00:09:20 system won't be able to go and drive. So if you
00:09:20 --> 00:09:23 can digitize that entire process, even if you're
00:09:23 --> 00:09:25 trusting the human along the way for each of
00:09:25 --> 00:09:29 the steps, over time, you'll be able to trust
00:09:29 --> 00:09:32 machines to take some of those steps or to elevate
00:09:32 --> 00:09:35 to a human who will then approve. And that's,
00:09:35 --> 00:09:36 I think, the world that we're building towards.
00:09:37 --> 00:09:39 But those foundational pieces that I talked about
00:09:39 --> 00:09:42 are the necessary components. There's enough
00:09:42 --> 00:09:45 technology now in place to be able to build those
00:09:45 --> 00:09:49 and to give enough insight and enough of a breadcrumb
00:09:49 --> 00:09:52 to actually start taking those actions. And root
00:09:52 --> 00:09:55 cause analysis, that's still one of the biggest
00:09:55 --> 00:09:58 time drains for IT teams. And if you can share
00:09:58 --> 00:10:01 on how automation between the platforms here
00:10:01 --> 00:10:04 shortens the path from alert to action and where
00:10:04 --> 00:10:07 human judgment still plays a role. Anything you
00:10:07 --> 00:10:09 can add to that? Yes. So I'll give an example
00:10:09 --> 00:10:12 of this. of a place where we're partnering with
00:10:12 --> 00:10:14 Dying Trace and how I think that can help sort
00:10:14 --> 00:10:19 of produce mean time to resolve. So, look at
00:10:19 --> 00:10:23 a world in which an event comes in. Now, there
00:10:23 --> 00:10:25 are tons of alerts, tons of events coming to
00:10:25 --> 00:10:27 the system, and you're trying to figure out and
00:10:27 --> 00:10:30 prioritize and understand what's happening in
00:10:30 --> 00:10:33 those events. And so, in a world where you're
00:10:33 --> 00:10:36 not waiting on a human to go and sort of triage
00:10:36 --> 00:10:38 through the list or prioritize them or drive
00:10:38 --> 00:10:42 correlation, but an agentic system can then go
00:10:42 --> 00:10:46 and do additional forensics, go from ServiceNow
00:10:46 --> 00:10:49 and query into Dynatrace, and then try to look
00:10:49 --> 00:10:53 at what is happening, understand what the root
00:10:53 --> 00:10:56 cause of that event is, potentially understand
00:10:56 --> 00:10:58 what the blast radius, what's impacted, right?
00:10:58 --> 00:11:02 Try to assess both priority, impact, and potentially
00:11:02 --> 00:11:06 source. You then start... removing potentially
00:11:06 --> 00:11:09 some of those multi -step processes that we hear
00:11:09 --> 00:11:11 often about where people are on a major incident
00:11:11 --> 00:11:14 bridge and every team is like, it's not me, it's
00:11:14 --> 00:11:17 not me, and then you spend the first hour just
00:11:17 --> 00:11:21 trying to figure out where the cause is, and
00:11:21 --> 00:11:23 you can potentially shorten that cycle time by
00:11:23 --> 00:11:26 doing some of that work ahead of time. And again,
00:11:27 --> 00:11:29 will it happen and solve it every time? No, it
00:11:29 --> 00:11:32 won't, but if you can... either reduce the amount
00:11:32 --> 00:11:35 of time it takes to do the analysis and the forensics,
00:11:35 --> 00:11:39 if you can be right 20, 30 % of the time, you
00:11:39 --> 00:11:43 can save hours of time in that diagnostic. And
00:11:43 --> 00:11:46 even in a world where like a lot of those steps
00:11:46 --> 00:11:49 are still taken by humans or relief, even the
00:11:49 --> 00:11:53 resolution pieces are done by humans, you can
00:11:53 --> 00:11:55 reduce the time that somebody sees an impactful
00:11:55 --> 00:11:58 event pretty dramatically. And so that's how
00:11:58 --> 00:12:02 we think about it. And that's a place where partnership
00:12:02 --> 00:12:05 between ServiceNow and Dynatrace, we can actually
00:12:05 --> 00:12:06 deliver some of those outcomes and bring the
00:12:06 --> 00:12:08 best of the Dynatrace platform, the best of the
00:12:08 --> 00:12:12 ServiceNow platform to get to faster resolution.
00:12:12 --> 00:12:16 And self -healing systems sound incredibly compelling.
00:12:16 --> 00:12:18 Almost remind me of the Christine movie all those
00:12:18 --> 00:12:22 years ago, but it can also feel risky to enterprise
00:12:22 --> 00:12:24 leaders. So what safeguards or design principles
00:12:24 --> 00:12:28 are essential to maintaining that trust in automation
00:12:28 --> 00:12:32 remediated at scale? Yeah. I'll say that I think
00:12:32 --> 00:12:37 like truly like full self -healing systems, like
00:12:37 --> 00:12:40 that's That's a ways away. Like we'll build towards
00:12:40 --> 00:12:42 it, but it'll take some time. What I think we're
00:12:42 --> 00:12:47 going to see is first relief. So I think as,
00:12:47 --> 00:12:51 and trust is such a big part of this. Like you
00:12:51 --> 00:12:54 may trust a system to do a fail over because
00:12:54 --> 00:12:56 you're already doing some of those fails fail
00:12:56 --> 00:12:58 over load balancer. You know, if they're like,
00:12:58 --> 00:13:00 there's a bunch of things that you could do.
00:13:00 --> 00:13:04 And oftentimes a lot of those are actually scripted,
00:13:04 --> 00:13:06 uh, outcomes that are delivered. They're just
00:13:06 --> 00:13:09 triggered by a human. So there's, there's a lot
00:13:09 --> 00:13:13 of places where the machine can then say, this
00:13:13 --> 00:13:15 is a suggested outcome. You still do the steps
00:13:15 --> 00:13:18 by a human. And so what, what I think we're going
00:13:18 --> 00:13:21 to see is you'll see a little bit more of that
00:13:21 --> 00:13:23 type of stuff. And I'll call it the low hanging
00:13:23 --> 00:13:27 fruit and it's around relief. Like, Hey, Not
00:13:27 --> 00:13:30 yet. Like I'm actually going to figure out where
00:13:30 --> 00:13:33 in the code, the issue is back out the change,
00:13:33 --> 00:13:35 redeploy the change, get it all done into production
00:13:35 --> 00:13:38 and push it out, do that all autonomously. Like
00:13:38 --> 00:13:41 that future future that you'll build towards,
00:13:41 --> 00:13:44 but you know, is not like the future that you're
00:13:44 --> 00:13:46 going to see in the next six months. Um, but
00:13:46 --> 00:13:49 you can say, well, let me first just give relief
00:13:49 --> 00:13:51 so that like we get back up and running, and
00:13:51 --> 00:13:53 then the team's going to do the diagnostic and
00:13:53 --> 00:13:56 somebody is going to. for sure be spending time
00:13:56 --> 00:13:58 working on like, can we drive more autonomy in
00:13:58 --> 00:14:02 those higher level outcomes? But I think that
00:14:02 --> 00:14:04 that is, that's a destination of future. And
00:14:04 --> 00:14:07 I think of, you know, the AI world is like a
00:14:07 --> 00:14:10 generational change. Like this journey is not
00:14:10 --> 00:14:12 going to be done in a year or two. Like it will
00:14:12 --> 00:14:15 be decades in the journey driving change, much
00:14:15 --> 00:14:17 like we are with cloud. Now we're going to make
00:14:17 --> 00:14:19 tremendous amounts of progress in the next few
00:14:19 --> 00:14:21 years. I think it's going to, it'll change how
00:14:21 --> 00:14:25 we work, but I also recognize that these changes
00:14:25 --> 00:14:28 take a long time, and it's not just the technology,
00:14:29 --> 00:14:30 it's the people in process also that have to
00:14:30 --> 00:14:33 come along for the ride. Do you think we'll have
00:14:33 --> 00:14:36 an AI member like Virtual Rick, AI Rick, attending
00:14:36 --> 00:14:39 the Change Advisory Board in a few years, do
00:14:39 --> 00:14:44 you think, maybe? I know we will. Yeah. We will
00:14:44 --> 00:14:48 have... They may not look like Rick, but I can
00:14:48 --> 00:14:50 tell you that we will have members of Change
00:14:50 --> 00:14:53 Advisory Board that are digital that are helping
00:14:53 --> 00:14:57 get to those changes. I can guarantee it. And
00:14:57 --> 00:15:01 here at Dynatrace Perform, you've been referencing
00:15:01 --> 00:15:04 heavily agentic AI and intelligent automation.
00:15:04 --> 00:15:07 How do you distinguish meaningful autonomy from
00:15:07 --> 00:15:10 simple task automation? And why does that distinction
00:15:10 --> 00:15:13 matter for IT and service management teams? Yeah,
00:15:13 --> 00:15:15 I think it's a super critical one and I think
00:15:15 --> 00:15:18 it's, I think that distinction is how I see the
00:15:18 --> 00:15:22 evolution of the autonomous world. Like the three
00:15:22 --> 00:15:26 layers are, I refer to it as step one of the
00:15:26 --> 00:15:32 maturity journey from like 22 to like 2023, 24
00:15:32 --> 00:15:37 was around insight. and just getting those, you
00:15:37 --> 00:15:39 know, the needles in the haystack and understanding
00:15:39 --> 00:15:41 what it was. And it could be a summary of an
00:15:41 --> 00:15:43 issue. It could be bringing together knowledge.
00:15:43 --> 00:15:46 It could be enabling a team, but often like for
00:15:46 --> 00:15:49 human loop activities. That was step one. Step
00:15:49 --> 00:15:52 two was tying that to the action. And that's
00:15:52 --> 00:15:55 where those task automations came in. Like, hey,
00:15:55 --> 00:15:59 I can provide relief by failing overload balancer.
00:15:59 --> 00:16:02 I can page a team and take an action that brings
00:16:02 --> 00:16:05 the right people onto the call. In each of those
00:16:05 --> 00:16:08 building blocks, I often will refer to as like,
00:16:08 --> 00:16:12 that was the agentic world. Those are the agentified
00:16:12 --> 00:16:16 tasks. Like you have an agent that does task
00:16:16 --> 00:16:18 routing. You have an agent that drafts resolution
00:16:18 --> 00:16:23 notes or creates a KB article. And step three
00:16:23 --> 00:16:27 in that journey is where you end up driving the
00:16:27 --> 00:16:30 autonomy. And what that looks like is you take
00:16:30 --> 00:16:33 a lot of those agentic outcomes that are really
00:16:33 --> 00:16:36 tasks, and you make them a system, and you make
00:16:36 --> 00:16:39 them a system that can actually complete a job
00:16:39 --> 00:16:43 to be done. And that system leverages all the
00:16:43 --> 00:16:45 insight layer, which we will refer to as skills,
00:16:45 --> 00:16:48 the agentic layer, which are some of those tasks
00:16:48 --> 00:16:52 on top of the skills, and then drive the autonomous
00:16:52 --> 00:16:55 outcome. So we're building towards that. Third
00:16:55 --> 00:16:57 stage, I would say even in the second stage of
00:16:57 --> 00:17:00 that journey, the automation, there's a lot of
00:17:00 --> 00:17:02 work to be done by us and by our customers to
00:17:02 --> 00:17:04 put all those pieces in place. But these are
00:17:04 --> 00:17:07 obviously necessary building blocks. And watching
00:17:07 --> 00:17:10 you on stage today with Dynatrace and ServiceNow,
00:17:11 --> 00:17:13 it seemed to me from the audience point of view,
00:17:13 --> 00:17:15 of course, and me sat there, is it's not just
00:17:15 --> 00:17:18 a technical partnership, but operational too,
00:17:18 --> 00:17:20 and both companies using each other's platforms
00:17:20 --> 00:17:23 internally. So what insights have you gained
00:17:23 --> 00:17:25 from being customers of each other and how has
00:17:25 --> 00:17:27 that helped shape your joint roadmap, maybe?
00:17:27 --> 00:17:32 Yeah, I often say our internal customer. So ServiceNow's
00:17:32 --> 00:17:35 digital technology team, that's our IT organization.
00:17:35 --> 00:17:39 is our best and toughest customer. They push
00:17:39 --> 00:17:42 us the hardest. They take our products before
00:17:42 --> 00:17:44 they're baked. They give us a lot of feedback
00:17:44 --> 00:17:47 around what's working and what's not. They don't
00:17:47 --> 00:17:51 pull any punches. And they ultimately have the
00:17:51 --> 00:17:53 same interests in mind. They want ServiceNow
00:17:53 --> 00:17:55 to be successful and they will challenge us and
00:17:55 --> 00:17:58 they will tell us and they will not hold back
00:17:58 --> 00:18:01 on it. And so for me, that's super important
00:18:01 --> 00:18:04 because They will always take our technology
00:18:04 --> 00:18:08 before we bring it out to customers. And so they
00:18:08 --> 00:18:11 really represent like the first pass of delivering
00:18:11 --> 00:18:14 really quality outcomes. So in a partnership
00:18:14 --> 00:18:17 like Nine Traces, the fact that our internal
00:18:17 --> 00:18:21 organization is using both technologies gives
00:18:21 --> 00:18:25 us a direct line to people within the company.
00:18:25 --> 00:18:27 that we can partner with to make sure that the
00:18:27 --> 00:18:30 outcomes are actually being delivered. And if
00:18:30 --> 00:18:32 they're not, we can hear from them directly.
00:18:32 --> 00:18:34 And so it's incredibly powerful. The fact that
00:18:34 --> 00:18:36 we do this internally, the fact that DynTrace
00:18:36 --> 00:18:38 is doing the same thing will deliver outcomes
00:18:38 --> 00:18:40 because every organization is different. They'll
00:18:40 --> 00:18:42 find some things we won't find. We'll find some
00:18:42 --> 00:18:44 things that they won't find, but it'll help us
00:18:44 --> 00:18:48 build. And I see this also recognizing that we
00:18:48 --> 00:18:50 have a bunch of customers who are design partners
00:18:50 --> 00:18:52 who are working also in parallel early. So...
00:18:52 --> 00:18:55 You want to have as many of these as possible
00:18:55 --> 00:18:57 to understand what the differences in requirements
00:18:57 --> 00:19:01 and environments, but our internal teams using
00:19:01 --> 00:19:04 this is one of the best canaries in the coal
00:19:04 --> 00:19:07 mine for the technology working. And if we zoom
00:19:07 --> 00:19:10 out a little from an industry perspective, what
00:19:10 --> 00:19:12 are the common operational challenges that you're
00:19:12 --> 00:19:16 seeing across enterprises right now that traditional
00:19:16 --> 00:19:20 ITSM and ITOM approaches are no longer equipped
00:19:20 --> 00:19:21 to handle alone because it feels like there's
00:19:21 --> 00:19:24 a lot of changes going on at the moment. Yeah.
00:19:24 --> 00:19:26 So I'll say something that I've seen that's been
00:19:26 --> 00:19:29 pretty interesting to see, which is If you think
00:19:29 --> 00:19:31 about the outcomes an organization is trying
00:19:31 --> 00:19:35 to drive, you talk to a CIO or CHRO or chief
00:19:35 --> 00:19:38 customer officer, all of which use ServiceNow
00:19:38 --> 00:19:41 technology or may not even, maybe prospect customers.
00:19:42 --> 00:19:44 The outcomes that we hear that they're seeking
00:19:44 --> 00:19:49 are not different. There are accelerations that
00:19:49 --> 00:19:51 they're expecting, but the outcomes aren't different.
00:19:51 --> 00:19:54 So as an example, like a service desk. In the
00:19:54 --> 00:19:57 service desk, they're expecting that they can
00:19:57 --> 00:20:00 take any questions that are coming in from employees,
00:20:00 --> 00:20:03 be able to handle them, route them, and get the
00:20:03 --> 00:20:05 employee on with their day, working on the stuff
00:20:05 --> 00:20:07 that they need to do their job, not an IT ticket
00:20:07 --> 00:20:11 or an HR ticket or whatnot. Now that said, what
00:20:11 --> 00:20:13 we're hearing from customers is like, we want
00:20:13 --> 00:20:17 to do that, but now with AI, we want to really
00:20:17 --> 00:20:19 rethink how we can deliver that outcome. We can
00:20:19 --> 00:20:22 deliver that outcome more efficiently, with a
00:20:22 --> 00:20:25 better experience, higher CSAT. And so really
00:20:25 --> 00:20:29 the outcome in and of itself, is still a similar
00:20:29 --> 00:20:30 outcome, whether it's a service task, whether
00:20:30 --> 00:20:32 it's command center, whether it's your asset
00:20:32 --> 00:20:34 management team, whether it's the EPMO or the
00:20:34 --> 00:20:37 PMO team that's working on your planning. But
00:20:37 --> 00:20:41 the how is what's ultimately changing and that
00:20:41 --> 00:20:45 how is meant to deliver the outcome more quickly,
00:20:45 --> 00:20:47 more efficiently with a better experience. And
00:20:47 --> 00:20:51 that's the journey that we are all on. And so
00:20:51 --> 00:20:54 for us at ServiceNow, that does require us re
00:20:54 --> 00:20:57 -imagining the how of how we build the technology.
00:20:57 --> 00:21:01 We are not in a mindset of incrementalism to
00:21:01 --> 00:21:05 build AI just on top of what we have and assume
00:21:05 --> 00:21:07 that's going to be the answer. We really are
00:21:07 --> 00:21:10 looking at if we want to deliver a 10x value
00:21:10 --> 00:21:15 prop expansion, how does AI deliver that? What
00:21:15 --> 00:21:17 is the experience that we need to do? How do
00:21:17 --> 00:21:20 we leverage the pieces that we have, the system
00:21:20 --> 00:21:24 of record, our workflows to go drive it? but
00:21:24 --> 00:21:26 make sure that we are also reinventing how we
00:21:26 --> 00:21:28 deliver that outcome. The good news with ServiceNow
00:21:28 --> 00:21:32 is we've done probably over a dozen AI acquisitions
00:21:32 --> 00:21:37 in the last eight years. A lot of it came from
00:21:37 --> 00:21:40 brainchilds of early research in LLMs and models.
00:21:40 --> 00:21:42 So we've been spending a lot of time. We also
00:21:42 --> 00:21:45 have a lot of feedback from customers. But it
00:21:45 --> 00:21:47 is a journey that we're building towards. And
00:21:47 --> 00:21:50 again, I think the outcomes are clear -known.
00:21:50 --> 00:21:52 The fact that we want to do them 10 times better
00:21:52 --> 00:21:55 is what we are spending a lot of time internally
00:21:55 --> 00:21:58 to work and reimagine how we deliver it. And
00:21:58 --> 00:22:00 if I was to ask you to look into my virtual crystal
00:22:00 --> 00:22:03 ball, look ahead, assuming organizations and
00:22:03 --> 00:22:06 leaders listening get this right, what changes
00:22:06 --> 00:22:08 should listeners expect to see in the role of
00:22:08 --> 00:22:12 IT teams right in their own experiences across
00:22:12 --> 00:22:14 corporate America over the next few years, especially
00:22:14 --> 00:22:17 as operations become more autonomous, they become
00:22:17 --> 00:22:20 more resilient. What should they be seeing? How
00:22:20 --> 00:22:22 can they measure those improvements? Yeah. We
00:22:22 --> 00:22:25 started this conversation around customers. And
00:22:25 --> 00:22:28 so I always come back to the customer. And being
00:22:28 --> 00:22:30 here at the conference today, I've run into probably
00:22:30 --> 00:22:33 a half dozen customers that I've known on the
00:22:33 --> 00:22:36 ServiceNow side who are here at Dynatrace Perform.
00:22:36 --> 00:22:39 And I often think, how do we make our customers
00:22:39 --> 00:22:42 successful? That, to me, is our mission. We are
00:22:42 --> 00:22:43 building technology, but technology with the
00:22:43 --> 00:22:46 purpose of making our customers successful. our
00:22:46 --> 00:22:49 customers to use ServiceNow, to use Dynatrace,
00:22:50 --> 00:22:53 to use our technologies in seeking an outcome
00:22:53 --> 00:22:56 and being able to deliver that and be able to
00:22:56 --> 00:22:58 be successful for their organization, for their
00:22:58 --> 00:23:03 customers' customers. And so, in that vein, as
00:23:03 --> 00:23:05 I think about, like, everything that we're doing,
00:23:06 --> 00:23:08 I come back to, like, for everybody who was in
00:23:08 --> 00:23:11 the audience today, and, you know, we asked folks
00:23:11 --> 00:23:13 to raise their hand if they were a ServiceNow
00:23:13 --> 00:23:16 customer in Dynatrace's audience, and... there's
00:23:16 --> 00:23:18 probably three quarters of the audience with
00:23:18 --> 00:23:20 ServiceNow customer and Dynatrace customer. What
00:23:20 --> 00:23:23 we really look to do is they're going to have
00:23:23 --> 00:23:26 really high expectations of what AI can deliver
00:23:26 --> 00:23:30 and those outcomes will translate to higher SLAs,
00:23:31 --> 00:23:33 delivering more efficiently, reducing time to
00:23:33 --> 00:23:36 resolve issues, shifting left and being able
00:23:36 --> 00:23:38 to find things before they ever hit environments.
00:23:38 --> 00:23:40 And so our mission is to be able to deliver those
00:23:40 --> 00:23:43 and then the measurements around that mission.
00:23:43 --> 00:23:47 I don't think that they necessarily change. MTTR,
00:23:48 --> 00:23:51 SLOs, SLAs, what are you driving in your air
00:23:51 --> 00:23:53 budgets? Those will continue to be them, but
00:23:53 --> 00:23:56 the bar is higher in terms of what those things
00:23:56 --> 00:24:00 are. Your SLAs are going to increase, your availability
00:24:00 --> 00:24:02 time needs to be higher. All those things need
00:24:02 --> 00:24:05 to happen in order to deliver the outcome. So
00:24:05 --> 00:24:07 I think that's where we're going to see the evolution.
00:24:08 --> 00:24:11 it's our job to deliver on the how so that out
00:24:11 --> 00:24:13 of the box the technology helps enable that.
00:24:14 --> 00:24:16 And some of these can be really critical and
00:24:16 --> 00:24:20 those is the technology pieces fit into both
00:24:20 --> 00:24:22 the organizational change that needs to happen
00:24:22 --> 00:24:24 and the process evolution that needs to happen
00:24:24 --> 00:24:27 at the customer in order to deliver on that promise.
00:24:27 --> 00:24:29 And one of the things I think that stands out
00:24:29 --> 00:24:32 at Dynatrace performing in fact every tech conference
00:24:32 --> 00:24:34 I go to is the power of the community there those
00:24:34 --> 00:24:38 conversations that you have not just with customers
00:24:38 --> 00:24:40 but with partners and also random people on the
00:24:40 --> 00:24:41 show floor that you would never be in the same
00:24:41 --> 00:24:44 room as I'm curious I know it's only day one
00:24:44 --> 00:24:46 that we're recording this but from all the conversations
00:24:46 --> 00:24:48 you had any themes anything that's got you thinking
00:24:48 --> 00:24:50 that you'll be thinking about on that flight
00:24:50 --> 00:24:52 home? Yeah absolutely and this is why I love
00:24:52 --> 00:24:54 these conferences because I'm spending a lot
00:24:54 --> 00:24:58 of time with join customers. I'll say a couple
00:24:58 --> 00:25:00 of things that came out like we were talking
00:25:00 --> 00:25:04 to a customer bank after the session and I'd
00:25:04 --> 00:25:07 mentioned this concept on stage around a preflight
00:25:07 --> 00:25:11 check. The idea that because a lot of our customers
00:25:11 --> 00:25:15 use service now for change and because change
00:25:15 --> 00:25:17 is often the leading cause of issues and outages
00:25:17 --> 00:25:21 in your environment. If we could help. through
00:25:21 --> 00:25:24 ServiceNow and DynaTrace, shift left and bring,
00:25:25 --> 00:25:27 as part of the change process, understanding
00:25:27 --> 00:25:30 of what the blast radius of potential impact
00:25:30 --> 00:25:33 of that change is, a risk assessment, and actually
00:25:33 --> 00:25:37 filter that in earlier on. We can actually start
00:25:37 --> 00:25:40 potentially reducing the number of outages or
00:25:40 --> 00:25:42 at least putting those checks and approvals in
00:25:42 --> 00:25:45 the hands of a team that can actually go and
00:25:45 --> 00:25:50 really make an informed decision. This bank customer
00:25:50 --> 00:25:52 came to me and said, we're trying to build this
00:25:52 --> 00:25:55 ourselves right now. Like we're weird between
00:25:55 --> 00:25:57 service and we're pulling stuff out of the system
00:25:57 --> 00:26:00 and we're doing like our own, but like they're
00:26:00 --> 00:26:04 trying to do that. And so for me as a technologist,
00:26:04 --> 00:26:06 I want to deliver that out of the box. I want
00:26:06 --> 00:26:09 to, I want to partner with this bank and I actually
00:26:09 --> 00:26:12 want to build that outcome together. And that's
00:26:12 --> 00:26:15 super powerful for me. And again, coming back
00:26:15 --> 00:26:17 to what I said around customers, like if we do
00:26:17 --> 00:26:20 our job, right. we're helping solve for our customers.
00:26:20 --> 00:26:22 And that customer would say, you're giving this,
00:26:23 --> 00:26:24 you and DynTrace are giving this to me out of
00:26:24 --> 00:26:27 the box. I have the outcome. So I've had a couple
00:26:27 --> 00:26:29 of those conversations around the future pieces.
00:26:30 --> 00:26:32 And the other thing I will say, every customer
00:26:32 --> 00:26:36 I spoke to raised their hand and was like, like,
00:26:36 --> 00:26:38 sign me up for design partnership. We will do
00:26:38 --> 00:26:40 this together. Like we want to partner with you.
00:26:40 --> 00:26:43 We're building this future together. And we think
00:26:43 --> 00:26:46 that between ServiceNow, DynTrace and us, we
00:26:46 --> 00:26:49 can do this. So I, that's super reassuring because
00:26:49 --> 00:26:50 it tells me that there is a there there. The
00:26:50 --> 00:26:52 customers actually want this. I think that's
00:26:52 --> 00:26:54 a powerful moment to end on, but before I let
00:26:54 --> 00:26:56 you go, anyone listening want to find out more
00:26:56 --> 00:26:58 information, keep up to speed with announcements
00:26:58 --> 00:27:00 from ServiceNow, et cetera. Any way you'd like
00:27:00 --> 00:27:04 to point everyone? Yeah. So I'll say a couple
00:27:04 --> 00:27:06 of things. If you're a, if you're a ServiceNow
00:27:06 --> 00:27:09 customer, reach out to your sales team. Like
00:27:09 --> 00:27:12 my team works really closely with our sales or
00:27:12 --> 00:27:16 pre -sales or other teams. Like, like they have
00:27:16 --> 00:27:18 all our enablement around. where we are, where
00:27:18 --> 00:27:21 the roadmaps are. I would encourage ServiceNow
00:27:21 --> 00:27:24 customers, our user conferences, and then world
00:27:24 --> 00:27:27 forums, which are in -site day or two day long
00:27:27 --> 00:27:31 events, like bring a lot of content. And if you
00:27:31 --> 00:27:34 are a customer, you should make sure that you're
00:27:34 --> 00:27:36 using our briefings because that's how you get
00:27:36 --> 00:27:38 informed on your products, where you are, where
00:27:38 --> 00:27:40 we are, and what the roadmap is. If you have
00:27:40 --> 00:27:43 any questions and you're not a ServiceNow customer,
00:27:43 --> 00:27:46 sales at ServiceNow .com. Reach out. And we'll
00:27:46 --> 00:27:47 find the right person, who the right contact
00:27:47 --> 00:27:49 is, so that you know how to get started on the
00:27:49 --> 00:27:51 journey with us. Awesome. I'll have links to
00:27:51 --> 00:27:54 everything you mentioned there. And I think very
00:27:54 --> 00:27:56 often people will hear that it's a tech podcast,
00:27:56 --> 00:27:59 a tech event, and we're talking about AI, agentic
00:27:59 --> 00:28:01 AI. But as you've said throughout this conversation,
00:28:01 --> 00:28:02 it's not even around the tech, it's about solving
00:28:02 --> 00:28:05 problems for customers. And I think that is a
00:28:05 --> 00:28:07 powerful moment to end on. But just thank you
00:28:07 --> 00:28:10 for joining me today. Thank you. One of the things
00:28:10 --> 00:28:11 that landed for me in this conversation with
00:28:11 --> 00:28:15 Pablo today is that autonomous IT. It's not just
00:28:15 --> 00:28:19 a simple switch that you can flip. It's a progression.
00:28:20 --> 00:28:24 Insight first, then action. Only then can systems
00:28:24 --> 00:28:27 coordinate those actions with confidence. And
00:28:27 --> 00:28:31 throughout that journey, trust, process and people,
00:28:31 --> 00:28:35 they matter just as much as the technology. So
00:28:35 --> 00:28:38 when we're hearing about partnerships like ServiceNow
00:28:38 --> 00:28:41 and Dynatrace, they work best when they start
00:28:41 --> 00:28:44 with real customer problems, not... technology
00:28:44 --> 00:28:48 first. Only then can you reduce the time to resolution,
00:28:48 --> 00:28:51 improve service reliability and prevent issues
00:28:51 --> 00:28:55 before they escalate. Which is so much better
00:28:55 --> 00:28:59 than just a bunch of abstract goals. We're talking
00:28:59 --> 00:29:02 measurable outcomes that show up in SLAs, customer
00:29:02 --> 00:29:05 satisfaction and the day -to -day sanity of IT
00:29:05 --> 00:29:08 teams. And being here at DynaTrace performed,
00:29:09 --> 00:29:11 surrounded by customers, partners and practitioners,
00:29:12 --> 00:29:15 all comparing notes, it really does reinforce
00:29:15 --> 00:29:18 the fact that something is changing here. Teams
00:29:18 --> 00:29:21 are no longer asking whether AI belongs in operations.
00:29:22 --> 00:29:25 They're asking, how can we use it responsibly?
00:29:25 --> 00:29:28 Where can we apply it first? And how can we build
00:29:28 --> 00:29:32 confidence in automation step by step? So I'll
00:29:32 --> 00:29:34 include links to everything Pablo mentioned,
00:29:34 --> 00:29:37 including how to learn more about ServiceNow's
00:29:37 --> 00:29:40 roadmap and how this partnership with Dynatrace
00:29:40 --> 00:29:43 continues to evolve. And if today's conversation
00:29:43 --> 00:29:46 made you reflect on how your organisation handles
00:29:46 --> 00:29:51 incidences, change control and resilience, I'd
00:29:51 --> 00:29:53 love to hear what stood out for you. So as you
00:29:53 --> 00:29:56 think about the next outage, the next change
00:29:56 --> 00:29:59 window or the next escalation call. What would
00:29:59 --> 00:30:02 it take for your operations to move from reactive
00:30:02 --> 00:30:06 to truly autonomous? You've heard from me today,
00:30:07 --> 00:30:09 you've heard from Pablo I'm sure you've got lots
00:30:09 --> 00:30:12 of ideas, experiences and insights too So please
00:30:12 --> 00:30:16 pop by techtalksnetwork .com You can leave me
00:30:16 --> 00:30:18 an audio message, send me a written message or
00:30:18 --> 00:30:21 connect with me on socials Let me know Regular
00:30:21 --> 00:30:24 listeners will know I always say that I only
00:30:24 --> 00:30:26 partner with companies that align with my values
00:30:26 --> 00:30:29 and what I'm trying to build here at Tech Talks
00:30:29 --> 00:30:33 Network. And NordLayer fits that perfectly by
00:30:33 --> 00:30:36 helping businesses stay secure without adding
00:30:36 --> 00:30:39 unnecessary complexity. And every company today
00:30:39 --> 00:30:42 relies on SaaS tools, whether it's collaboration
00:30:42 --> 00:30:46 platforms, CRMs or finance systems. The common
00:30:46 --> 00:30:48 denominator here is everything now happens in
00:30:48 --> 00:30:51 the browser. But here's the problem, most browsers
00:30:51 --> 00:30:54 were never designed with business security in
00:30:54 --> 00:30:57 mind. This is one of the many reasons why Nordlayer
00:30:57 --> 00:31:00 has introduced a new business browser that puts
00:31:00 --> 00:31:04 security, visibility and control directly where
00:31:04 --> 00:31:07 work happens. And it helps protect against things
00:31:07 --> 00:31:10 like phishing, malicious sites and unauthorised
00:31:10 --> 00:31:13 access, while also giving your teams a safer
00:31:13 --> 00:31:16 and more controlled way to work online. And the
00:31:16 --> 00:31:20 best part is... doesn't change how people work.
00:31:20 --> 00:31:23 It just makes what they're already doing more
00:31:23 --> 00:31:25 secure. So if you want to learn more, please
00:31:25 --> 00:31:29 head over to Nordler .com slash browser and see
00:31:29 --> 00:31:33 how it fits into your workflow. But that's it
00:31:33 --> 00:31:35 for now. Time for me to hit the show floor again,
00:31:35 --> 00:31:36 but I'll be back again tomorrow.