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In this hard-hitting episode of Discover Dialogues, Vikramsinh Ghatge, Senior Marketing Director and Editor-in-Chief, engages in a candid conversation with Adam Gale, Field CTO for AI and Cybersecurity at NetApp. With over 20 years of experience across finance, government, and enterprise technology, Adam brings a rare combination of deep technical knowledge, strategic acumen, and relatable storytelling.

The discussion kicks off with Adam recounting his unorthodox path into tech—starting with a childhood mishap involving a floppy disk, moving through support roles, and eventually finding his stride in presales and strategic leadership. Throughout, his adaptability and hunger for learning come through clearly, alongside a natural talent for connecting with people across industries.

As the conversation deepens, Adam turns a sharp lens on the rising cybersecurity threats tied to artificial intelligence—especially around training data. He highlights the dangers of data sprawl, poor governance, and improperly classified storage systems still housing sensitive, compliance-critical information. For organizations aiming to scale AI responsibly, Adam underlines the importance of data visibility, intelligent classification, and strong governance.

👉 Read the full episode breakdown here: Adam Gale, Field CTO For AI & Cybersecurity At NetApp On Securing Critical Infrastructure In The AI-First Era

The episode also delves into alarming, fast-emerging threats—such as data poisoning, model hijacking, and synthetic data manipulation. According to Adam, human-led detection methods simply can’t keep up. Instead, companies must adopt AI-driven defense tactics like behavioral analytics, just-in-time permissions, and immutable logging to protect their environments.

On the encryption front, Adam sounds the alarm on the looming impact of quantum computing. He references rising concerns over crypto wallet breaches and urges enterprises to start migrating to post-quantum encryption standards before it’s too late. Proactive audits and future-proof cryptographic strategies, he argues, will be key to securing AI-intensive infrastructures.

Beyond the technical strategies, Adam shares refreshing takes on regulation and leadership. He views governance not as red tape but as a vital framework—likening regulations like GDPR and the EU AI Act to safety standards forged through past lessons. By leveraging tools like auditability, redundancy, and immutability, he believes businesses can confidently meet these frameworks while fostering innovation.

As the dialogue wraps, Adam offers invaluable advice for aspiring CTOs and cybersecurity leaders: Be curious. Be cross-functional. Cultivate “T-shaped” expertise—deep in your domain but broad in understanding. It’s this blend, he says, that enables leaders to align tech with compliance and strategy in a volatile digital landscape.

In this episode of Discover Dialogues, Vikramsinh Ghatge, Sr. Marketing Director and Editor-in-Chief, is joined by Neeraj Manik, Vice President & Senior Partner – Intelligent Business Operations at IBM Consulting. With over 25 years of transformation leadership at global powerhouses like GE, Genpact, and IBM, Neeraj brings a unique perspective shaped by deep operational experience, stakeholder empathy, and AI-first innovation.

From his early beginnings in the hospitality sector during the 1990s to now spearheading a billion-dollar AI-powered business portfolio, Neeraj’s journey is a powerful example of how personal growth can mirror the evolution of enterprise transformation itself.

What You'll Learn in This Episode:

🔹 Why Adoption > Perfection Neeraj explores why most enterprise AI initiatives fail—not because of technological limitations, but due to insufficient adoption. He shares how his team increases usage by eliminating fallback channels such as human email support, making AI the default mode of interaction.

🔹 Measuring What Really Matters Rather than relying on polished dashboards or limited-scope POCs, Neeraj explains which metrics actually move stakeholders and build trust around AI-led transformations.

🔹 From GE to IBM: Key Lessons in Scale He reflects on his time at GE during its peak, and how those experiences laid the foundation for his thinking around scaling operations and executing large-scale transformations with precision.

🔹 Stakeholder Mindsets & the Culture Layer We unpack how ignoring frontline users and middle managers can derail even the most technically sound projects. Neeraj emphasizes the importance of designing with the human experience in mind.

🔹 The First 100 Days of AI Transformation What should leaders prioritize early on? Neeraj lays out the key wins to target, how to shift the conversation from cost to value, and why being visible on the ground still matters—even in digital-first environments.

Want to hear the full conversation? 👉 Listen to the episode here

Who Should Tune In?

Transformation and operations leaders aiming to scale AI initiatives

Automation professionals facing roadblocks in adoption or execution

BPO strategists rethinking their operating models

Enterprise innovators seeking practical strategies for intelligent workflows

In this episode of Discover Dialogues, Vikramsinh Ghatge, Sr. Marketing Director and Editor-in-Chief at TechDogs, engages in an insightful conversation with Jayalakshmi Nagarajan, Chief Operating Officer at Aakit Technologies Pvt. Ltd. With more than 25 years of industry experience, Jaya shares her perspective on driving real ERP transformation across complex industries — from manufacturing and mill production to real estate and wholesale distribution.

What sets Jaya apart is her strategic clarity, operational rigor, and commitment to people-first leadership. Under her guidance, Aakit has helped enterprises modernize legacy systems not through technical brute force, but through an approach grounded in user empathy, process alignment, and precision delivery.

At the core of Aakit’s methodology is Design Thinking — not just as a trend, but as a practical framework to uncover true business needs. As Jaya explains in this conversation, Aakit breaks away from traditional ERP implementation patterns by involving users early, prototyping rapidly, and validating ideas through real-world feedback. This ensures ERP platforms are not only functional, but intuitive, scalable, and aligned with business outcomes.

Key Insights from This Episode:

Why industries like manufacturing and real estate demand resilient, scalable ERP ecosystems

Common pitfalls in SAP and cloud migrations—and how to sidestep them

How Design Thinking transforms rigid systems into innovation platforms

The mindset shift enterprises must embrace before adopting AI or S/4HANA

How Aakit stands apart from conventional ERP vendors

Success stories from brands like Madura, Kataline, and Lorenz

How hypercare and co-created roadmaps drive long-term ERP value

Aakit’s distinct approach stands on three pillars:

1. Outcome-Focused Delivery Success is defined upfront—beyond system go-lives. Aakit accelerates value realization through sector-specific templates, pre-built accelerators, and structured hypercare strategies.

2. Built-In Agility Using a modular, cloud-native framework, Aakit ensures fast deployments, streamlined S/4HANA adoption, and adaptive iteration cycles. Agile sprints paired with the latest SAP updates fuel continuous business innovation.

3. Strategic Client Partnerships Aakit stays engaged beyond implementation, with client success teams focused on co-creating roadmaps, enabling automation, and integrating emerging tech like AI, blockchain, and ESG reporting tools.

What if the next wave of computing isn’t about choosing between AI, LLMs, or quantum—but combining them into one transformative force?

In this episode of Discover Dialogues, host Nikhil Sonawane speaks with Orlagh Neary, a global tech leader whose journey—from AI innovation to Microsoft’s Quantum & AI Ecosystem GTM—offers a glimpse into how converging technologies are reshaping the enterprise landscape.

Now a board member at Cambrian Futures and advisor to UNESCO’s International Year of Quantum, Orlagh is known for turning cutting-edge trends into scalable business value. Her core message: AI, LLMs, and quantum computing aren’t silos—they’re a powerful trio working in synergy.

🎧 Tune in: 👉 Orlagh Neary, Former VP Of Quantum Ecosystem Engagement And GTM At Microsoft, On Building Scalable And Safe AI And Quantum

Highlights from the episode:

Quantum is no longer futuristic—it’s foundational.

AI strengthens both LLM accuracy and quantum fault tolerance.

Use cases like drug discovery, energy, and logistics are already seeing results.

Quantum Safety is about long-term data and brand protection.

Early partnerships and the right mindset are key to being “Quantum Ready.”

Retrieval-Augmented Generation (RAG) is more than a passing trend — it's becoming a cornerstone in building scalable, enterprise-ready Generative AI systems. In this episode of Discover Dialogues, we’re joined by Suman Debnath, Principal Developer Advocate for Machine Learning at Amazon Web Services (AWS), to explore the evolution of intelligent agents, the growing importance of retrieval, and how multimodal AI is reshaping enterprise deployments.

With a proven track record of over 100 technical talks at conferences like PyCon, PyData, ODSC, and AWS re:Invent, Suman brings both technical depth and a unique ability to make AI accessible to developers and business leaders alike.

The Core Insight: Retrieval First, Generation Next

A key takeaway from this conversation? Hallucinations in GenAI aren't a symptom of poor models — they're a consequence of weak retrieval. As Suman puts it, “If your librarian hands you the wrong book, reading it thoroughly still won’t give you the right answer.” This perfectly illustrates how faulty or insufficient data retrieval undermines even the best AI models.

That’s where RAG steps in. By grounding large language models with real, relevant external data — such as documents, product catalogs, internal wikis, or even IoT sensor data — RAG significantly improves the reliability and accuracy of AI outputs.

🡒 Don’t miss the full episode to hear Suman break it all down.

Beyond Text: Enter Multimodal AI Agents

Suman also offers a deep dive into the next chapter: Agentic RAG powered by Vision-Language Models. As enterprises begin merging structured and unstructured data — think PDFs, images, voice commands, and dashboards — standard text-based retrieval methods hit their limits.

To address this, Suman introduces Colpali, a new approach focused on enhancing multimodal search and decision-making. In industries like finance, healthcare, and logistics, where AI systems must interpret forms, read visuals, extract context, and take action — this shift toward multimodal agents is already underway.

Why This Discussion Is Crucial

This episode isn’t just conceptual — it’s a roadmap for action. Whether you’re:

A product or engineering team implementing GenAI

A CXO future-proofing your company’s AI investments

A tech leader evaluating next-gen AI infrastructure

Suman offers invaluable insight into where the real innovation is happening and what it takes to deploy intelligent systems that are both powerful and trustworthy.

In this episode of Discover Dialogues, Vikramsinh Ghatge, Sr. Marketing Director and Editor-in-Chief at TechDogs, sits down with Varun Srinivas—Founder & CEO of Therix.ai and Co-Founder at Coditas—to explore what it truly takes to build scalable AI systems that thrive beyond flashy demos and into real-world applications.

With over a decade of experience bridging software fundamentals with AI scalability, Varun brings clarity to a space often clouded by buzzwords. His central message is refreshingly grounded: AI isn’t about replacing people—it’s about empowering them. As he puts it, “AI won’t replace your job. But someone using AI might.”

However, Varun challenges alarmist narratives and urges companies to shift focus from fear to innovation—encouraging cultures built around experimentation, engineering discipline, and human-centered execution.

One of the standout topics in the discussion is the rise of “vibe coding”—a fast, instinctive coding approach enabled by generative AI. While powerful for prototyping, Varun warns that this method alone doesn’t scale. Without thoughtful evaluation, rigorous testing, and robust observability, vibe-coded systems often break down in production.

To hear the full conversation, check out the episode and explore how real-world AI can be made reliable, repeatable, and responsible.

Key Takeaways From the Discussion:

Prototypes Aren’t Products: Treat AI systems like software—not sorcery.

Adoption Is Cultural: Drive success by celebrating early wins and making the tech more accessible.

Code Quality Still Counts: Even with GenAI, clarity and simplicity remain foundational.

Lead Without Overriding: Great leaders guide through inquiry, not control.

Stay Agile: AI roadmaps should evolve every few days—not follow a rigid annual plan.

Varun also makes a clear distinction between “good data” and “usable data.” Clean data isn’t enough—it must be timely and contextual to be effective in model training and decision-making. He advocates for tighter product feedback loops and cross-functional collaboration, ensuring AI is not a siloed initiative but a shared mission.

This episode is a must-listen for:

Teams working on AI-powered product development

Engineering orgs diving into GenAI

Enterprise leaders guiding digital transformation

Startups moving from MVPs to production-ready systems

In this raw and revealing episode of Discover Dialogues, Stephen Walters, Field CTO at GitLab, sits down with host Vikramsinh Ghatge to unpack the real-world impact—and pitfalls—of AI in DevOps. Stripping away the hype, they dive deep into the shifting role of developers, the hidden dangers of AI-generated code, and what enterprises must do to stay ahead.

Episode Snapshot:

AI and DevOps are reshaping enterprise technology—but not without friction. Stephen Walters brings sharp insights from hands-on experience, including a shocking case where an AI-generated system spanning over 3 million lines of code led to hundreds of security flaws. The culprit? The AI didn’t actually "think"—it simply produced code without understanding the context or consequences.

In this episode, you'll learn:

Why AI won’t eliminate developers—but will raise the bar for skills

The security risks lurking in auto-generated code

How tech leaders can balance AI hype with practical, long-term strategy

Why human judgment still matters in an age of automation

The need for ongoing investment in continuous learning and system improvement

AI has moved beyond just producing outputs—it’s now about intelligent systems that can think, plan, and earn trust across every layer of the enterprise.

In this episode of Discover Dialogues, Vikramsinh Ghatge, Sr. Marketing Director and Editor-in-Chief, speaks with Keith McFarlane, Chief Technology Officer at Globality. With a career spanning leadership roles at Oracle, LiveOps, and now Globality, Keith provides a behind-the-scenes look into how enterprise platforms are being reimagined in the age of AI-native transformation.

Keith unpacks the foundational principles behind Globality’s platform—where his team is pioneering the use of agentic AI frameworks capable of autonomous decision-making, contextual planning, and execution. He emphasizes that while intelligence can be engineered, building trust into these systems is the real challenge.

In fact, in the full episode on TechDogs, Keith shares how purpose-built internal tools gave Globality the agility, speed, and control they needed—something off-the-shelf vendors couldn’t match.

Key Topics Covered:

What agentic AI really is—and how to deploy it with the right controls

Embedding reasoning and context-awareness into enterprise workflows

Why trust—not model performance—is AI’s biggest hurdle

How CTOs can design for scalability, autonomy, and governance simultaneously

Lessons from building robust internal systems at Globality at lightning speed

Whether you’re scaling enterprise tech, initiating AI strategies, or rethinking how platforms should be built—this conversation offers a practical roadmap for creating AI-first systems with real-world impact.

AI has moved beyond just producing outputs—it’s now about intelligent systems that can think, plan, and earn trust across every layer of the enterprise.

In this episode of Discover Dialogues, Vikramsinh Ghatge, Sr. Marketing Director and Editor-in-Chief, speaks with Keith McFarlane, Chief Technology Officer at Globality. With a career spanning leadership roles at Oracle, LiveOps, and now Globality, Keith provides a behind-the-scenes look into how enterprise platforms are being reimagined in the age of AI-native transformation.

Keith unpacks the foundational principles behind Globality’s platform—where his team is pioneering the use of agentic AI frameworks capable of autonomous decision-making, contextual planning, and execution. He emphasizes that while intelligence can be engineered, building trust into these systems is the real challenge.

In fact, in the full episode on TechDogs, Keith shares how purpose-built internal tools gave Globality the agility, speed, and control they needed—something off-the-shelf vendors couldn’t match.

Key Topics Covered:

What agentic AI really is—and how to deploy it with the right controls

Embedding reasoning and context-awareness into enterprise workflows

Why trust—not model performance—is AI’s biggest hurdle

How CTOs can design for scalability, autonomy, and governance simultaneously

Lessons from building robust internal systems at Globality at lightning speed

Whether you’re scaling enterprise tech, initiating AI strategies, or rethinking how platforms should be built—this conversation offers a practical roadmap for creating AI-first systems with real-world impact.

In this episode of Discover Dialogues, host Vikramsinh Ghatge, Senior Marketing Director and Editor in Chief, sits down with Keith McFarlane, Chief Technology Officer at Globality, to explore how enterprise platforms are evolving in an era defined by AI-native transformation. With a wealth of experience from leadership roles at Oracle, LiveOps, and now Globality, Keith offers invaluable insights into the frameworks driving the next generation of sourcing platforms.

The discussion unpacks Globality’s approach to platform design, where agentic AI systems are at the core—capable of autonomous decision-making, strategic planning, and context-aware execution. Keith highlights the complexity of engineering trust—arguably a more difficult challenge than building intelligence itself—and shares how Globality’s bespoke internal tools enabled greater speed, control, and adaptability than any off-the-shelf solution could provide.

Key topics covered in the Episode include:

What agentic AI truly entails—and how to implement it with precision and control

Strategies for embedding reasoning and contextual awareness into enterprise workflows

Why building trust in AI systems is a greater hurdle than model accuracy

The imperative for CTOs to prioritize scalability, autonomy, and governance in unison

Insights from rapidly developing Globality’s internal systems with an AI-first mindset

Whether you're driving AI strategy at scale, navigating platform architecture, or reimagining procurement systems, this conversation offers a practical roadmap for building AI-first enterprise solutions with meaningful impact.

Keith also reflects on navigating enterprise adoption challenges, infosec requirements, and what engineering leaders need to cultivate teams that thrive in the era of autonomous systems. He delves into the decision to build in-house rather than rely on third-party tools, striking a balance between solving current business needs and laying the groundwork for the future.

In this episode of Discover Dialogues, VikramSinh Ghatge, Senior Marketing Director and Editor-in-Chief at TechDogs, sits down with Victoria Dimmick, CEO of Titania, to explore what many businesses are still getting wrong about cybersecurity in 2025. Spoiler: just passing a compliance audit doesn’t mean your systems are truly secure.

Victoria’s journey began in the world of corporate law and M&A, where she played a key role in scaling tech companies toward successful exits. But her career took a decisive turn when she identified a growing disconnect between perceived security and actual protection. Now, as CEO of Titania, she leads efforts to help industries like healthcare, aviation, and finance protect their network infrastructure — not only from current threats but from the often-overlooked vulnerabilities that can leave systems exposed.

In This Episode, You’ll Learn:

Why compliance does not equal real cybersecurity

The critical difference between cyber resilience and incident response

How AI-driven attacks are advancing faster than most defenses

The growing risks in supply chain security

Why network segmentation is a non-negotiable for secure infrastructure

Victoria also shares how to frame cybersecurity in terms that resonate in the boardroom, positioning cyber resilience as a fundamental part of business continuity rather than a siloed IT issue.

Packed with actionable insights — from sector-specific threat intelligence to strategies for attack surface reduction and real-time visibility — this episode is a must-listen for:

CISOs and CIOs

Cybersecurity and infrastructure teams

Compliance leads

Founders and executives in regulated industries

AI is reshaping industries at an unprecedented pace—but with that transformation comes a new set of challenges for leaders. How do you stay ahead, scale effectively, and deliver real value with AI, without getting lost in the noise?

That’s exactly what we explore in this episode of Discover Dialogues with Andy Boyd, Chief Product Officer at Appfire. With experience leading AI initiatives at IBM Watson and now shaping product strategy at Appfire, Andy brings a unique, firsthand perspective on building future-ready products and teams.

He emphasizes that true product leadership isn’t just about rolling out features—it’s about solving real problems, embracing innovation, and preparing for what’s next.

Here’s what we dive into in this episode:

AI in product strategy: How to weave AI into your workflows in a way that drives both innovation and business value.

Scaling AI-first teams: Why mindset matters as much as skillset when growing high-performing, AI-driven product teams.

The shift to product-led growth (PLG): How companies are moving from sales-heavy models to customer-first product adoption—and why it works.

Andy also shares his thoughts on the evolving role of product leaders in the age of AI, and how organizations can align tech investments with long-term success.

Let’s face it — your customers expect more these days. And we’re not just talking about great products or a smooth checkout. What they really want? A response that feels personal and happens right now.

We’ve all felt it — that frustration when a brand takes too long to reply, or when the message they send feels like it was meant for someone else. In a world where attention spans are shrinking and choices are endless, real-time interaction isn’t just a cool feature anymore — it’s survival.

Now, we know what you're thinking. Real-time anything sounds expensive, complex, or like something only massive brands can pull off. But that’s just not true anymore. Thanks to new tools and tech, you can engage with your customers at the right time, in the right place, without needing an army of support agents or a massive IT setup.

The key is having the right software behind the scenes — something smart that helps you deliver the perfect message or response while your customer is still paying attention. That means not just knowing who they are, but where they are in their journey, what they’re doing, and what they might need next.

Yeah, we know — it sounds like magic. But that’s where real-time interaction management (RTIM) software comes in.

We’ve seen brands totally transform their customer experience just by making their responses faster, more relevant, and a whole lot more human. And honestly? It works. People notice when they feel seen and understood, especially when it happens right when they need it most.

But here’s the tricky part — there are tons of platforms out there promising to do this. And sure, some are solid, but not all are created equal. So how do you know which one’s going to deliver for your business?

That’s exactly why we pulled together a guide that breaks down the best options out there right now — the real standouts for 2025 that are helping brands like yours level up their customer interactions.

Because at the end of the day, timing and relevance aren’t optional anymore — they’re your biggest edge.

Okay, so here’s the deal — when someone says “enterprise infrastructure,” your eyes might glaze over a bit. We totally get it. It sounds super technical, like something buried in a data center or only relevant to giant corporations with teams of IT wizards.

But here’s the thing — enterprise infrastructure is the quiet powerhouse behind everything your business does online.

Whether you’re handling internal systems, managing data, running apps, or making sure your customers never see the dreaded “server error” page… it all comes down to the infrastructure. And if that foundation’s shaky? Well, everything else feels harder than it should.

We’ve seen it time and time again — businesses hitting a wall because their systems aren’t built to scale, secure, or even just stay sane. You add new tools, hire more people, grow your reach... and suddenly, your setup starts to crack under pressure.

That’s where a strong infrastructure comes in.

Now, we’re not saying you need to overhaul everything overnight. But we are saying it’s time to stop thinking of infrastructure as “the IT team’s problem” and start seeing it for what it really is: your growth engine.

And guess what? You don’t need to figure this out on your own.

There are some brilliant tools out there right now—like, truly next-level platforms—that are built to help businesses like yours stay secure, flexible, and fully connected in 2025 and beyond. The trick is just knowing which ones are actually worth your time (and budget).

So, before you dive into another software trial or patch your systems together one more time, maybe take a step back and think about the big picture. Are your current systems helping you grow—or holding you back?

Because here’s the truth: the right enterprise infrastructure doesn’t just support your business—it amplifies it.

Let’s be real for a second — data center virtualization? It sounds like something only enterprise tech teams or massive IT departments would be worried about. But here’s the truth: it matters to you, whether you're running a growing business, managing systems, or just looking for smarter ways to keep things running without constantly upgrading hardware.

We’ve all been there — juggling servers, dealing with hardware that’s outdated the moment you install it, and spending more time putting out fires than actually improving performance. That’s where data center virtualization steps in and says, “Hey, what if we just did this smarter?”

Now, don’t worry. We're not about to drop a bunch of confusing tech terms and expect you to keep up. We’re just here to talk about why this whole thing is worth your time—before you even start digging into tools and platforms.

Virtualization, at its core, is just a way of doing more with what you already have. Instead of relying on physical servers for every task, you can create virtual machines that operate independently—but on shared hardware. Think of it like living in an apartment building instead of buying separate houses for every person. Same land, more efficient use.

And you know what? It’s not just for the big players. In fact, smaller teams and businesses often see the fastest wins from virtualization. Why? Because it allows you to cut down on hardware costs, reduce maintenance, improve uptime, and adapt quickly when your needs change. Flexibility is the name of the game.

But let’s zoom out for a moment. Why are we even talking about this now?

Because the way we manage IT infrastructure is changing—fast. Cloud adoption, hybrid work, and digital transformation have all pushed businesses to rethink their data strategies. And trying to scale with physical infrastructure alone? That’s like trying to build a skyscraper with LEGO blocks. It’s going to get shaky, and fast.

We’ve watched businesses struggle with this. You add more servers, more racks, more people—and still, the system crawls. You lose time. You lose money. You lose sanity. Virtualization? It flips that script. Suddenly, you’re not reacting to problems—you’re proactively building a better environment.

Still, we won’t lie. Choosing the right virtualization software can feel like standing in the cereal aisle—there are so many options. Which one’s best? Which one fits your setup? Which one’s going to support you down the line? That’s a whole conversation on its own.

And that’s exactly why we created something to help.

We’ve gone deep into the world of virtualization software—looked at the top players, broke down the key features, considered real-world use cases—and put together a guide that cuts through the noise. So when you’re ready to actually take the leap, you’ll know where to land.

Bottom line? If you’re trying to modernize, streamline, or just take control of your infrastructure, virtualization isn’t a maybe—it’s a must. And no, you don’t have to figure it all out alone.