TECHtonic: Trends in Technology and Services

Hosted by Technology & Services Industry Association

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Episodes

135

Latest episode

Aug 2026

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EN-US

About the show

Join host Thomas Lah as he discusses shifts in the ever-changing technology industry with tech executives, researchers, and thought leaders who share their experience and provide their perspective and data on what companies should do to stay relevant, be profitable, and succeed.

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60 recent

July 26, 2024Episode 81507262440 min

TSIA Takes: Gainsight on How to Redefine Customer Success

On this episode of TECHtonic, Thomas asks hard questions about the shifting landscape of customer success with Nick Mehta, CEO of Gainsight. Inspired by a provocative chapter in Frank Slootman's "Amp It Up" that questions the necessity of customer success, Thomas and Nick explore the current debates and future directions of this critical business function. Nick shares his insights on why customer success is more vital than ever, especially as technology companies face increasing pressure to prove their business value. From the historical context of customer success a decade ago to today's innovative strategies, Nick discusses the integration of AI, the importance of verticalization, and the evolving roles within customer success organizations. Listeners will gain valuable perspectives on how to leverage AI for better customer experiences, early warning systems, and productivity enhancements. Nick and Thomas also tackle the challenge of balancing cost efficiency with maintaining the core capabilities of customer success teams and the necessity of adopting a beginner’s mind in the face of seismic industry shifts. Tune in to receive actionable advice and discover how you can stay ahead in the debate on the value of customer success and prepare your organization for the future.

July 12, 2024Episode 8007122446 min

TSIA Takes: Salesforce and the Customer Success + Support Services Experiment

Join us for the first episode of TSIA Takes, a limited TECHtonic podcast series. During this series, Thomas Lah dives deep into the pivotal question: What is the value of customer success? This pressing question has turned the customer success organization upside down as it navigates what the future of its business looks like. In this episode, Thomas is joined by Jim Roth, President of Customer Success at Salesforce, who discusses Saleforce’s pioneering approach to integrating customer success, support, and training into a seamless, unified experience. They explore the dynamic roles within Salesforce, emphasizing the importance of customer success managers (CSMs) as orchestrators who ensure comprehensive customer support. Jim shares how Salesforce's strategy of merging support, training, and success roles leads to a more streamlined and compelling customer experience. This allows Salesforce to leverage data to drive customer health, adoption, and education and create a unified customer success score that guides its strategies. They also discuss the financial models behind customer success, debating the merits of monetizing versus offering services as part of the overall customer experience. Jim provides a compelling argument for why tech companies should consider customer success a critical investment rather than a cost center. Whether you're a tech industry veteran or new, this episode offers insights to elevate your understanding of customer success. Take advantage of this first episode of our TSIA takes special podcast series, which challenges conventional wisdom and provides a fresh perspective on making your customer success business model successful.

November 3, 2023Episode 202363514 min

Bonus Episode AI Capabilities Integrations: Stay Ahead of the Curve

With a wealth of practical expertise between them, TSIA's Thomas Lah and George Humphrey, Distinguished VP & Managing Director of Offering and Delivery Research, delve into the transformative impact of AI on technology business models. They focus on three pivotal dimensions: Data-Driven Decision-Making Efficiency and Cost Reduction Enhanced Customer Experience Emphasizing the urgency for companies to effectively organize around AI, they discuss the risks of stagnation in the face of rapid technological advancements. They stress the need for proactive strategies and highlight the potential dangers of irrelevance and diminished competitiveness for companies that fail to strategically embrace AI-driven transformations. Take the first step on the Enterprise AI in Technology and Service Operations Research Journey by completing the TSIA Quick Poll: Organizing for AI Success , enabling leaders to remain at the forefront of how AI is reshaping the technology industry. Gain valuable insights, stay informed, and be part of the transformative conversation that is shaping the landscape of technology businesses worldwide.

August 21, 2026Episode 13333 min

133. Beyond the Blunt Instrument: Why “It Hallucinated” Isn't an Answer

What happens when an AI agent fails, and how can enterprises prove they saw it coming? On this episode of TSIA’s TECHtonic, Thomas Lah takes on one of the most important questions facing organizations moving AI from experimentation into the enterprise: How do you prove that AI is actually delivering the outcomes you promised? Drawing on TSIA’s Five Proofs of Outcome-Based Revenue, Thomas and guest Sekhar Sarukkai unpack why proof of performance and telemetry are becoming essential to proving business value. Sarukkai, a serial entrepreneur who previously founded Skyhigh Networks and Securent, now leads Chatsee.ai, which recently raised $6.5 million to build what he calls a failure intelligence layer for AI agents. The conversation takes a revealing look at what really goes wrong when AI agents enter the real world. After analyzing 10,000 enterprise agent failures, Chatsee identified 157 distinct failure categories, and found that hallucinations account for less than 10% of actual failures. Instead, enterprises are facing bigger and often invisible challenges around resolution, escalation, silent execution, and the growing gap between pre-deployment controls and runtime governance. Thomas and Sekhar also unpack the hidden economics of AI failure, including how a seemingly minor error can quietly spread through downstream systems for weeks. Sekhar introduces a framework for measuring direct loss, propagation, detection delay, and reversibility, while making the case for shared accountability across enterprises, AI platforms, and integrators. If your organization is serious about moving AI agents into production, and proving the value they deliver, this is a conversation you’ll want to hear.

August 7, 2026Episode 13248 min

132. Rerouting Around the Accident to Build a New Revenue Model

Thomas Lah opens the episode by describing TSIA's model-driven revenue engine framework: using AI to monitor every customer touchpoint in real time instead of running revenue off CRM fields and pipeline reviews. His guest, Stephen Messer, has spent three decades living that shift firsthand. Messer co-founded LinkShare in the 1990s, and later co-founded Collective[i], the AI sales intelligence network the Wall Street Journal has compared to Waze for sales. Messer argues that most AI investment in sales, from chatbot-assisted CRM entry to faster email drafting, is being layered onto a system that was never built around the buyer. He explains how Collective[i] models buying committees, introduces sequencing, and maps the hidden relationships driving each deal. The conversation also challenges one of sales' longest-standing practices: forecasting. Messer argues that traditional forecast calls are little more than weekly guesswork that consumes valuable selling time without improving accuracy. In its place, he outlines an AI-first approach that provides a dynamic, daily view of deal health, highlighting what's changed, why it changed, and where sales teams should focus next. Like a navigation app that constantly recalculates the fastest route, AI helps revenue leaders adapt to changing buyer behavior as it happens.

May 29, 2026Episode 13143 min

127. Your Customers Have Been Telling a Story. AI Can Finally Read It.

Your CRM knows what happened. It doesn’t know why—or what’s about to happen next. That gap is costing revenue teams millions in preventable churn, missed expansion, and deals that slip away long before anyone saw it coming. In this episode of TECHtonic, TSIA Executive Director Thomas Lah sits down with Alok Shukla, CEO and co-founder of Funnel Story, to explore a new category of technology: the AI-powered revenue intelligence layer. Unlike traditional CRM dashboards that report on structured activity data in a single point in time, Funnel Story’s patented composite model combines structured data (usage, revenue, activity), unstructured conversational data (calls, emails, notes), and third-party market signals—then reverse-engineers your full historical timeline to train itself from day one. Median deployment time: less than a day. Alok introduces the concept of “needle movers”—AI-detected early warning patterns that surface months before churn or expansion become visible to any human. He shares a compelling real-world example where signals from three different organizational levels (an executive conversation, a support ticket, and a CSM interaction) were silently pointing to competitive risk—patterns that only emerged because of historical churn analysis. Without the intelligence layer connecting those dots, the account would have been marked “healthy” right up until it churned. Drawing on his 20+ years in cybersecurity (McAfee, Intel Security, Imperva), Alok makes a powerful analogy: the Security Operations Center went from 80% people / 20% tech to nearly the inverse over 20 years—and that transformation is now coming for revenue and CS organizations. The leaders who will thrive are those who start thinking now about what it means to manage a fleet of agents rather than a team of reps.

July 24, 2026Episode 13140 min

131. Psychological Safety Is Your AI Strategy

Thomas Lah welcomes social psychologist Sarah DiMuccio to talk about the human side of AI transformation. They dig into why AI adoption triggers anxiety across every role, seniority level, and demographic: it isn't resistance to a task, it's a threat to how people see themselves professionally. Sarah explains that companies are investing heavily in AI technology while investing almost nothing in enablement, treating adoption as something that happens automatically once the tool is switched on rather than a genuine redesign of how people work. That gap shows up as “quiet checkout,” a form of disengagement Sarah argues is more damaging than outright sabotage because it's invisible to leadership and never gets addressed. The conversation turns to what actually builds trust and follow-through: naming the fear directly instead of talking around it, leaders modeling experimentation in front of their teams, and co-creating AI use cases with employees rather than imposing them from the top down. Sarah introduces her framework for future-ready leadership, a Venn diagram of AI fluency, strategic agility, and relational intelligence, arguing that leaders missing the relational piece may retain talent short-term through “golden handcuffs,” but they lose the honesty, experimentation, and judgment that AI-era competitiveness actually depends on.

July 10, 2026Episode 13034 min

130. Beyond Billable Hours in Professional Services with Certinia

In this episode of TECHtonic, Thomas Lah welcomes Deb Ashton, Founder of Certinia, for a conversation about the transformation of professional services in the age of AI. They explore why traditional utilization-based business models are giving way to outcome-driven engagements, how AI is changing pricing, delivery, and workforce strategies, and why customer value must become the foundation of every services organization. Deb shares practical insights from working with technology companies that are embracing AI to streamline delivery while empowering consultants to focus on strategic guidance, governance, and customer relationships. Together, they discuss the rise of Professional Services 2.0, the importance of measuring time-to-value and business outcomes, and what leaders must do today to build more scalable, profitable, and customer-centric services organizations.

June 26, 2026Episode 12943 min

129. The AI Bill Is Coming Due: Making Enterprise AI Profitable

AI is changing everything—but there's one part of the conversation many organizations still aren't having: the economics. As enterprises race to deploy copilots, agents, and generative AI across every department, leaders are discovering that AI costs don't arrive as a single invoice. They show up across GPUs, token consumption, cloud infrastructure, data platforms, and idle compute resources, making it difficult to understand whether AI investments are actually delivering business value. In this episode of TECHtonic, TSIA Executive Director Thomas Lah sits down with Kunal Agarwal, CEO and co-founder of Unravel Data, to discuss why AI FinOps has become one of the most important disciplines for enterprise technology leaders. Kunal explains how organizations can optimize prompts, right-size AI models, eliminate wasted GPU capacity, and gain real-time visibility into the full AI technology stack. Together, they explore why AI should no longer be treated as a science experiment, how leading organizations are creating headroom to fund continued innovation, and why the companies that combine AI ambition with financial discipline will become tomorrow's AI-native market leaders. If you're responsible for AI strategy, cloud operations, infrastructure, finance, or technology investments, this episode offers a practical roadmap for balancing innovation with profitability—and ensuring your AI initiatives deliver measurable business outcomes.

June 12, 2026Episode 12836 min

128. SIGNAL Over Noise: AI, Convergence, and the End of Siloed Service

In this episode of TECHtonic, host Thomas Lah, EVP and Executive Director of TSIA, sits down with Agam Vasani, former SVP of Customer Experience at LeanData, to explore what it actually takes to build an AI-driven post-sale organization. Agam shares how his team was drowning in over 40 fragmented customer health signals, leaving CSMs spending more time assembling data than acting on it. He then reveals how they used AI to consolidate those signals into a single, coherent view that reps could actually use.He also breaks down the SIGNAL framework, a six-part filter he developed to cut through a crowded AI vendor market and evaluate tools on source of truth, intelligence quality, go-to action, workflow fit, team-wide adoption, and continuous learning. Discover how peer-driven "AI jams" drove grassroots adoption where top-down mandates failed, and why most AI tools fall short because they're sold like SaaS when AI behaves nothing like it. Don't miss this candid conversation on what separates AI deployments that move the needle from ones that just add another tool to the stack.