Vikul Gupta on AI Quality: The New Trust Gate | Ep 1326
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What is the main topic discussed in this episode?
Welcome to Corusant Technologies, home of the Digital Executive Podcast. Do you work in Emergent Tech, working on something innovative, maybe an entrepreneur? Apply to be a guest at www.corizant.com forward slash brand. Welcome to the Digital Executive. Today's guest is Vikal Gupta. Chief Technology Officer Vikal Gupta is a visionary technology leader driving innovation in digital engineering and AI transformation at Quality AI. As CTO at Quality AI, he has led the creation of next generation AI and automation platforms that enhance software delivery and accelerate digital modernization for global clients. Under his leadership, Quality AI's next gen center of excellence has grown into a 150-member Global Innovation Hub, delivering cutting-edge solutions across cloud, DevOps, and Gen AI.
Vehicle's initiatives have earned industry recognition, including the CEO Award 2025 for exceptional impact on company growth and innovation. Well, good afternoon, Bickle. Welcome to the show. Thanks, Blind. Thank you, my friend. I appreciate it. You making the time today. Uh, you're hailing out of Raleigh, Durham, North Carolina. I'm in Kansas City. So just an hour difference today. I appreciate that. I know sometimes it's hard to traverse time zones. So let's jump into it. Bickle, you've spent over two decades in enterprise technology with leadership roles at HP Software and Cog Cognizant before. Before becoming the Chief Technology Officer at Quality AI. And along the way, you've secured patents and AI-driven quality engineering.
How did Vikul Gupta move from DevOps into AI-powered quality engineering?
What's that through line across those chapters in your career? And what drew you specifically towards quality engineering as a place to apply AI at scale?
Right, I've I've been a hardcore engineer, right, from from from the get go. Now, quality happened by accident to me. So I was I was with HP, I was the global CTO for DevOps, and I was with the engineering division and was also their data center and cloud automation division. And one of the large SI wanted me to come and establish the DevOps practice. When I joined in, I realized that their DevOps practice was with the quality organization. So I took that as a challenge. I've never done quality before that. And one of the things which which the head of quality quality organization asked me to do was apply bring engineering discipline, convert quality assurance to quality engineering. And that's what I did.
And at that time, one of the key levers which I thought will make the transformation really impactful and quick was AI. And from the day I started there, I I I I was intrigued by what all is possible. The lot of possibilities in quality engineering were just immense. Coming from engineering background, I realized that AI was in some form always there for For software development, whether it was code completion and things like those.
Why did AI become essential for delivering software quality at speed?
But when it came to quality, quality as a discipline, there was some bit of automation, but almost zero AI. And then as digital became more and more prominent, it was found like we were training code much faster than we could test it. And AI became not just an option, then AI became a way for us to Do quality at speed. So that's how it started. And after my stint with the large service provider, I was stopped by Quality AI, previously known as Qualitest, to join the organization to do something similar. Quality AI has been in the quality business for almost 28 plus years. Now, what they were looking was to bring in the next gen aspect. of quality. The entire journey from quality assurance to quality engineering.
And that's what I've been doing within quality AI for the last five years. Patents were an outcome of me trying to solve problems. Problems like how much time does it take to design tests? How then, after you design the test, what how much time does it take to automate them? And after you automate them, how much time does it take to identify why your test case failed? So as we were looking at all those solving those problems, we developed these solutions, and these solutions became patents.
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Chapters
8 chapters
1
What is the main topic discussed in this episode?
0:08–1:43
2
How did Vikul Gupta move from DevOps into AI-powered quality engineering?
1:43–3:06
3
Why did AI become essential for delivering software quality at speed?
3:06–4:29
4
How can AI prevent software defects by identifying flawed requirements earlier?
4:29–6:24
5
What does Quality AI’s rebrand reveal about the role of trust in AI?
6:24–9:26
6
Why do AI pilots fail to reach production, and how can AI assurance build trust?
9:26–12:00
7
How can production customer journeys reveal software testing coverage gaps?
12:00–16:23
8
How will AI-generated code change the future of quality engineering?
16:23–21:59
Speakers
1 identifiedMore from The Digital Executive
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