In this episode of TechDogs Discover Dialogues Fireside Chat, host Vikramsinh Ghatge sits down with Dan Owens, Chief Financial Officer at Maxio; Jerod Sands, Chief Financial Officer at Parameter; and Vivek Dalmia, Chief Financial Officer at MoveInSync, for a practical CFO roundtable on how finance leadership is evolving beyond the balance sheet.Today’s CFO is no longer limited to reporting, compliance, and financial control. The role has expanded into capital allocation, AI adoption, business transformation, risk management, operational efficiency, and long-term value creation. The conversation explores how finance leaders are balancing the pressure to invest in growth with the need to protect margins, manage cash flow, and build financial resilience.The panel explores where AI is already creating measurable value and where expectations are still ahead of reality. Jerod explains that AI ROI is becoming clear in high-volume, rules-based processes such as order management, but that judgment-heavy areas like forecasting still require a strong “trust but verify” approach. Another key theme is efficiency. The panel reframes efficiency beyond cost-cutting. For CFOs, efficiency now means operating leverage, faster decision-making, better visibility, stronger workflows, and the ability to remove friction across teams. The episode closes with a broader reflection on the evolving CFO mandate. CFOs are becoming more strategic, more operational, and more technology-aware. Yet the panel agrees that this influence is only credible when the fundamentals remain strong: accurate reporting, controls, compliance, transparency, and the courage to challenge assumptions when the numbers do not support the story.In this episode, we cover:• Why “growth at all costs” has given way to disciplined capital allocation• How CFOs are balancing growth, margins, cash flow, and resilience• Where AI is creating real ROI in finance and business operations• Why AI in finance still requires trust, verification, and human oversight• How automation is changing forecasting, order management, dashboards, and FP&A• Why shadow AI, fraud, data privacy, and governance are becoming major CFO concerns• How finance leaders are redefining efficiency through operating leverage and decision speed• Why the modern CFO must be both strategic and deeply grounded in control• How CFOs can lead transformation without losing sight of compliance and resilienceKey Takeaway:The CFO role is no longer confined to managing numbers after the fact. Today’s finance leaders are shaping where capital goes, how AI is adopted, how risk is managed, and how businesses grow with discipline. The CFOs who will define the next phase of business will not choose between strategy and control. They will master both.About the Guests:Dan Owens is the Chief Financial Officer at Maxio, where he leads financial strategy and operations with deep experience across public companies, private equity-backed technology businesses, financial planning, M&A, revenue operations, and scalable growth systems.Jerod Sands is the Chief Financial Officer at Parameter, where he leads financial strategy, operational planning, and growth initiatives. His experience spans private equity-backed, venture-backed, and public companies, with a focus on disciplined scaling and operational efficiency.Vivek Dalmia is the Chief Financial Officer at MoveInSync, where he leads financial strategy, planning, governance, compliance, capital efficiency, and data-driven decision-making for sustainable growth.

In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Abhishek Mehrotra, Chief Human Resources Officer at Yubi, to explore how HR is fundamentally evolving, from a backend support function to a strategic decision engine. This conversation cuts through the noise around AI in HR and gets to what it actually means for leaders, teams, and the future of work.Organizations today are investing heavily in HR technology, yet most still treat it as operational infrastructure rather than a source of strategic intelligence. The real opportunity, and the real gap, lies in reimagining people systems as proactive decision-making platforms. As AI becomes embedded in hiring, performance, and workforce planning, the question isn't whether to adopt it, but how to do so without losing the human judgment that makes organizations sustainable.Abhishek brings over 25 years of people leadership across technology, telecom, social media, and fintech to this conversation. Having navigated transformations at global enterprises and fast-scaling platforms alike, his perspective spans both the architectural and the deeply human dimensions of organizational change. What makes his viewpoint distinctive is the rare combination of data-driven discipline and empathetic leadership philosophy, and the conviction that HR must own business outcomes, not just enable them.Here is a core insight that reframes how most organizations approach AI adoption in HR: Abhishek argues that rather than launching company-wide skilling programs and waiting for training to drive adoption, organizations should start by creating internal champions, and build success stories that others naturally want to replicate. Adoption, in his model, is pulled by curiosity and proof, not pushed by mandates.For most HR leaders, this reordering is significant. It means democratizing access to AI tools across all functions, not just engineering, and trusting that on-the-job experimentation will outperform structured classroom training. The shift from "training first, then adoption" to "access first, then learning" fundamentally changes how organizations build AI fluency at scale.In this episode, we cover:• How Abhishek's 25-year journey, from executing people processes to architecting people intelligence, shaped his view of HR's strategic role• Why HR is no longer an enabler but a co-pilot with skin in the game for business outcomes• How AI is being embedded in hiring, performance management, and workforce planning, and what the human in the loop actually does now• Why roles are converging across functions and what a skills-based talent strategy looks like in practice• How the challenges of building a 0–100 organization differ fundamentally from scaling a 1,000-to-5,000 one• How to think about role reconstruction, reimagining team structures for a world where AI handles the what and how• Why leaders must be hands-on AI users themselves before they can credibly lead transformation• How psychological safety, system literacy, and human-centric resilience define leadership in an AI-first era• What budding HR professionals should do today to future-proof their careers, starting with their own daily workflows

Key Takeaway:The most important shift in HR leadership isn't about adopting the right tools, it's about owning the right outcomes. Abhishek's core argument is that HR becomes a decision system when its leaders stop waiting for a seat at the table and start earning one by demonstrating measurable business impact. As AI accelerates the convergence of roles, compresses time-to-market, and reshapes the skills landscape, organizations that pair algorithmic intelligence with human judgment, curiosity, critical thinking, emotional🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com

In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Sandip Wadje, Managing Director and Global Head of Emerging Technology Operational Risks & Intelligence at BNP Paribas, to explore how enterprises can securely embrace AI and emerging technologies while navigating an increasingly complex risk landscape. From overlooked vulnerabilities in agentic systems to the fragmented global regulatory environment, this conversation cuts through the hype and gets to what actually matters for leaders on the front lines of innovation.AI adoption is accelerating faster than most governance frameworks can keep pace with. Organizations are deploying generative and agentic models at scale yet the foundational questions around accountability, data quality, and output-level risk remain largely unresolved. One of the sharpest insights in this conversation: Sandip argues that organizations rushing into high-impact AI use cases; fraud detection, security operations, without addressing the basics first are setting themselves up for failure. His recommendation is to start with summarization, which accounts for roughly 50 60% of corporate knowledge work, build ROI there, and only then move into higher-complexity applications. This sequenced approach: summarize, write, reason, reframes AI adoption as a disciplined business case rather than a technology experiment.For enterprises already stretched across multiple emerging technology domains, this reordering of priorities is significant. Fixing data quality, cleaning up access permissions, and establishing output-level accountability before scaling AI is not just risk management; it is the foundation that makes AI ROI sustainable.In this episode, we cover:• How Sandip's career, from government officer to global risk leader, mirrors the evolution of technology itself• Why emerging technology is defined by the absence of regulatory clarity, and what that means for AI governance• The most underestimated risks in quantum computing, digital assets, robotics, and autonomous AI systems• Why the 'run the bank vs. change the bank' model is reaching an inflection point in large institutions• How organizations should sequence AI adoption: summarize first, then write, then reason• Why starting from AI output failures not model guardrails is the right approach to risk management• The compensatory control mindset: using existing security infrastructure before chasing new tools• Why global regulations are fragmented and what prescriptive, harmonized guidance should look likeKey Takeaway:The biggest risk in AI adoption is not moving too slowly it is deploying AI on a foundation that was never designed to support it. Sandip's core argument is that organizations must address data quality, access permissions, and output accountability before scaling AI into high-stakes domains. As agentic systems grow more autonomous and quantum computing edges closer to practical disruption, the institutions that build this disciplined foundation now will be far better positioned to lead, not just survive the next wave of technological change.About the Guest:Sandip Wadje is the Managing Director and Global Head of Emerging Technology Operational Risks & Intelligence at BNP Paribas, where he leads the firm's strategic approach to identifying, assessing, and mitigating risks across AI, cloud, digital assets, and quantum technologies. His background spans more than two decades, beginning as a Class 1 government officer in India's Ministry of IT before transitioning through KPMG, Deloitte, JP Morgan, and Risk IQ into his current global leadership role. What distinguishes Sandip is his ability to bridge deep technical expertise with board-level risk strategy, having operated across both the practitioner and advisory sides of some of the world's most complex financial systems.🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🌐 Visit us at: https://www.techdogs.com

The role of HR is evolving faster than ever before, and AI is at the center of that transformation. In this exclusive TechDogs Discover Dialogues HR Roundtable, we bring together three senior HR leaders to discuss how organizations can balance people, performance, technology, and the future of work in an AI-driven world. Featuring: Nancy Hauge Chief People Experience Officer, Automation Anywhere Lisa Sherwell Chief People Officer, SUSE Arpit Shelat Director - Human Resources, Genesys India As AI reshapes how businesses operate, HR leaders are being asked bigger questions than ever before: How do you stay people-first while driving business performance? Can AI make HR more human? How should companies build future-ready workforces? Is work-life balance outdated? What do employees expect from modern workplaces today? This conversation explores how HR is moving beyond traditional functions and becoming one of the most strategic drivers of business transformation. From AI-powered employee experiences to internal mobility, hybrid roles, workforce personalization, and leadership transformation, this roundtable dives deep into what the future of HR really looks like. Whether you're a CHRO, HR leader, business executive, founder, talent leader, or someone curious about the future of work, this episode is packed with actionable insights. Key Takeaways: ✔ Why people-first companies often outperform others ✔ How AI is improving employee experience ✔ Why HR must become more strategic ✔ The future of workforce planning✔ Why internal mobility matters more than ever ✔ How Gen Z is reshaping workplace expectations ✔ Why work-life balance may need redefinition Subscribe to TechDogs for more conversations with global leaders shaping the future of business, technology, leadership, and innovation.🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com

AI is changing how products are built, how teams operate, and where bottlenecks show up inside organizations. In this episode of TechDogs Discover Dialogues, Nikhil Sonawane speaks with Justin Stottlemyer from Intuit about scaling AI responsibly, getting data AI ready, integrating agentic systems, and building the evaluation strategies that make non deterministic systems dependable in production.

Justin shares lessons from decades of building at scale and explains why today’s AI shift is not just another digital transformation wave. It is a deeper disruption that forces new thinking around architecture, collaboration, governance, and leadership.

In this episode, we cover:

• Justin’s journey across early internet and commerce platforms and what it taught him about availability and scaling

• Why thinking in 1000x forces better architectural decisions than 10x planning

• What changes when LLMs, agents, and multimodal systems enter the production stack

• Data readiness for AI and why access, security, and structure matter more than ever

• The real architectural challenge: coordination overhead across teams, not just tools

• FinTech AI: combining non deterministic reasoning with deterministic APIs for accuracy and trust

• Human in the loop and validation strategies to reduce risk in AI powered workflows

• Build vs buy in AI: what to develop internally and what to leverage externally

• Evals and the Agentic Development Lifecycle, and why evaluation strategy is now a core competency

• Leadership for AI first organizations: gateway mindset with guardrails

Key takeaways:

• AI changes the pace of delivery, so leaders must measure where the next bottleneck is.

• Data must be AI ready to unlock real value, without compromising security.

• Non deterministic systems still need rigor, testing, and evaluation loops across the lifecycle.

• The winners are teams that democratize access safely and invest in education and adoption.

About the Guest:

Justin Stottlemyer is a Distinguished Engineer at Intuit and part of the FinTech AI Center of Excellence, where he focuses on AI transformation, developer productivity, and building scalable foundations for agentic experiences.

If you’re exploring enterprise AI, agentic workflows, FinTech innovation, developer productivity, eval strategy, or AI leadership, this episode is packed with practical insights

Subscribe for more conversations on AI, data, cloud, cybersecurity, and enterprise technology.

Core banking modernization is not about shiny new tech. It is about upgrading systems without breaking uptime, trust, or compliance. In this episode of TechDogs Discover Dialogues, Nikhil Sonawane speaks with Mike Stawchansky, EVP and CTO at Finastra, about practical modernization playbooks, AI in mission critical banking, and how to scale reliability across global engineering teams.Mike explains why modernization starts with measurement, why compliance needs to be built into the foundation, and why incremental change using the Strangler Fig approach beats big bang rewrites for core systems.We also discuss AI in banking, where it adds value today, why it should complement core systems rather than replace them, and why production automation still requires human checks and the four eyes principle.In this episode, we cover:• How to modernize legacy banking platforms without disruption by measuring what exists first • Why non-functional requirements must be explicit before migration or re-architecture • Compliance by design and how to make it difficult to do the wrong thing in production • Why big bang rewrites are risky for core banking and why Strangler Fig works better • Where to start modernization: user journey, adoption, and what actually improves customer outcomes • The modernization mistake many teams repeat: delaying tech debt until it becomes urgent • AI in mission critical banking: where it adds value, and why it cannot replace deterministic core systems • AI governance: where to draw the line on automation and why humans must stay in the loop • How global engineering teams stay aligned on reliability, delivery standards, and ownership • Reliability culture: breaking the “throw it over the wall” model across engineering, DevOps, and support • Leadership lessons for sustaining momentum during long transformation cyclesKey takeaways:• Measure first. Modernization should preserve or improve reliability, not reduce it. • Modernize incrementally. Strangler Fig reduces risk and builds trust through small wins. • AI complements core systems. Its probabilistic nature makes deterministic banking cores difficult to replace. • Keep checks in production. Treat AI like any engineer. Use validation and the four eyes principle. • Communication is the scaling factor. Clear, explicit communication and playback prevent misalignment in global teams. About the Guest:Mike Stawchansky is EVP and Chief Technology Officer at Finastra, where he leads technology strategy with a focus on product and infrastructure modernization and cloud transformations for mission critical financial services platforms. He brings deep experience across platform engineering, reliability, and large scale modernization, with a practical operating mindset focused on measurable baselines, shared accountability, and execution at scale.🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com

In this episode of TechDogs Discover Dialogues, host Nikhil Sonawane, Lead-Media Relations and Partnerships sits down with Gonçalo Borrêga, VP Product, AI & AppDev at OutSystems, to explore one of the biggest shifts happening in technology today, the rise of Agentic AI in enterprise software.Enterprise software has traditionally been built around stability, control, and reliability. But with AI entering the picture, that balance is rapidly evolving. As organizations move toward AI-first strategies, the question is no longer just how fast we can build software, but how intelligently we can evolve it without breaking systems.Gonçalo brings over two decades of experience across software engineering, product strategy, and enterprise innovation. In this conversation, he shares powerful insights on how AI is transforming not just development workflows, but the very nature of software systems, teams, and leadership.One of the most compelling ideas from this episode is simple yet powerful. AI is making speed a commodity.With AI accelerating code generation and lowering barriers to entry, the real challenge is no longer building software. It is building systems that can scale, adapt, and remain stable over time.In this episode, we cover:• How Agentic AI is reshaping enterprise software • Why speed is no longer a competitive advantage • The shift from developers to system thinkers • The role of abstraction, low-code, and AI-assisted development • AI agents as coworkers and even customers • Why governance and orchestration are becoming critical • How organizations can balance AI adoption with workforce concerns • Leadership lessons such as empathy, grit, and building for outcomes • Advice for founders building in the age of AIKey takeaway:The future of enterprise software is not just about AI. It is about how humans and AI collaborate. While AI accelerates execution, humans remain essential for defining intent, making decisions, and ensuring accountability.About the Guest:Gonçalo Borrêga is VP Product, AI & AppDev at OutSystems, where he leads innovation across AI, application development, and enterprise platforms. With a background spanning development, architecture, and product leadership, he is at the forefront of shaping AI-driven software ecosystems.🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com

Digital transformation is no longer a technology problem. It is a strategy, execution, and alignment problem.In this episode of TechDogs Discover Dialogues, hosted by Nikhil Sonawane, Lead Media Relations and Partnerships invites Mehdi Sebti from ServiceNow to share why most AI and digital transformation initiatives fail and what enterprises must rethink to actually deliver value at scale.With nearly two decades of experience across global organizations like Toyota Tsusho (CFAO), Accenture, and ServiceNow, Mehdi brings a rare “three-prism” perspective as a customer, consultant, and platform advisor.This conversation goes beyond buzzwords and dives into the real challenges enterprises face when trying to scale AI, align stakeholders, and drive meaningful transformation.What You’ll Learn in This Episode:• Why “technology is global, but adoption is local” and why this matters more than ever• The hidden reasons why most AI transformation programs fail• Why financial ROI alone is no longer enough to justify transformation• How value means different things to CFOs, CIOs, COOs, and CEOs• The biggest mistake enterprises make when investing in customer experience• Why platform thinking is replacing use-case driven transformation• How to balance automation with human-in-the-loop governance• The complexity of scaling transformation across EMEA• How to align cross-functional teams using a “North Star” approachKey Insight: Most companies do not fail at digital transformation because of bad technology. They fail because of fragmented thinking, poor alignment, and lack of a unified strategy.Who Should Watch This:• CIOs, CTOs, and Chief Transformation Officers • Business leaders driving AI and automation initiatives • Enterprise architects and digital strategy leaders • Consultants and professionals in digital transformation • Anyone interested in the future of AI in businessAbout the Guest:Mehdi Sebti is a seasoned digital transformation leader with nearly two decades of experience spanning ERP systems, consulting, and enterprise strategy across global organizations such as Toyota Tsusho (CFAO), Accenture, and ServiceNow. Having worked across Europe, the US, and Africa, he brings a unique “three-prism” perspective shaped by his roles as a customer, consultant, and software advisor. Mehdi specializes in helping enterprises unlock real business value through AI, platform-led transformation, and strategic alignment, with a strong focus on bridging the gap between technology execution and human-centric adoption.Subscribe to TechDogs for more expert-led conversations on AI, enterprise tech, and digital transformation.If you found this valuable, do not forget to like, share, and comment your key takeaway.🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com

In today’s fast-moving SaaS landscape, growth is often seen as the ultimate success metric. But what happens when companies scale faster than their ability to operate effectively?In this episode of Discover Dialogues by TechDogs, we sit down with Sachin Agrawal, Managing Director at Zoho UK, to explore one of the most overlooked challenges in modern SaaS: the gap between growth and operational maturity.With over two decades of experience across consulting, restructuring, entrepreneurship, and global leadership, Sachin brings a rare perspective shaped by real-world transformations, from the dot-com boom and bust to scaling a startup and leading Zoho’s UK expansion.What you’ll learn in this episode:• Why product-led growth works initially, but struggles at scale • The hidden risks when growth outpaces organizational readiness • How to identify market readiness signals before expansion • Why AI is no longer a differentiator in SaaS • What truly differentiates SaaS companies today: architecture, business model, and data control • The importance of operational maturity in scaling organizations • Leadership lessons on staying grounded in complexity and making better decisionsOne of the most powerful insights from this conversation:“Product-led growth gets you through the door… but operational maturity determines whether you can truly scale.”As SaaS companies grow, they often move from simple adoption to complex organizational integration—where systems, teams, and processes must evolve together. This episode breaks down why many businesses struggle at this stage and how to overcome it.Who should watch this?• SaaS founders and startup leaders • Product and growth leaders • Business operators scaling organizations • Enterprise decision-makers • Anyone interested in leadership, AI, and digital transformationAbout the guest:Sachin Agrawal is the Managing Director at Zoho UK, where he leads the company’s growth and market expansion in one of its key global regions. With a career spanning over two decades, he has worked across consulting, restructuring, entrepreneurship, and enterprise technology, gaining experience through major industry shifts including the global financial crisis. He is also the co-founder of ePoise Systems, an HR-tech startup that was later acquired by Zoho. His journey across India, the Middle East, Asia Pacific, and Europe has shaped his perspective on scaling businesses, operational maturity, and building sustainable organizations in complex and evolving markets.Subscribe to TechDogs for more conversations with leaders shaping the future of technology and business.If you found this valuable, don’t forget to like, share, and comment your biggest takeaway.#SaaS #Leadership #ProductLedGrowth #Zoho #TechPodcast #AI #StartupGrowth #BusinessStrategy #ScalingBusiness #DigitalTransformation #DiscoverDialogues🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com

AI is no longer a future ambition. It is already embedded across enterprise workflows, platforms, and decision-making systems. While building AI pilots has become easier, scaling AI securely, responsibly, and effectively across the enterprise is where organizations face real challenges.In this episode of TechDogs Discover Dialogues, we bring together a panel of leading CTOs and technology experts to unpack what actually happens when AI moves from experimentation to production. Today’s roundtable is moderated by Vikramsinh Ghatge, Editor-in-chief and Sr. Marketing Director at TechDogs. The panellists on the show are:• Tal Lev-Ami, Co-Founder and CTO at Cloudinary• Gilles Baillet, Head of Technology at AND Digital• Keith McFarlane, Chief Technology Officer at Globality, Inc.• Markus Nispel, CTO EMEA, Head of AI Engineering at Extreme NetworksThe conversation explores why secure AI is not just about protection, but also about governance, ownership, and trust.From infrastructure and developer platforms to enterprise AI applications, each panellist brings a unique perspective shaped by real-world deployments. This discussion moves beyond the hype and focuses on the practical realities of scaling AI in complex enterprise environments.What you will learn in this episode:• Why AI security begins with data, not just models • What breaks first when AI scales beyond pilots • The hidden risks of autonomous agents and AI-driven workflows • Why governance, auditability, and explainability are essential • How organizations can move from AI excitement to AI discipline • The role of people, culture, and leadership in scaling AI • Why secure by design is becoming a business imperative One of the key takeaways from this discussion is that AI does not introduce entirely new risks. It amplifies existing ones. Poor data quality, weak governance, and unclear ownership become more problematic when AI is layered on top.The panel also highlights how AI is reshaping not only technology stacks but also entire operating models. As AI accelerates certain functions, new bottlenecks appear. This forces organizations to rethink workflows, roles, and decision-making structures.Another important theme is the need for a risk-based approach. Not all AI use cases carry the same level of risk, and organizations must design guardrails accordingly. The goal is to balance speed, innovation, and control.Who should watch this?This conversation is relevant for:• CIOs, CTOs, and technology leaders • CISOs and security professionals • AI and data leaders • Digital transformation and innovation teams • Enterprise architects and product leaders Whether you are starting your AI journey or scaling existing initiatives, this episode offers practical insights to help you navigate enterprise AI adoption.Subscribe for more conversations with global technology leaders.#ArtificialIntelligence #EnterpriseAI #AISecurity #TechLeadership #DigitalTransformation #AIGovernance #FutureOfWork🔔 Subscribe to our channel now: https://tinyurl.com/TDYTSub🔔 Subscribe to stay ahead of enterprise tech trends: https://www.techdogs.com/newsletter 🌐 Visit us at: https://www.techdogs.com