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techdaily.ai, your source for technical information. This deep dive is sponsored by Stonefly, your trusted solution provider and adviser in enterprise storage, backup disaster recovery, hypercon converged and VMware, HyperV, Proxmox cluster, AI servers, SA365, a turnkey security appliance, and public and private cloud. Check out stonefly.com or email your project requirements to sales@ stonefly.com. Okay, so when you think about big companies, there are these core systems, right? The ones that just have to be there.
Absolutely. The foundational stuff.
Exactly. And Workday is well, it's a huge name there. Almost synonymous with managing people, managing finances, the real uh critical resources. It's been that go-to system of record for ages.
The established player for HR and finance data,
right? But things are changing fast. AI, artificial intelligence, it's not sci-fi anymore. It's getting into the like the nuts and bolts of business operations.
It really is. It's becoming pervasive,
which throws up this big question. What happens these foundational systems like workday in a world that's increasingly shaped by AI. How do they adapt? What's their new role?
It's a fundamental question for the whole enterprise software landscape.
Definitely. And to really dig into this, we're looking at insights from someone with a pretty unique viewpoint. Carl Ishinbach, he's the CEO of Workday now, but he also spent a lot of time as a partner at Sequoia Capital.
Ah, so we've seen it from both sides running a massive tech company and you know spotting the next big thing from a VC perspective. That's valuable context
for sure. So our mission today is basically to understand Workday's game plan with AI. How are they positioning themselves? What does it mean for businesses? And honestly for us, the people working in them. Okay, let's uh let's unpack this.
Sounds good. I think the first thing that jumps out especially when you talk AI and HR systems is the job question. You know, is AI replacing people? What does that mean for workday which tracks all those people?
Yeah, that's the immediate sometimes fearful reaction, isn't it? But what's interesting is Workday's position, they're not just about people. They're also the system of record for money, for the financials,
right? That dual role is key.
And it means they're sitting on this enormous, carefully curated data set. We're talking insights from what over 70 million users and they process something like 30% of US job wrecks. That's a huge amount of data.
It's fast. But it's not just the volume, is it? It's the context.
This data isn't just floating around. It's embedded in actual business processes, day-to-day workflows.
Exactly. So, it's not just abstract numbers. It's tied to how work actually gets done. That context, um, that's what makes it incredibly potent for building useful AI agents much more so than just a general LLM could achieve,
right? Because the AI understands the why and how behind the data points. You mentioned something else crucial earlier. Trust.
Ah, yes. Trust.
Enterprises trust these established systems. They relied on them. moving from on-prem to the cloud and now with AI they're looking to these same partners like Workday to navigate this huge shift.
It's like okay we're entering this new territory who do we trust to guide us
precisely and that trust is vital when you start thinking about bringing AI agents into your operations. Companies need assurance these uh digital workers will be secure, responsible, ethical, compliant,
all the things you need for human workers basically.
Exactly. Which leads to this really fascinating concept. Workday is developing. becoming the system of record not just for humans but for AI agents too.
Okay, hold on. The agent system of record that sounds significant. Tell me more about that.
Yeah, the idea is basically that every AI agent working inside a company needs to be onboarded, managed, governed just like a person.
So giving the AI an employee ID almost
sort of they're building what they call an AI gateway. Think of it as controlling how these agents access data, what systems they can touch as a way to prevent, you know, agent sprawl.
Agent sprawl. I like that term like dozens of little AIs running around doing things without any central oversight.
Exactly that risk. So this agent system of record aims to unify the records, human workers, digital workers, all in one platform.
Okay. So you get a single view of your entire workforce, human and digital. That allows for much better planning, right?
It's the goal. Holistic workforce management and planning across both. It's a pretty fundamental shift in thinking.
It really is. Okay, let's switch gears slightly. How does workday actually make money from all this AI stuff? What's the monetization strategy?
They seem to have a three-part approach. First, there's a kind of uh seatbased uplift. So, a small extra cost per user for AI features that benefit everyone like AI assistance, productivity tools baked into the platform,
right? A base level of AI value for everyone with a modest price bump. Makes sense. What's number two?
Second is pricing based on specific role-based agents. So, imagine an AI designed purely for say running payroll or optimizing talent acquisition.
Ah like specialized AI workers.
Exactly. The price for those would be tied to the specific value they deliver, the efficiencies they create or the cost they save.
Paying for the specific AI job function. Got it. And the third part
the third is more about consumption. It's API access. As more AI agents, maybe even third party ones or other systems need to pull data from or push data into Workday, there'll be charges based on usage, how much data, how often. Okay, so seat uplift, role-based agents, and API consumption. Now, the obvious question, if these agents are doing work people used to do, does the agent pricing potentially, you know, cannibalize the traditional seat licenses? Fewer humans, fewer licenses.
That's the big debate, isn't it?
Yeah.
But the narrative, at least from workday, seems to be that AI is more about augmentation, freeing up humans from routine stuff to focus on higher value work.
So, making the existing workforce more productive rather than shrinking it necessarily.
That seems to be the primary pitch, driving overall growth and allowing reinvestment, not just cost cutting.
Yeah.
It's also interesting that they initially held back on big price hikes for the first wave of co-pilot features.
Yeah. They positioned them more as core functionality, didn't they?
Suggesting a longer game, embedding the value first before potentially charging more for highly specialized capabilities later.
Right now, this ties into the broader, often anxious conversation about AI and jobs. The narrative we're hearing from Workday is less about displacement and more about growth, reinvestment.
Yes. Framing AI as an engine for efficiency that frees up capital and human potential for new opportunities for expansion. It's a more optimistic take than just robots are taking jobs.
And it suggests we're heading towards maybe a skilled evolution alongside the AI one.
Absolutely. As AI takes on certain tasks, humans need to adapt, develop new skills, learning to work with AI, manage it, and focus on those uniquely human higher level tasks.
We even heard about Echinbach himself using AI tools like Gemini for summarizing reports or Zoom AI for meeting notes. They seem to be walking the walk internally.
Yeah, and apparently they have this everyday AI initiative trying to train all their own employees on using these tools for productivity gains, empowering their people, not replacing them.
That's a strong message. Let's get specific though. What are some of these AI agents they're actually building or acquiring? The recruiter agent from hired score sounds impactful.
Hugely impactful potentially. The numbers mentioned are pretty striking, like a 50% boost in recruiter productivity and much faster time to hire.
Wow. How does it achieve that?
By rapidly sifting through massive candidate pools, analyzing skills and experience against the job requirements far faster than a human could, identifying the best fits really quickly.
That could genuinely transform recruiting. What about agents focused inside the company?
Yeah, they're talking about talent optimization and talent mobility agents. These are aimed at reducing attrition essentially.
Well, how so?
By looking at employee skills, career goals, performance data, and actively matching them with internal projects, open roles, or development opportunities within the company.
So, helping people grow internally instead of looking elsewhere. That ties into that skills-based economy idea, too, right? Focusing on what people can do, not just their degree.
Exactly. AI is really good at that, identifying and matching granular skills to needs. We're seeing big companies like Accenture already moving heavily in that direction. Prioritizing skills over traditional credentials
makes sense. But what about interviews? Can AI really assess culture fit? That human connection?
The consensus seems to be not entirely. The human in the loop is still seen as critical there. AI can screen, schedule, maybe even conduct initial factual checks, but that final assessment. Cultural alignment, team dynamics, empathy that still needs a human.
So AI handles the transactional bits, freeing up humans for the relational bits.
That's the optimistic view, focusing recruiters and managers on networking, feedback, collaboration, the stuff AI can't easily replicate.
Okay. Now, workday was already a massive success before Echinbach took over. What's been the focus of the transformation under his leadership?
Well, first it's emphasized that it's a team effort building on a very strong foundation. The core values, people, customers, integrity, innovation, fun, profitability, those are apparently sacrosanked.
So, the DNA is the same. What's evolved? There seems to be a push for more let's say operational rigor getting more efficient as they've scaled into this huge company also refining the go to market getting deeper into specific industries specific verticals
becoming more specialized
and building out a much stronger partner ecosystem moving towards creating a whole economy around workday not just selling the core product
and technically AI wasn't exactly new for them
not at all they've had machine learning embedded in the platform for like over a decade the difference now seems to be the speed and velocity.
Why the acceleration?
Because they recognize the unique position their data gives them in this generative AI wave. It's led to some tough calls too like that workforce restructuring explicitly to reallocate resources towards AI and growth investments.
Really doubling down on AI as the future. So looking forward, what is their competitive advantage, their moat in this AI era? How does it change?
The message is loud and clear. The data is the moat. Echinbach apparently said something like data is the new UIUX for AI.
Interesting phrase.
It emphasizes that curated contextual data is the key differentiator. That's what allows them to build not just generic co-pilots, but these sophisticated role-based agents that understand skills, workflows, business outcomes.
So, it's the quality and context of the data powering specialized agents that sets them apart.
That seems to be the core argument. Moving beyond just task automation to more intelligent rosp specific augmentation built on that trusted data platform and again leveraging the trust enterprises already have in them to navigate this complex AI transition.
Okay, so summing this up, Workday is really evolving from being the system of record for people and money. They're aiming to be the system of record for AI agents too,
right? Unifying human and digital workforce management.
And they're leveraging that incredible data set they have with all its context to build these specialized role-based AI tools designed to augment what humans do, drive growth. with a big emphasis on that human AI partnership and the need for continuous skill development.
It's a fascinating strategy which leaves us with a final thought for you the listener. How is our whole concept of a workforce going to keep changing as these lines between human and will digital workers get blurriier? What new skills, what new strategies are going to be non-negotiable for individuals and for companies to really succeed in this new landscape?
Something definitely worth thinking about.
techd.ai your source for technical information. This deep dive is sponsored by Stonefly, your trusted solution provider and adviser in enterprise storage, backup, disaster recovery, hypercon converged in VMware, HyperV, Proxmox cluster, AI servers, SA365, a turnkey security appliance, and public and private cloud. Check out stonefly.com or email your project requirements to sales at stonefly.com.