This panel at Google Cloud Next '26 examines how artificial intelligence, AI, cloud-native workflows and human-centered design streamline healthcare operations for providers and members. The conversation covers automating repetitive tasks, synthesizing unstructured data, human-in-the-loop design, security and compliance and rapid prototyping. Speakers describe how cloud tools and partnerships accelerate delivery and produce measurable outcomes while prioritizing customer problems and embedding privacy security and responsible AI from the start.
Panel participants include Danny Brakebill of Elevance Health, staff vice president; Venkat Alladi of Elevance Health, staff vice president; Balaji Ramdoss of Deloitte, managing director; and John Furrier of SiliconANGLE Media, co-founder and co-chief executive officer, with the session hosted by theCUBE Research. Brakebill describes an AI solution that reduces manual research and speeds provider responses, and they report measurable productivity improvements. Alladi emphasizes redesigning processes with human oversight to improve accuracy, and they highlight human-in-the-loop design as essential. Ramdoss credits cross-functional teams and curated partnerships for moving prototypes into production and driving measurable outcomes, and they underscore the value of rapid prototyping and governance. Furrier moderates the discussion and guides practical lessons for implementing AI in healthcare operations.
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Balaji Ramdoss, Deloitte & Venkat Alladi & Danny Brakebill, Elevance Health
This panel at Google Cloud Next '26 examines how artificial intelligence, AI, cloud-native workflows and human-centered design streamline healthcare operations for providers and members. The conversation covers automating repetitive tasks, synthesizing unstructured data, human-in-the-loop design, security and compliance and rapid prototyping. Speakers describe how cloud tools and partnerships accelerate delivery and produce measurable outcomes while prioritizing customer problems and embedding privacy security and responsible AI from the start.
Panel participants include Danny Brakebill of Elevance Health, staff vice president; Venkat Alladi of Elevance Health, staff vice president; Balaji Ramdoss of Deloitte, managing director; and John Furrier of SiliconANGLE Media, co-founder and co-chief executive officer, with the session hosted by theCUBE Research. Brakebill describes an AI solution that reduces manual research and speeds provider responses, and they report measurable productivity improvements. Alladi emphasizes redesigning processes with human oversight to improve accuracy, and they highlight human-in-the-loop design as essential. Ramdoss credits cross-functional teams and curated partnerships for moving prototypes into production and driving measurable outcomes, and they underscore the value of rapid prototyping and governance. Furrier moderates the discussion and guides practical lessons for implementing AI in healthcare operations.
Balaji Ramdoss, Deloitte & Venkat Alladi & Danny Brakebill, Elevance Health
In this interview from Google Cloud Next 2026, Danny Brakebill, vice president of business operations at Elevance Health, joins Venkat Alladi, staff vice president of technology at Elevance Health, and Balaji Ramdoss, managing director at Deloitte, to talk with theCUBE's John Furrier about how a human-centered AI approach is simplifying healthcare operations and accelerating value delivery for members and providers. Brakebill frames the core business problem: provider inquiries that require extensive research and multiple handoffs, where AI now delivers 90% o...Read more
Balaji Ramdoss
Managing DirectorDeloitte
Venkat Alladi
Staff VPElevance Health
Danny Brakebill
Staff VPElevance Health
In this interview from Google Cloud Next 2026, Danny Brakebill, vice president of business operations at Elevance Health, joins Venkat Alladi, staff vice president of technology at Elevance Health, and Balaji Ramdoss, managing director at Deloitte, to talk with theCUBE's John Furrier about how a human-centered AI approach is simplifying healthcare operations and accelerating value delivery for members and providers. Brakebill frames the core business problem: provider inquiries that require extensive research and multiple handoffs, where AI now delivers 90% o...Read more
exploreKeep Exploring
What problem was solved here, and why does it matter?add
How was the AI initiative approached and rolled out, including data strategy, cloud infrastructure, security-by-design, compliance and governance measures, stakeholder roles, and human-in-the-loop controls?add
What technology tools did you evaluate and use to implement this solution, and how did you decide on them based on the business problem, workflow/process, and database/architecture requirements?add
How does injecting intelligence into the workflow — specifically using human-in-the-loop processes and subject-matter-expert feedback — affect the accuracy, consistency, security, and productivity when architecting and deploying solutions?add
How should responsible AI be approached, communicated, and implemented in healthcare to ensure patient safety, trust, and human oversight?add
Balaji Ramdoss, Deloitte & Venkat Alladi & Danny Brakebill, Elevance Health
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John Furrier
>> Welcome back to theCUBE's live coverage here at Google Next '26. I'm John Furrier, with Alison Kosik's here out getting the stories. It's the third, three days of wall to walk live coverage. We got every conversation you can imagine from deep tech to the C-suite. We got it all covered. Of course, the developers are all making it happen. AI natives coming. We're seeing vertical markets really explode in value creation, also value extraction on the customer side. Healthcare has been one of them. Making healthcare simpler and more connected is the session here. We got Danny, VP of business operations at Elevance Health. Thanks for coming on. Good to see you.
Danny Brakebill
>> Yeah. Absolutely. Thank you.
John Furrier
>> Venkat, staff VP on the technology side, elevance Health, thanks for coming on. And Balaji, managing director at Deloitte, making it all happen. Gentlemen, thank you for coming on this CUBE session. It's kind of a mini CUBE interview panel. I really appreciate it. Let's start with what you guys roles are.
Danny Brakebill
>> Yeah.
John Furrier
>> Daniel, we'll start with you. What do you do?
Danny Brakebill
>> Yeah, so I'm in the business, and so my role really is looking at how I can use AI to make our experience for our members, our providers, and our associates simpler. And really that gets to the core of it, simpler, more connected and more personal.
Venkat Alladi
>> John, my role in technology is to look into that vision and see how we can build practical applications, AI native, but keeping security, privacy in the core of it. And then at the end of the day, a human-centered experience.
John Furrier
>> Balaji, make it all happen.
Balaji Ramdoss
>> Oh, absolutely. I'm looking forward to it. And our role at Deloitte is to help connect the business priorities and AI with an AI practical implementation. It's basically our focus is on applying AI in a way that naturally fits in a real workflow and supports people in their day-to-day work and create experiences for better outcomes.
John Furrier
>> We've been covering the AI sector since the beginning as it's evolving. You're starting to see the frontier models, the word frontier by design, because they're pushing the envelope on the frontier. But frontier customers are out there doing it too. We're starting to see real evidence of value creation. So I want to start with what you guys put together. What problem did you guys solve here and why does it matter?
Danny Brakebill
>> Yeah. So we took something ... One of our processes that has a lot of handoffs, requires a lot of research, and also is kind of painful, right? So correspondence and inquiries from our providers come in and they need answers quick so they can serve our members and take care of them. And so we looked at a way to make that simpler. So instead of them having to dig through, recreate a claim and understand what happened to answer a question, we get them 90% of the way there and they can just answer the question quickly and get back to our providers so our providers can get back to providing care to our members.
John Furrier
>> And that pain was real.
Danny Brakebill
>> Yeah.
John Furrier
>> People can feel that pain.
Danny Brakebill
>> Yeah. Yeah.
John Furrier
>> Technology.
Venkat Alladi
>> Yeah. And like Danny said, when we looked at this problem, we couldn't look at it from a traditional way. We had to think different because the problem brought in a lot of unstructured information that we had to synthesize and we needed new tooling or technology, such as AI, to bring in all of that information, look at different formats of information coming in, understand what it meant, and then come up with a scalable solution with security and governance in play. That's where AI made a difference for us in bringing something speed to market, like bringing all of this information together and finding a solution that removed a lot of the manual steps and put the subject matter expert in the middle to make decisions.
John Furrier
>> The data's key. Data feeds the AI. We're seeing the success on the cloud side. Security was kind of that component that made DevOps work.
Venkat Alladi
>> Yeah.
John Furrier
>> In AI, the compliance and governance is a huge issue.
Venkat Alladi
>> Absolutely.
John Furrier
>> How'd that go?
Venkat Alladi
>> So good question, John, because we realized with AI, security is by design. Responsible AI and best practices have to be thought through from day one. What we did from a technology standpoint is broaden some of our partners in the business side, including our operations leader, along with them where our legal compliance, responsible AI team, guiding us on what the guardrails are. Where do we have human in the loop to verify information and make the right choices for us? That is how we built our application stack.
John Furrier
>> Great teamwork there. A lot of stakeholders.
Venkat Alladi
>> Absolutely.
John Furrier
>> When you put this problem together, you attack the problem. How did it go? How did it roll out? How did you scope it? What were some of the tactics and strategy and tactics you guys executed from Deloitte's standpoint?
Balaji Ramdoss
>> So at a high level, if you look at it, AI interprets the incoming information from the providers and consumers and translate them for our internal associates and make sure that the information is available readily when they start the work, and able to consume in a way that is more effective and efficient. So this means they have less time focusing on manually piecing the information together and more time on focusing on the work that matters, which is judgments and creating experiences for the providers and customers.
John Furrier
>> The technology is always a piece of the puzzle. We've seen big projects before, technology transformation projects. But with AI, it's got business value. Venkat, on the technology side, what was the key thing that's different versus, say, traditional approaches pre AI or pre ... I'll say pre AI.
Venkat Alladi
>> So I think when you really look at a problem that Danny brought up, which is how unstructured the information was, how it was manual intense, we had to bring in AI to see what were those steps that can be re-engineered. It was not just a technology thing, it was also business transformation. What was the repetitive steps that can be now automated, but then the key decisions where AI can assist in making that with the humans, the human in the loop. That redesigning with the human in the loop process, along with AI components, was unique to our solution.
John Furrier
>> The humans drive the AI, not the AI driving the human.
Venkat Alladi
>> Absolutely.
John Furrier
>> Plus domain expertise sits, you mentioned domain experts, not documented, but they're the ones driving.
Venkat Alladi
>> Yeah.
John Furrier
>> They get smarter.
Venkat Alladi
>> Absolutely. Yeah. And that's how we see this.
John Furrier
>> All right. Deloitte's well known for their AI center of excellence, you guys. We've covered that story on SiliconANGLE in theCUBE. What tooling ... Because you got a lot of deep tech in the tool chest there. What technology tools did you guys look at to implement this? Take us through some of the play by play.
Balaji Ramdoss
>> So before we look at the technology, we looked at business problem at the center, right? What problem are we trying to solve? What outcomes are we expecting? The technology is an enabler. So in this case, what we have done is we have leveraged Google's ADK and built a solution that effectively leverages all the incoming inquiries and translate them into some meaningful outcomes for both our customers and to our members and providers. So in order to create experiences, that helps them to make the process more seamless.
John Furrier
>> Process, workflow, database, databases is a word that I've used more this year than any year in 17 years doing theCUBE, because the workflow is where the intelligence gets injected, and the human portion is there. Can you guys expand on that? Because this is a big variable in, one, architecting-
Venkat Alladi
>> Absolutely....
John Furrier
>> and then deploying.
Venkat Alladi
>> Yeah. And I think the value unlock comes from the human in the loop and accuracy of the application and how secure it is. I know Danny and I, we partnered very closely and we can talk about it, how the subject matter experts actually added the feedback loop to us and improved the accuracy of the solution itself. Danny, anything you want to add?
Danny Brakebill
>> Yeah, no. I mean, I think that is the secret sauce, is having a person in the middle of this who can use their judgment and reasoning to get to the right outcome and make the model better. And it's allowing our associates to spend more time examining what happens, and the consistency we're seeing in our output is increased because humans have that judgment and the consistency is up and it's been great. And we've seen more time for the team to focus on solving other problems with our IT partners, as well as just time to coordinate care with our members and providers.
John Furrier
>> The productivity is, which is talked about at length online and the media, is a real thing. And when you have productivity, the macroeconomics actually increase on a country basis. GDP is going to go up, but companies are seeing that. So the jobs are expanding because there's more radiologists. We heard that here again, that's consistently happening in, say, healthcare as an example. So there's productivity in the team construction change. And now you add agents to the mix. How has all this impacted the team composition, the makeup, talent? What's been the reaction? Take us through the day-to-day experiences of the team. Because yeah, they could get shifted, but it's going to expand the scope, more product opportunities. Google talks about forward deployed engineers, but when you forward deploy technology teams with business teams, you get loops. AI loves process and loops because then you can get smarter faster.
Danny Brakebill
>> Yeah. I think it just brought our teams closer together. We're already pretty close. We sit in the same office, we visit each other all the time, but bringing in the frontline staff who do the work, the associates who do the work are closer to the work now, giving us feedback in the actual process, designing with us, which has changed. Usually we've had kind of a business analyst or somebody in between them and we're just closer now.
Venkat Alladi
>> And I'd like to add, John, I think the collaboration is key. What the AI influence has done for us is it has brought operations and technology, and other areas, closer to interact and have that dialogue to come together and vision what does the future look like. And what we would do in months, we could do in weeks, what we would do in weeks could be done in days or hours.
John Furrier
>> Yeah. And the psychology impact to a human being is one. My time is freed up from doing mundane, repetitive tests-
Venkat Alladi
>> Yes, absolutely....
John Furrier
>> to really domain specific, meaningful, whether I'm an engineer or a manager who was an engineer who'd be constantly code. So the roles are changing. And also the teamwork and partnership definitions change. It's almost if you can combine teamwork and partnership, teamship, a word we've said on theCUBE this past year is that teamship is both teamwork and partnership because partnership means you're in it together. This is psychology.
Venkat Alladi
>> Yeah, absolutely.
Balaji Ramdoss
>> So we look at it with the framework of people, process, technology. We put people at the center. We enable the process and technology to support the people. People could be our internal associates. It could be care providers. It could be consumers. It could be members. We are able to serve them better and create experience that's meaningful in a measurable and trusted way.
John Furrier
>> I have to ask you because I find that ... I love the line, people processing, now. I use it all the time, but a lot of people roll their eyes when they hear that word, we know, change management. But now with the way the tech and the AI and the business outcomes are all on the table and achievable at higher speeds, and mentioned the velocity, we can actually do this now. So this is actually something you can address all three in one.
Venkat Alladi
>> Absolutely. That's right.
John Furrier
>> How has that changed? Again, the psychology, time to market, time to value, do you agree?
Venkat Alladi
>> Absolutely. I think what this allows us is to think the right problem, look at the problems to solve, and given the tools, it enables an enterprise to look at where to invest, to bring simpler, connected, and human-centered experiences. And the guardrails, if you have the right responsible AI governance in place and security policies in place, we can definitely create the unlock that we want here.
John Furrier
>> Yeah. I find this game to be very interesting right now in the tech business because the business outcomes are on the table. Developers, deep tech and the C-suite are all engaging in teamship and teamwork and partnership. But there's still concern. Responsible AI is a major thing. So it's not just like, check the box, "Hey, we're responsible." You have to actually do things at those three levels. Let's talk about responsible AI because people want confidence. In healthcare, there are lives on the line. And there's also a lot of work that could be accelerated that it has a huge impact. So talk about the responsible AI, how you guys see that, how you think about it, how you communicate it, and how you put it into action.
Venkat Alladi
>> Sure. Danny, you want to take that first?
Danny Brakebill
>> Sure. It is probably the number one thing that we think about as we're designing solutions. Every change we make, it's brought through our committees. We have a cross-functional group of people on the call, our legal compliance, security, everyone's there collaborating, talking about it. And we have really meaningful conversations, and it's always the member and their data, the member at the middle of this, because we know that we have to keep that trust at the center of everything we're doing. So yeah, I think Venkat, you can probably elaborate more, but-
Venkat Alladi
>> I think you called it out right. At the end of the day, it's our customers that come to play here. We always think about how does this impact or touch or improve the experience of our customer, be it a member or a provider, and how do we design processes and solutions that gets that outcome better for them? And as long as we can show consistent and reliable and secure decisions that we make, I think AI is going to unlock that for us.
John Furrier
>> It's interesting that the idea of X, Y, access chart of performance and trust, you want to be in the upper right all the time. That is the new benchmark-
Venkat Alladi
>> Absolutely....
John Furrier
>> of this AI world. Because yeah, we don't want to have hallucinations or any kind of agents going off the rails, but also it's got to be trusted. There's PPI, you got all kinds of compliance. So you got to get it right.
Venkat Alladi
>> Yes.
John Furrier
>> It's a hard task.
Venkat Alladi
>> Yeah.
Balaji Ramdoss
>> Yeah.
John Furrier
>> What does this mean for you and broader opportunities?
Balaji Ramdoss
>> So I would call it responsible AI is essential, specifically in healthcare field, because trust matters, right? Human in the loop is not an add-on process, but it needs to be part of the design. So it's basically AI can surface insights and recommendations, but at the end of the day, humans are accountable to review those decisions and outcomes and serve better for our consumers.
John Furrier
>> Yeah. And the humans actually have to have accountability because they can't let the AI do it because they're the domain expert.
Venkat Alladi
>> That's right.
John Furrier
>> If you ask AI, is the code good? They're going to say, "Yeah, great job." We see that all the time. "How's my job?" "Oh, looks good." But this is real. The humans have to be curating, engineering, critical thinking through the entire process. Is that new? You guys do this for a living, you have critical thinkers, but in large corporations, the repetitive task could wear people down, but now they get a superpower. How has that changed people's roles and their skills?
Venkat Alladi
>> I think, John, in the beginning, we talked about change management, it's key. Bringing that training, education, and awareness is key. And we see that a lot of people initially have that little bit of a reluctance to understand what it is, but the moment they see the advantage and how it can help them in their day-to-day tasks, there's a wide acceptance on it. So we went through that process of doing a pilot group with a cross-functional team and introducing these concepts and have them play with it. And as we saw the results, and the human validated it, the belief and trust went up with the guardrails that we have. I think that was key for our success.
John Furrier
>> Yeah. If you don't mind me double clicking on that, because I'm starting to get some data on this. I don't really have an exact number because it's different by project and company, but there seems to be like a bar of time spent on the project before it kicks in. Not the light bulb or the aha moment, but more of the muscle. Do you guys have a feel for, when you get these teams together, how fast is it? Scope the speed. Doesn't have to be exact, but it's not months, sometimes days. And what's the learning curve? Because we're seeing this get very low.
Venkat Alladi
>> Yeah. Yeah.
Danny Brakebill
>> I guess from a ... When you're saying learning curve, you're talking about like people using the technology or-
John Furrier
>> It seems a breakthrough moment where you got to get in. I started coding again, came out of retirement 30 years, and I actually didn't have to know any of the syntax.
Danny Brakebill
>> Yeah, yeah.
John Furrier
>> So I programmed a lot in my day, but like, okay, I can build architecture and just codes. But that took some time to put the hooks in and little stuff I had to learn. But it was only like a day.
Danny Brakebill
>> Well, we were just meeting earlier today looking at some of our prototypes of what we're working on next. And I can say, we've been working on, for the past 90 days, on about six or seven different concepts and they look like products now. It's so much faster than it used to be. You're right. You'd sit around and maybe you'd see a couple demos and it was all in or something like that. Now this is real.
John Furrier
>> That's consistent with what we're hearing from practitioners. Demo, not memo.
Venkat Alladi
>> Yes.
Danny Brakebill
>> Yeah.
John Furrier
>> That seems to be the ... Because you can do it.
Danny Brakebill
>> Yeah.
John Furrier
>> By the time it takes to write a craft a nice scope document, you could actually do the demo and there's your PRD.
Danny Brakebill
>> Yeah, that's right. Yeah.
Venkat Alladi
>> And John, I want to call out an example. This is where I appreciate the partnership with a leader like Danny in the organization where there's synergy. We were both willing to invest in bringing the right talent together that a cross-functional team that was willing to spin up and do prototypes in a rapid fashion. It was not months and months, it was weeks and show a small win. The small win gave the encouragement for our sponsors to see the results and believe that this is possible.
John Furrier
>> And they see the energy too in the team. This really matters. I love that example. Love to get some more examples, but we should get an hour, go through all the mechanisms you guys got and the capabilities. But I really want to get into what it means for the future because the next pattern we see is once you get these wins, the product and the evolution happens fast. The prototypes start coming in.
Danny Brakebill
>> That's right.
John Furrier
>> The ideas now can be expanded. The old ways, too many ideas. Well, now it's a marketplace of ideas because then you just go to the team and say, "Stack rank the priorities." "Okay, I like this one." I mean, everyone's got a list along for ... You're smiling. Go ahead.
Balaji Ramdoss
>> So with the evolution of AI, it's really faster to get the first POC done, but in order for your POC to move from experimentation to implementation, leaders like Danny and Venkat would encourage in order to get to production. It's to realize the impact and the value and the experiences that it can bring. So basically it's a tight coordination between business, technology, and the partners to ensure that we are able to deliver what matters most for our consumers and create experiences.
John Furrier
>> And for you guys, the product roadmap, you get enthusiasm, which leads right to confidence.
Venkat Alladi
>> Yep, absolutely.
John Furrier
>> Whole flywheel kicks in.
Danny Brakebill
>> That's right.
Venkat Alladi
>> And I think the catalyst here is curated partnerships. Here we are at Google Conference with Deloitte, two partners for us, and we see such partnerships really trigger such innovation and ideas that we can bring forward to our customers, members, and providers and enriching their experience with cool AI solutions.
John Furrier
>> Yeah. I think one of the big stories that's not really told well here at the show, because there's a lot of tech involved, is this teamwork partnership in the ecosystem because the teamwork gets faster engagement, closer engagement, can go deeper, faster. That's a beautiful story. It's not just, "Hey, here's some APIs and here's some tech." Project management kind of mode. It's really like partners in crime, if you will, to get the job done.
Venkat Alladi
>> Absolutely.
John Furrier
>> All right. Final question to close out. A lot of people are looking at journeys and the AI journey. You guys are pioneers in this and on the frontier category. What advice would you guys give? We'll go down the line to wrap up. Danny, we'll start with you. Advice to someone on a journey.
Danny Brakebill
>> Yeah. I think find a problem that matters to your customers. Look at things like multiple handoffs or research that's needed and look at those and prioritize them against your goals. And I think that's where you start and see how AI can help.
John Furrier
>> Venkat?
Venkat Alladi
>> I would say build trust from the beginning. Bring in your privacy, security, compliance folks right from the get go. Human in the loop is not an afterthought. It is integral to the solution. And think about simpler, richer, and connected, human-centered experience.
Balaji Ramdoss
>> Yeah. Focus on AI that fits into the actual workflow naturally, rather than just focusing on just the technology by itself. It's people at the center. Technology is the enabler.
John Furrier
>> Awesome. Gentlemen, thank you so much. Great session. Great example. Thanks for sharing your environment and your goals and successes. And , congratulations on the prototype coming out.
Danny Brakebill
>> Thank you.
John Furrier
>> You guys are just on a great partnership and teamship, teamwork and partnership. Thanks for coming on. Appreciate it.
Danny Brakebill
>> Yeah. Thank you.
John Furrier
>> All right, I'm John Furrier. Healthcare, it's the same theme. Builders, operators, investors all coming together, stakeholders in an integrated AI journey that has a lot of value, happens super fast. The speed and velocity of the creation and capture of the value is happening in AI with cloud distributed computing is happening very, very fast. Of course, we're doing our part to bring that data to you. Thanks for watching.
John Furrier