Discover Dialogues

TechDogs
  • 0.0 (0)
  • Technology

Explore candid Interviews, Q&A's with C-suite leaders on strategic leadership and management, Leadership Challenges, and Leadership Accountability.

  1. Jul 28

    HR In The AI Era Must Stay Deeply Human Ft. Arppna Mehra, VP Of Human Resources At Honeywell

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Arppna Mehra, Vice President Human Resources at Honeywell, to explore how HR leadership is changing in an era shaped by AI, transformation, culture shifts, employee experience, and future-ready workforces.This is not a conversation about HR automation alone. It is a grounded discussion on why the future of HR must balance AI-enabled efficiency with human judgment, empathy, trust, psychological safety, and culture-led transformation.Arppna brings over 30 years of experience across HR, business transformation, mergers and acquisitions, people experience, and leadership. Her journey began in an era when HR was often seen as a personnel or policy function. Over time, she made a conscious choice to step out of the traditional HR back office and immerse herself in the business. She spent time shadowing line managers, sales leaders, operational teams, engineering teams, manufacturing environments, supply chain functions, and customer conversations.The conversation closes with leadership lessons for professionals moving into modern leadership roles. Arppna highlights contextual agility, influence without authority, active listening, inclusive environments, and the ability to manage people through uncertainty and macro-level anxiety. Her strongest leadership habit is listening: not to respond immediately, but to make people feel heard, supported, and understood.In this episode, we cover:• How Arppna’s 30-year HR journey evolved from personnel management to people experience• Why HR must operate close to business realities, not from the back office• How shadowing line leaders and operational teams shaped her business-first HR philosophy• Why HR leadership has shifted from control to enablement• Why psychological safety, trust, and commitment matter more than compliance alone• How AI is changing HR workflows, talent screening, skill mapping, and workforce planning• Why AI should augment human intelligence rather than replace human judgment• Why hiring, culture, empathy, and career development still need human involvement• How organizations can balance automation with a human employee experienceKey Takeaway:AI will reshape HR, but it should not remove the human center of the function. The future of HR is not about replacing judgment with automation. It is about using AI to reduce repetitive work, improve insight, personalize experiences, and help leaders make better people decisions while preserving empathy, trust, culture, and human connection. Arppna’s core argument is that HR must stay business-first and people-centered. The function cannot create impact from an ivory tower. It must be close to employees, close to operations, close to transformation, and close to the lived reality of work. In the AI era, the strongest HR leaders will be the ones who combine agility with empathy, transparency with trust, and automation with deeply human leadership.About Arppna Mehra:Arppna Mehra is the Vice President Human Resources at Honeywell. She brings over 30 years of experience across HR leadership, people experience, business transformation, mergers and acquisitions, culture building, organizational change, and future-ready workforce strategy. Her career reflects the evolution of HR from personnel management and policy enforcement to strategic people leadership and business transformation. Arppna’s leadership approach is shaped by operational immersion, active listening, psychological safety, transparent communication, contextual agility, and a strong belief that HR must be deeply connected to the business and the people it serves.#HRLeadership #FutureOfHR #AIInHR #PeopleExperience #WorkforceTransformation #HumanCenteredAI #EmployeeExperience #OrganizationalCulture #PsychologicalSafety #FutureReadyWorkforce #LeadershipDevelopment #TransformationLeadership #Honeywell #ArppnaMehra #TechDogs #DiscoverDialogues

    HR In The AI Era Must Stay Deeply Human Ft. Arppna Mehra, VP Of Human Resources At Honeywell

  2. Jul 23

    From Software Marketplaces To Agentic Commerce Ft. Andy Sen, CTO and Co-Founder At AppDirect

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Andy Sen, CTO and Co-Founder at AppDirect, to explore how software marketplaces, SaaS buying, digital commerce, and AI-led productivity are reshaping the way businesses discover, buy, manage, and scale technology.This is not a conversation about marketplaces as a static distribution channel. It is a practical discussion on how software commerce has evolved from large enterprise sales and on-premise implementations to subscription-based SaaS, self-service adoption, advisor-led buying, marketplace ecosystems, and now AI-assisted and agentic commerce. At AppDirect, this internal productivity wave led to an important realization. If employees are building their own AI-powered tools, organizations need visibility, governance, guardrails, approved LLMs, data protection, and a platform to manage that activity. That thinking led AppDirect to create and productize its AI productivity platform, devs.ai.The episode also explores platform leadership. Andy emphasizes two principles for anyone building scalable, customer-focused platforms: know your customer and build observability from day one. Teams must measure whether the platform is solving the right problem, whether customers are getting value, and whether the product is performing at the right level. Just as importantly, leaders must build great teams, hire for the characteristics that matter, measure what matters, and push decision-making as far down as possible.In this episode, we cover: • How Andy’s career moved from IBM eBusiness to Walmart Labs, Salesforce, and AppDirect • Why e-commerce became the through line of his career • How software purchasing evolved from enterprise sales to SaaS subscriptions • Why marketplaces and ecosystems became strategic priorities for business leaders • How software buying became more decentralized and user-led • Why time to value is now central to software adoption • How trusted advisors influence software buying for small and mid-sized businesses • Why SaaS management has become more important as software stacks grow • How marketplace platforms can help manage subscriptions, assignments, usage, and visibility • Why enterprise software pricing and billing have become more complex • Where AI is creating real productivity impact today • Why AI has not yet produced many category-defining Key Takeaway: The future of software commerce is moving from traditional buying to marketplaces, ecosystems, advisor-led trust, subscription management, AI-assisted productivity, and eventually agentic commerce. Andy’s core argument is that the biggest shift in software buying is time to value. Businesses no longer want to wait months or years before software creates impact. They expect products to deliver value quickly, scale across teams, and remain manageable as software stacks grow. AI is adding a new layer to this shift by allowing people to build tools faster, but it also creates a new governance challenge: organizations need visibility, guardrails, and platforms that help them scale AI productivity responsibly. About Andy Sen: Andy Sen is the CTO and Co-Founder at AppDirect. He brings deep experience across engineering, product management, e-commerce, software marketplaces, subscription commerce, platform strategy, SaaS management, and AI-led productivity. Andy began his career at IBM’s eBusiness division during the early days of internet commerce. He later worked across digital commerce and platform initiatives at companies including Walmart Labs and Salesforce before co-founding AppDirect. At AppDirect, Andy helps build platforms that enable businesses to create marketplaces, manage software subscriptions, support trusted advisor ecosystems, and navigate the shift toward AI-assisted and agentic commerce.

    From Software Marketplaces To Agentic Commerce Ft. Andy Sen, CTO and Co-Founder At AppDirect

  3. Jul 21

    AI Readiness Starts With Trusted Data Ft. Dave Shuman, Chief Data Officer At Precisely

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Dave Shuman, Chief Data Officer at Precisely, to explore why AI readiness does not begin with models, platforms, or the latest technology trend. It begins with trusted data. This is not a conversation about AI demos or technical buzzwords. It is a practical discussion on why organizations must get the foundational layers right before expecting AI, automation, real-time analytics, or advanced technologies to create meaningful business value. Dave brings a unique and non-linear career journey to the conversation. He began in broadcasting, running radio stations across Caribbean islands, where he learned how to cut through noise and deliver a signal that connected with audiences. That early experience shaped how he thinks about data today: organizations are constantly transmitting information, but the real question is whether the signal is accurate, trusted, and received in a way that supports action. The conversation closes with leadership lessons for data professionals. Dave explains that future data leaders must own outcomes, not outputs. They must translate technical concepts into business language, stay technically curious without making technology their entire identity, and build trust with business leaders through quick wins, mid-term initiatives, and long-term foundational investments. In this episode, we cover: • How Dave’s broadcasting background shaped his understanding of signal, noise, and feedback loops • What the dot-com era taught him about behavioral data and fast decision-making • Why companies that survived disruption used data to make better decisions faster • How demand signal analytics revealed gaps between internal assumptions and real market movement • Why scale makes data quality and governance more important • Why AI readiness starts with data catalogs and semantic layers • How the OODA loop applies to enterprise AI and data strategy • Why “observe” requires visibility into data, lineage, and quality • Why “orient” depends on shared business definitions and semantic consistency • How organizations should define which AI decisions can be automated and which need humans Key Takeaway: AI readiness does not begin with the model. It begins with trusted data, shared definitions, continuous quality, semantic context, governance, and business alignment. Dave’s core argument is that organizations cannot expect AI to deliver value if the data foundation is weak. AI agents do not always fail loudly. They can produce confident, coherent, and incorrect answers, which makes governance, semantic consistency, and data quality even more critical. The organizations that succeed will be the ones that move through the decision cycle faster because they can observe clearly, orient correctly, decide responsibly, and act with confidence. About Dave Shuman: Dave Shuman is the Chief Data Officer at Precisely, where he leads work across trusted data, data quality, governance, AI readiness, real-time analytics, and enterprise data strategy. His career spans broadcasting, e-commerce, demand signal analytics, big data, IoT, connected industries, smart cities, and enterprise data leadership. Dave’s professional journey began in broadcasting, where he learned the importance of signal, noise, audience feedback, and relevance. He later moved into the dot-com era, where behavioral data shaped real-time business decisions, before moving into demand signal analytics, supply chain intelligence, Hadoop, streaming data, and IoT. At Precisely, Dave focuses on helping organizations build trusted data foundations that support better decisions, stronger governance, and responsible AI adoption.

    AI Readiness Starts With Trusted Data Ft. Dave Shuman, Chief Data Officer At Precisely

  4. Jul 16

    Building Trusted AI For The Future Of Work Ft. Naomi Lariviere, Chief Product Owner & VP At ADP

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Naomi Lariviere, Chief Product Owner and Vice President at ADP, to explore how workforce platforms are evolving from systems of record into systems of guidance, action, and trust.This is not a conversation about adding AI into HR and payroll because it is the latest trend. It is a practical discussion on how AI can create real value only when it removes friction, supports better decisions, protects trust, and helps people accomplish important work more easily. The conversation begins with Naomi’s product philosophy and how her career shaped the way she thinks about building technology. For her, technology is a tool, but understanding people is the real foundation. If product teams understand people deeply, they can build tools around their needs rather than forcing users to adapt to software.Naomi explains that organizations no longer want HCM platforms that simply store information or automate transactions. Employees want fast, clear answers. Leaders do not want another dashboard that requires interpretation. HR teams want to spend less time managing processes and more time helping the organization use its people more effectively. The episode closes with leadership lessons for product professionals. Naomi explains that early-career professionals should stay curious, seek learning over comfort, ask better questions, and build empathy for customers. For individual contributors moving into leadership, the biggest shift is realizing that the skills that earned the promotion are not the same skills that make someone a successful leader. Leadership is about creating clarity, removing obstacles, developing teams, and helping others become the heroes of their own stories.In this episode, we cover:• How Naomi’s 20-year career shaped her people-first product philosophy• Why technology is a tool, but understanding people is the foundation of good product design• How HCM platforms are evolving from systems of record to systems of guidance and action• Why employees want answers instead of more places to search• Why leaders need guidance, not just dashboards• How AI is making workforce software more conversational, contextual, and proactive• Why useful AI starts with customer friction, not technology placement• Why AI should often feel invisible inside the user experience• How product teams should avoid turning AI into just another feature• Why trust and innovation must go hand in hand in HR and payroll• How ADP evaluates AI use cases based on what happens if something goes wrong Key Takeaway:AI will not create value in workforce technology simply because it is added as a feature. It creates value when it solves real customer problems, removes friction, provides guidance, protects trust, and helps people get important work done more easily. Naomi’s core argument is that the best workforce products are built around people, not technology. In HR and payroll, where products influence pay, compliance, employment records, and major life moments, innovation must always be matched with accountability. About Naomi Lariviere:Naomi Lariviere is the Chief Product Owner and Vice President at ADP. With over 20 years of experience in technology, product management, software development, customer experience, human capital management, payroll, data analytics, and AI-powered innovation, Naomi brings a deeply human-centered perspective to product leadership.

    Building Trusted AI For The Future Of Work Ft. Naomi Lariviere, Chief Product Owner & VP At ADP

  5. Jul 14

    Enterprise AI Needs A Strong Foundation Ft. Ameet Joshi, BU Head, YASH Technologies Middle East

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Ameet Joshi, BU Head – Enterprise AI, SAP BAIP & Digital Platforms at YASH Technologies Middle East, to explore how enterprises can move from AI pilots and platform investments to real business outcomes.This is not a conversation about adopting AI for the sake of AI. It is a practical discussion on why enterprise AI needs the right foundation, why fragmented data is an architecture problem rather than an AI problem, & why transformation should always begin with business outcomes.Ameet brings a non-linear and deeply practical career journey to the conversation. He started with an entrepreneurial venture at the age of 19, building and scaling a fish food selling business across two cities before formally learning terms such as sales, distribution, marketing, and customer engagement. That early experience shaped one of his lasting principles: build, deliver, and repeat. The conversation turns to talent and the future of technology professionals. Ameet’s advice is clear: stay hungry, stay foolish, keep learning, fail fast, and fall in love with the problem, not the tool. Tools will change, platforms will evolve, and technologies will be replaced. What keeps professionals relevant is deep business knowledge, the ability to solve problems, and the discipline to create outcomes.In this episode, we cover:• How Ameet’s entrepreneurial journey shaped his approach to enterprise transformation• Why transformation should be measured by business outcomes, not technology adoption• How sophisticated technology can fail when the human experience is ignored• Why simple solutions can outperform complex tools when the business problem is clear• Why many AI pilots struggle to scale in enterprise environments• Why fragmented data is an architecture issue, not an AI issue• How SAP BTP helps build the foundation for integration, data harmonization, automation, and AI• Why enterprises should prepare their foundations before chasing more AI use cases• How SAP Joule and SAP Business AI can change enterprise user experiencesKey Takeaway:Enterprise AI will not create value simply because an organization runs more pilots or adopts more tools. It creates value when the enterprise foundation is ready. That means harmonized data, integrated processes, strong architecture, clear business outcomes, and people who understand the problem they are solving.Ameet’s core argument is that transformation is not about technology. Technology creates possibilities, but people create outcomes. SAP BTP, SAP Business AI, Joule, and autonomous enterprise capabilities can help organizations scale intelligence across processes, but only when the business case is clear and the foundation is strong.About The Guest:Ameet Joshi is the BU Head – Enterprise AI, SAP BAIP & Digital Platforms at YASH Technologies Middle East. He leads initiatives across SAP BTP, enterprise AI, SAP Business AI, digital platforms, cloud migration, analytics, mobility, automation, and platform-led business transformation. His journey began with entrepreneurship before moving into technology with SAP Labs India in 2005. Over the years, Ameet has worked across transactional systems, data and analytics, enterprise mobility, cloud platforms, SAP Cloud Platform, SAP BTP, and digital ecosystems involving SAP, Microsoft, Salesforce, and UiPath. At YASH Technologies Middle East, he focuses on helping enterprises modernize foundations, adopt AI responsibly, and create measurable business value through integrated platforms and business-led transformation.

    Enterprise AI Needs A Strong Foundation Ft. Ameet Joshi, BU Head, YASH Technologies Middle East

  6. Jul 13

    Why Enterprise Transformation Fails? Ft. Anshuman Vedi, Founder At Techspire Consulting

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Anshuman Vedi, Founder at Techspire Consulting, to unpack why enterprise transformation programs often struggle to deliver real business impact despite significant investments in technology, advisory, implementation, and modernization. This is not a conversation about technology as the problem. It is a grounded, experience-led discussion on why enterprise transformation often fails because of execution gaps, unclear sequencing, misaligned expectations, complex delivery models, and a lack of hands-on accountability. Anshuman’s core argument is clear: technology rarely fails on its own. Transformation fails when organizations make the journey more complicated than it needs to be. The conversation begins with Anshuman’s professional journey and how his early exposure to engineering, ERP systems, consulting travel, and multinational transformation programs shaped his view of enterprise technology. His experience across Hitachi, Accenture, and EY gave him a front-row seat to the structural gaps that exist between clients, advisors, implementation partners, and delivery teams. A central insight from this episode reframes how organizations should think about transformation. Anshuman argues that transformation must be broken down, sequenced, and delivered with clear ownership. Enterprises often define ambitious benefits before they fully understand the technical and operational reality. When the actual implementation begins, the business case, technology capability, and delivery model may not align. That is where complexity builds and programs begin to drift.In this episode, we cover:• How Anshuman’s journey from engineering to enterprise consulting shaped his transformation philosophy• Why enterprise transformation is rarely a pure technology problem• How consulting, delivery, advisory, and entrepreneurship gave Anshuman a full view of transformation gaps• Why transformation programs fail when benefits are defined before technical realities are understood• How business transformation and technical transformation create complexity when they are not sequenced properly• Why enterprises must maintain continuity, stability, and agility while modernizing• Why AI should be treated as a multiplier, not a standalone solution• How Oracle, SAP, and other enterprise application vendors are embedding AI into real workflowsKey Takeaway:Enterprise transformation does not fail because technology is unavailable. It fails when organizations define ambitious outcomes without enough clarity, sequence business and technical change poorly, overcomplicate delivery, and lose accountability between advisors, implementation partners, technology providers, and internal teams.About Anshuman Vedi:Anshuman Vedi is the Founder of Techspire Consulting, a specialist consulting firm focused on simplifying complex enterprise transformation programs and delivering measurable business impact. With over two decades of experience across enterprise applications, ERP transformation, Oracle Cloud, consulting delivery, advisory, and program leadership, Anshuman has worked across organizations such as Hitachi, Accenture, and EY before founding Techspire Consulting.#EnterpriseTransformation #DigitalTransformation #ERPTransformation #OracleCloud #AITransformation #EnterpriseAI #ConsultingLeadership #TechspireConsulting #AnshumanVedi #EnterpriseModernization #BusinessTransformation #AIInEnterprise #TransformationStrategy #TechDogs #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

    Why Enterprise Transformation Fails? Ft. Anshuman Vedi, Founder At Techspire Consulting

  7. Jul 10

    AI Won’t Replace Work. It Will Redesign It. Ft. Lucy Beaumont, Global SVP Product At SHL

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Lucy Beaumont, Global SVP Product at SHL, to explore how AI, data, and talent intelligence are changing the way organizations understand, develop, and deploy their people. This is not a conversation about AI replacing jobs. It is a grounded discussion on how work itself is being redesigned, how talent decisions are becoming more data-driven, and why organizations must prepare their people before expecting AI investments to deliver real business value. The conversation begins with Lucy’s professional journey and how psychology shaped her understanding of people at work. She explains how the industry has moved from narrow, point-in-time assessments toward broader, always-on views of talent. Earlier, organizations often focused on individual assessments for hiring or leadership selection. Today, the opportunity is to combine multiple signals, data sources, and assessment insights to create a more complete view of talent across the organization. A central insight from this episode is that AI is helping organizations move beyond the old trade-off between precision and scale. Historically, organizations could either make very precise talent decisions for small groups or attempt scalable approaches with less depth. Lucy explains that AI and talent intelligence are now making it possible to achieve both: precise insight into people at enterprise scale. In this episode, we cover: • How Lucy’s background in occupational psychology shaped her approach to talent and product leadership • Why talent decisions are moving from point-in-time assessments to always-on intelligence • How AI is helping organizations achieve precision and scale in workforce decisions • Why hiring is more data-driven than many internal talent decisions • Where intuition still influences promotion, mobility, leadership, and development decisions • Why organizations need a data strategy, not just more people data • How to identify which talent data can be trusted for workforce decisions • Why HR must help embed data into everyday decision-making for managers, leaders, and employees • Why AI transformation requires close collaboration between CHROs and technology leaders • How AI is improving internal mobility, workforce planning, skills mapping, and reskilling pathways Key Takeaway: AI will not simply replace work. It will redesign work. The organizations that succeed will be the ones that understand their people deeply, use trusted data to make better talent decisions, and prepare employees for continuous reskilling, mobility, and change. About Lucy Beaumont: Lucy Beaumont is the Global SVP Product at SHL, where she works across talent intelligence, assessment science, product innovation, workforce strategy, and AI-enabled talent decision-making. With a background in occupational psychology, Lucy has spent her career helping organizations make fairer, more objective, and more scalable decisions about people. #TalentIntelligence #FutureOfWork #AIInHR #WorkforceTransformation #SkillsBasedOrganization #PeopleAnalytics #TalentStrategy #AIReadiness #LeadershipDevelopment #EmployeeMobility #Reskilling #Upskilling #WorkforcePlanning #SHL #LucyBeaumont #TechDogs #DiscoverDialogues

    AI Won’t Replace Work. It Will Redesign It. Ft. Lucy Beaumont, Global SVP Product At SHL

  8. Jul 2

    Staying Human In An AI-First Workplace Ft. Laura Thiele, CPO At Optimizely

    In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Laura Thiele, Chief People Officer at Optimizely, to explore what it truly takes to lead people, culture, and organizations through an AI-first world. This is not a conversation about AI replacing work. It is a grounded, human-centered discussion on how leaders can help people absorb change, build new skills, stay engaged, and continue creating value as roles, tools, and expectations evolve.Organizations across the world are racing to become AI-first, but the human impact of that shift is often underestimated. AI is changing workflows, decision-making, skill expectations, business processes, and the role of leaders.Laura brings a deeply practical perspective shaped by nearly 30 years in HR and people leadership. Her journey spans Lockheed Martin, SAP, and Optimizely, where she has worked across recruiting, compensation, HR generalist leadership, systems implementation, people transformation, and business-aligned talent strategy.A central insight from this episode reframes how leaders should think about AI transformation. Laura argues that becoming AI-first is not simply about deploying tools or redesigning workflows. It is about helping people absorb change. Leaders often underestimate the emotional and practical effort required for employees to learn new tools, rethink processes, overcome anxiety, and experiment without fear of failure.Her view of culture is particularly striking. Culture is not a static document or a set of values written on a wall. It is built through everyday actions: how people give feedback, how teams experiment, how colleagues inspire each other, and how leaders create space for learning. In Laura’s framing, a strong culture becomes the inner glue that keeps people connected and motivated during periods of transformation.In this episode, we cover:• How Laura’s journey from Lockheed Martin to SAP and Optimizely shaped her approach to people leadership• Why learning has been the central theme across her career and leadership style• How HR technology implementation taught her the importance of team alignment and transformation readiness• Why leaders must shift from individual achievement to helping teams succeed at scale• What organizations underestimate when they try to become AI-first• Why employees need support, encouragement, psychological safety, and room to experiment with AI• How culture acts as the inner glue that keeps people connected during rapid growth and transformation• Why HR leaders must influence business strategy through a human lens• How AI is changing the way leaders access workforce insights and make people-related decisionsKey Takeaway:The AI-first workplace will not be shaped by technology alone. It will be shaped by leaders who can help people learn, adapt, experiment, and stay connected through change. Laura’s core argument is that organizations must not underestimate the human effort behind AI transformation. Employees need clarity, support, encouragement, and room to make mistakes as they rebuild skills and rethink how work gets done.For Laura, the leaders who will succeed in this next phase of work are not the ones who simply push faster adoption. They are the ones who balance empathy with accountability, connect talent strategy to business outcomes, and build cultures where learning is not forced but genuinely desired. In an AI-driven world, human contribution becomes more valuable, not less. Judgment, empathy, creativity, critical thinking, and the desire to keep learning will define the workforce of the future.About Laura Thiele: Laura Thiele is the Chief People Officer at Optimizely, where she leads the company’s people function across HR strategy, culture, talent development, employee engagement, workforce planning, and organizational transformation.

    Staying Human In An AI-First Workplace Ft. Laura Thiele, CPO At Optimizely
See All (88)

About

Explore candid Interviews, Q&A's with C-suite leaders on strategic leadership and management, Leadership Challenges, and Leadership Accountability.

Information

  • Creator
    TechDogs
  • Years Active
    2025 - 2026
  • Episodes
    88
  • Rating
    Clean
  • Copyright
    © TechDogs
  • Show Website
    Discover Dialogues