Advertise on podcast: TECHtonic: Trends in Technology and Services

What does it take to turn AI from an exciting innovation into a business model that actually delivers value? On this episode of TECHtonic, Thomas Lah walks through TSIA’s AI pricing ladder with Alon Talmor, founder and CEO of Mosaic AI, to unpack how companies can move beyond traditional seat-based pricing and start monetizing the work AI gets done. After selling his first startup to Salesforce and earning a PhD in natural language processing, Alon saw an opportunity to use AI to fundamentally transform technical support and how engineers tackle complex challenges. Alon shares how Mosaic AI takes a different approach to AI adoption, starting with an in-depth look at how support engineers work to identify the highest-impact automation opportunities. Thomas then connects this approach to a bigger question facing technology companies: How do you price AI based on the value it creates? Together, they discuss why understanding the work, defining success with customers, and measuring the right productivity metrics are critical to building an AI business model that works. But pricing is only part of the equation. They also tackle what it takes to drive adoption, bring experienced engineers along on the AI journey, and rethink the economics of software in a world where AI does more of the work. From outcome-based pricing to the future of technical support, this conversation challenges some long-standing assumptions about how technology companies sell and deliver value. The big takeaway? If AI is changing how work gets done, it’s time to rethink how you charge for it.

Technology providers have mastered the art of selling value, but too often struggle to prove it after the deal is signed. In this episode of TSIA’s TECHtonic, Thomas Lah sits down with Steve Zimba, founder of Nulia, and Sue Nabeth Moore, founder of Success Chain, to explore how their teams have come together to build Tivium, a platform designed to bridge the gap between technology adoption and measurable business outcomes. Through their work on value realization, they reveal why product usage alone isn't enough, how activity and performance measurements can connect everyday workflows to business results, and why understanding both realized and perceived value is critical to customer retention and growth. Steve and Sue share how Tivium helps providers track progress, identify customers who may be falling short of expected results, and use those insights to strengthen retention and drive expansion. As AI raises customer expectations for tangible returns on technology investments, the ability to consistently deliver on value promises is becoming a business imperative. The episode challenges providers to rethink the role of customer success, embrace monetizable value-added services, and close the loop between what they build, what they sell, and the outcomes customers actually achieve.

AI is creating a new question for managed services: what happens when the work itself becomes software-driven? On this episode of TSIA’s TECHtonic, Thomas Lah talks with Scott McIsaac, CEO of Helios Core, about the shift from labor-driven IT support to AI-driven operations. Scott brings two decades of managed services experience to the conversation, including leadership roles at Secure-24 and NTT, and shares how customer demand led to the creation of Mira Resolve, an AI-powered platform he describes as an autopilot for IT. The conversation looks at what happens when AI starts doing the work traditionally handled by IT support teams, including how agents can operate across an environment while bringing humans in for the moments that matter. Thomas and Scott also dig into the knowledge-management problem underneath AI adoption, the challenges of pricing AI-driven work, and why buying AI technology alone does not create efficiency. The bigger question is how services organizations adapt their technology, knowledge, and business models when labor is no longer the primary unit of work.

AI is forcing technology companies to rethink what customers are actually paying for, and how they prove the value they deliver. On this episode of TSIA’s TECHtonic, Thomas Lah sits down with Michael Speranza, CEO of Kantata, to explore how AI is reshaping the economics of SaaS, professional services, and enterprise technology. As software becomes easier to build and AI accelerates automation, the code itself is becoming less defensible. The real value is shifting toward industry expertise, data, context, and the ability to turn insights into measurable business outcomes. Thomas and Michael unpack why simple AI automation is quickly becoming table stakes, while predictive and agentic capabilities are opening the door to a new level of value creation. They also examine the growing pressure to move beyond seat-based and time-and-materials pricing toward consumption- and outcome-based models—and why both technology providers and their customers are still figuring out what that transition should look like. The conversation also explores the rise of the hybrid workforce, the changing role of technology services, the importance of reducing time to value, and why the future of enterprise software may not be a choice between standardization and customization, but a new model that combines the two. For technology and services leaders navigating AI, the message is clear: the question is no longer simply what your technology can do. It’s what becomes possible for your customer because of it, and whether you can prove it.

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.

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.

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.

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.

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.

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.

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.

Recorded live at the May 2026 TSIA Board Summit, this executive panel brings together technology and services leaders to explore how AI is transforming the future of customer engagement, professional services, support, sales, and education services. Moderated by Thomas Lah and George Humphrey, the discussion dives into emerging business model trends shaping the technology industry, including forward-deployed engineers (FDEs), AI-native operating models, value realization frameworks, agentic workflows, outcome-based selling, and the evolving role of services organizations in driving revenue growth. Panelists Kusal DeSilva of AptEdge, Prasad Sular of Certinia, Shari Cravens of HPE Digital Experience, Usman Nasir of Salesforce, Fotini Costopoulos of ServiceNow, and Kurt Kuelz of Siemens Digital Industries Software share real-world examples of how leading organizations are restructuring around customer outcomes, why services teams are playing an increasingly strategic role in the sales cycle, and the evolving skills technology professionals will need to thrive in an AI-first economy. This candid, unscripted live discussion captures how leading companies are navigating one of the fastest technology shifts the services industry has ever experienced.

In this episode of TECHtonic, Thomas Lah of TSIA sits down with Michael Harnum, CEO of ESG Success, to unpack a bold idea reshaping the tech industry: Customer Success as a Service. As companies face mounting pressure to cut costs while still driving retention and growth, traditional customer success models are being pushed to their limits. Michael shares how his experience scaling renewal operations and training services led to a broader, more holistic approach—helping organizations not just execute customer success, but design, optimize, and even outsource it. From building maturity assessments to leveraging AI for scalable success plans, the conversation dives into how companies can transform fragmented, underperforming CS functions into strategic growth engines. If you’re grappling with churn, struggling to prove ROI, or wondering how to scale without adding headcount, this episode delivers practical insights and a fresh perspective on making customer success a true driver of business value.

In this episode of TECHtonic, host Thomas Lah sits down with Angelica Riemann, SVP and President of the CrossLab Group at Agilent Technologies, to unpack how a legacy hardware company is transforming into a modern, recurring-revenue powerhouse. From its origins as a spinout of HP to becoming a global leader in lab innovation, Agilent is redefining what it means to deliver value—not just through instruments, but through an integrated ecosystem of services, consumables, software, and digital experiences. Angelica reveals how Agilent is: Building a “flywheel” of recurring revenue across the entire lab lifecycleNavigating increasingly complex buying personas and pricing modelsLeveraging AI and digital tools to transform both customer support and internal operationsShifting from selling products to delivering outcomes and workflow solutionsThe conversation also explores the future of enterprise buying—where frictionless digital experiences, self-service support, and even AI-to-AI transactions are reshaping how customers engage. If you're in tech, services, or any industry facing disruption, this episode offers a powerful look at how to evolve your business model for a world that demands more value, speed, and flexibility.

In this episode of TECHtonic, Thomas Lah sits down with Cormac Whelan, CEO of Nitro Software, to unpack what it really takes to compete, and win, when you’re up against industry heavy weights. As AI reshapes the software landscape, Cormac shares how smaller, more agile companies are using it as a force multiplier, enabling lean teams to innovate faster, deliver smarter products, and “punch above their weight.” But technology alone isn’t the advantage. The real differentiator? Customer intimacy and value realization. Cormac dives into how Nitro leverages deep customer insights to uncover massive efficiency gains, like reducing document redaction from hours to seconds, and turning those insights into scalable, AI-powered solutions. The conversation explores why traditional software models are breaking down, how pricing is shifting toward outcomes, and why proving value is now the ultimate competitive edge. You’ll also hear: Why incumbents still hold power, and where they’re vulnerableHow AI is changing product development, pricing, and go-to-market strategiesThe growing importance of trust, security, and transparencyWhy the future belongs to companies that deliver outcomes, not just softwareIf you're navigating today’s rapidly evolving tech landscape, this episode offers a clear message: the winners won’t be the biggest—they’ll be the most agile, customer-focused, and value-driven.