TECHtonic: Trends in Technology and Services

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.

Recorded live at the 2026 TSIA Board Summit, held in May, Thomas Lah delivers a provocative and insightful keynote on why the AI era is forcing companies to fundamentally rethink their operating models, pricing strategies, and service organizations.
Drawing from nearly 30 years of experience advising global product companies, Thomas explains why today’s AI transformation is moving faster — and carrying higher stakes — than any previous business shift, including the rise of the internet and the move to “as-a-service” business models.
In this session, he introduces the “Services 2.0” framework: a practical model for navigating AI-driven business transformation while overcoming the two biggest obstacles companies face — organizational inertia and flawed business assumptions. He explores why outcome-based pricing is rapidly becoming unavoidable, how customer value delivery is evolving, and why service organizations are increasingly becoming central to enterprise growth strategies.
Thomas also shares research-backed insights into why most transformations fail, the leadership mindset required to succeed, and the specific operational capabilities companies must build now to remain competitive in the AI economy.