3367: CGS Reinvents Workplace Training With AI-Powered Role Play

In today’s episode of Tech Talks Daily, I sat down with Andy Bell, Head of Data Product Management at Precisely, to explore a challenge that many organizations continue to underestimate: the role of data integrity in AI strategies. With only 12 percent of businesses expressing confidence in the quality of their AI data, it's clear that the rush to implement AI is often outpacing the readiness of the data that supports it. Andy and I unpack what happens when enterprises leap into generative or agentic AI without addressing foundational data issues. From hallucinations to bias to unreliable outputs, the risks are significant. As we discussed, these risks don’t just impact models — they erode trust with customers and complicate accountability, especially in regulated industries where traceability is non-negotiable. We then explored the power of third-party data enrichment and how it can offer much-needed context that internal datasets often lack. Andy shared real-world examples, including how a major delivery company saved 65 million dollars by optimizing address accuracy and how San Bernardino County used Precisely’s wildfire risk models to improve emergency planning. These aren’t abstract use cases — they show measurable business value. Andy also introduced the Precisely Data Link program, a solution designed to make it easier to connect, manage, and query multiple third-party datasets. With persistent IDs and flexible delivery methods through APIs, managed services, and platforms like Snowflake and Databricks, Precisely is helping organizations speed up time to value while reducing integration headaches. Looking ahead, Andy shared how Precisely is building AI capabilities that allow users to query third-party data using natural language. This shift aims to make complex data interactions more intuitive and accessible to business users who may not be data engineers. If data is the fuel for AI, then the quality and context of that data will define the road ahead. Is your organization doing enough to ensure its data can be trusted by the AI it deploys?

In this episode of Tech Talks Daily, I sat down with Joseph Landes, co-founder and Chief Revenue Officer at Nerdio, to explore how one conversation at a Microsoft conference led to a billion-dollar cloud automation company. From his 23-year career at Microsoft to building a fully remote team now supporting over five million users, Joseph’s story blends strategic risk-taking with deep industry insight. We unpacked how Nerdio grew from a startup idea in 2018 to a company that just secured 500 million dollars in Series C funding. Joseph walked me through the early days of building the business alongside co-founder Vadim Vladimirsky and how they focused on simplifying Microsoft Azure for IT professionals and MSPs. Their goal was clear: make cloud management easier, faster, and more cost-effective through automation and policy-driven governance. But this episode wasn’t just about cloud optimization. We also dug into Nerdio’s fully remote culture and the intentional design behind it. Joseph shared how initiatives like appointing city mayors, launching the Nerdio Break Room, and hosting an annual global kickoff have helped maintain a strong sense of community and accountability across 350 remote employees. We also discussed why Nerdio does not compete with Microsoft. It enhances and extends Microsoft’s products, helping customers navigate Azure complexity while staying aligned with Microsoft's fast-changing roadmap. This customer-centric strategy, coupled with deep product knowledge and agility, has been key to Nerdio’s ability to scale without losing focus. Looking ahead, Joseph shared his perspective on why AI and continuous cost optimization will shape the future of enterprise IT. He made a strong case for simplifying IT operations, empowering professionals, and turning savings into reinvestment opportunities. In an era of complexity and noise, Nerdio’s growth story is a reminder of what can happen when you combine deep platform expertise with a culture that truly listens. How is your organization turning cloud complexity into an advantage rather than a barrier?

The training room is changing, and it's not going back. In this episode, I sat down with Phil Friedman, the founder and CEO of CGS Inc., to explore how AI, avatars, and immersive simulations are rewriting the playbook on workplace training. With over four decades at the helm of CGS—a company he built from scratch after immigrating to the US—Phil brings a perspective shaped by both technological evolution and global business experience. The heart of our conversation centered on Cicero, CGS’s AI-driven platform that blends artificial intelligence with extended reality to create dynamic, real-time role-play simulations. Far from just another e-learning tool, Cicero tackles one of the biggest blind spots in workforce development today: soft skills. From objection handling in medical device sales to flight attendant training and fast-food onboarding, the platform is being used to scale training faster, cheaper, and more effectively than traditional classroom or online methods ever could. What really stood out was how Phil views this as a moment of acceleration rather than disruption. AI isn’t here to replace human trainers or eliminate roles; it's a tool that can deepen learning and speed up how people acquire both interpersonal and job-specific skills. In a world where young workers are more comfortable with gaming engines than whiteboards, the immersive, responsive nature of AI-powered simulations offers a natural fit. Phil shared compelling stories from industries like healthcare, aviation, and fast food, where training time has been slashed from months to days. But more than the metrics, it’s the idea that training can now adapt in real time, simulate unpredictable human behavior, and offer meaningful feedback immediately that points to where we’re headed next. As AI and XR technologies converge, what will it mean when every employee can have a personalized, just-in-time coach at their fingertips?

When we think about gene editing, the conversation often feels trapped between scientific journals and ethical debates too complex for public forums. In this episode, I spoke with Neal Baer, a rare voice who bridges both worlds. Known to many as an award-winning television showrunner for series like ER, Law & Order SVU, and Designated Survivor, Neal is also a Harvard-trained physician and co-director of the Media, Medicine, and Health program at Harvard Medical School. His latest project brings all of that experience together in a new collection of essays that explores the promise and peril of CRISPR gene-editing technology. Neal takes us on a journey that begins with his time as a medical resident treating a young sickle cell patient, and leads to a much broader conversation about science, ethics, and storytelling. We discuss how CRISPR is already being used to cure diseases like sickle cell, and how companies are now exploring gene edits that promise permanent reductions in cholesterol. But the real power of this discussion is not just in what CRISPR can do, but in what we still don’t fully understand about its long-term impact. The conversation moves into difficult territory—unintended mutations, germline editing, the risk of pathologizing human diversity, and the slippery slope of “enhancement” where only those with access can benefit. Neal raises critical questions about the social cost of deciding which conditions should be “fixed” and who gets to make that call. We also dive into the lack of political and regulatory oversight, and why a global framework, not just scientific advancement, is urgently needed. This episode offers a powerful reminder that the future of CRISPR shouldn’t be left solely to researchers or startups. It demands wide engagement, from classrooms to policymaking, and inclusive voices that challenge how we define progress. How should we decide what counts as improvement when the very definition of being human is at stake?

In this episode of Tech Talks Daily, I welcomed back Sumit Johar, CIO at BlackLine, for a timely conversation about how AI is transforming finance operations from the inside out. When we last spoke earlier this year, AI was still in the early stages of enterprise experimentation. Just a few months later, everything has shifted. Sumit shared how AI has moved well beyond pilot programs and into a space where business leaders themselves are actively requesting implementations. What stood out in our conversation was how this change has reshaped the relationship between CIOs and CFOs. The skepticism is fading, and a stronger sense of collaboration is emerging as both sides work together to drive transformation, align strategies, and reimagine outcomes. We explored the growing need for CIOs to be “multilingual”—not in the linguistic sense, but in their ability to navigate both technology and business. It’s no longer enough to speak in code or technical jargon. CIOs must understand finance workflows, end-to-end processes, and the operational pressures CFOs face every day. This alignment is critical when evaluating how and where to deploy AI. Sumit also unpacked some of the core challenges around AI integration, including data quality, long-term sustainability, security, and ethical use. Unlike previous SaaS waves, AI adoption carries more complex risk vectors. Demos might impress, but real-world deployments demand rigorous controls, responsible governance, and the right culture. The conversation covered the ongoing build versus buy dilemma, why it’s context-specific, and how BlackLine approaches those decisions with long-term scalability in mind. Sumit also shared how internal councils and cross-functional collaboration have helped guide AI strategy across the organization. If you’re leading digital transformation or building the next phase of AI integration in your finance or IT teams, this episode offers clear, experience-driven insights. What’s your organization doing to prepare for AI not as a concept, but as a day-to-day operational reality?

In this episode of Tech Talks Daily, I sat down with Boris Bialek, VP and Field CTO at MongoDB, for a conversation that moved well beyond databases. As AI continues to accelerate across sectors, MongoDB is positioning itself at the intersection of modern data architecture and intelligent application development. Boris shared how his team is simplifying AI adoption for enterprises, with a clear focus on real-world outcomes, developer productivity, and global inclusion. We began by exploring MongoDB’s recent acquisition of Voyage AI. This move extends MongoDB's native capabilities into vector search, embeddings, and re-rankers, allowing developers to build AI-powered applications more efficiently. Boris explained how MongoDB is removing the complexity from AI integration by providing a unified API, collapsing what used to be 18 disconnected tools into a streamlined developer experience. But the discussion wasn’t just about technology. Boris brought a passionate focus to the issue of financial inclusion. We talked about how AI can enable alternative credit scoring for the 27 percent of adults globally who remain unbanked. By analyzing behavioral signals such as mobile payment histories or utility data, AI can help unlock microcredit opportunities for individuals and small businesses in underserved regions. Boris shared use cases from PicPay in Brazil, M-Pesa in Africa, and Proxtera in Singapore, each demonstrating how AI and MongoDB are enabling new forms of digital trust. We also tackled the organizational and technical hurdles to enterprise AI adoption. From fears about hallucinations to managing constant model updates, Boris described how MongoDB is building systems that prioritize transparency, auditability, and scale. With its document model and integrated tooling, MongoDB offers a stable foundation for companies navigating fast-moving AI transformations. For developers, the platform now includes learnmongodb.com and quick-skill badges designed to make AI approachable and hands-on. And with the upcoming release of Boris’s new book, there’s more to come on how businesses can move from pilot experiments to production-grade solutions. How is your organization rethinking its data strategy to make AI work at scale?

When we think about innovation in technology, power grids rarely enter the spotlight. Yet, they are the foundation for everything from artificial intelligence to electric vehicles and data centers. In this episode, I spoke with Adrian Guggisberg, President of the Smart Power Division at ABB, to unpack the evolving role of electrical power distribution in a world shifting rapidly toward digital infrastructure and clean energy. Adrian joined me from Zurich to share how ABB is helping grid operators navigate an increasingly complex landscape. With rising pressure from extreme weather, surging energy demand, and growing decentralization of power sources, the traditional grid model is being challenged on multiple fronts. We explored recent high-profile outages like the Heathrow disruption and the cascading blackouts in Spain and Portugal, and what these incidents reveal about systemic vulnerabilities. What stood out was Adrian’s clear message that resilience is no longer optional. He walked me through how switchgear plays a vital role in controlling flow, isolating faults, and restoring power with precision. Rather than waiting for outages to happen, ABB is championing a smarter, decentralized approach that supports microgrids and localized decision-making. The transition to intelligent infrastructure requires investment, digital tools, and collaboration across public and private sectors. We also discussed the cultural and political shift required to truly modernize the grid. Adrian pointed out that while grid operators understand the urgency, public awareness and policymaker support will be key to driving progress. His optimism came through clearly, especially when he talked about ABB’s purpose in powering a more sustainable future. If energy is the backbone of society, then conversations like this are the starting point for building something stronger. What would a smarter grid mean for the communities and industries you serve?  

In a digital-first world where cybersecurity often dominates headlines, the conversation around physical security can sometimes feel like an afterthought. But what if technology could bring a new level of intelligence, proactivity, and efficiency to protecting real-world environments? In this episode, I sat down with Ryan Porter, co-founder and CEO of LVT, to learn how his team is reshaping physical security through innovation rooted in both technology and field experience. What began in Ryan’s garage as a way to monitor construction projects through live video has evolved into a powerful enterprise platform used by 30 of the Fortune 50. LVT provides mobile security units equipped with cameras, lights, solar power, and edge-based AI capabilities that don't just observe but actively deter criminal behavior. From parking lots to retail environments, and even the Super Bowl, LVT’s presence is being felt wherever safety is at risk. Our conversation uncovered how LVT’s approach differs from traditional reactive security models. Rather than reviewing footage after incidents happen, LVT creates controlled environments designed to prevent events before they occur. This shift toward deterrence, combined with a visible and multi-sensory presence, is producing measurable results. In cities like Paducah and Opelika, LVT’s Access Task Force program contributed to a ten percent reduction in citywide crime. We also explored how the company overcomes the challenges of deploying AI in environments with limited power and bandwidth. By running intelligent models on edge devices, LVT delivers real-time insights in places that lack the infrastructure for heavy cloud computing. The result is a system that delivers value instantly, improves business intelligence, and enhances community safety. This is not just about technology for its own sake. It is about building systems that serve people, keep environments secure, and foster collaboration between businesses, law enforcement, and local communities. How are you using technology to create safer, smarter spaces in the real world?

In today’s episode of Tech Talks Daily, I connected with Brittany Christenson, CEO of AidKit, to explore how cutting-edge technology is being used not to disrupt markets or chase margins, but to deliver real, measurable social impact. AidKit is a public benefit corporation building infrastructure that helps vulnerable communities access aid quickly, securely, and with dignity. While many tech conversations orbit around scale and efficiency, Brittany brings a different kind of energy, one grounded in values, user empathy, and purpose-built innovation. She shared how AidKit’s journey began as a nonprofit initiative during the pandemic, evolved into a for-profit startup to attract engineering talent, and most recently achieved B Corp certification, reinforcing its long-term commitment to balancing people, planet, and profit. We discussed what dignity and equity look like in real-world software experiences, and how user-centric design can transform burdensome forms and gatekeeping processes into streamlined, accessible interfaces that actually work for people in need. Aidkit doesn’t stop at technology. Their model also includes multilingual support, advisory councils made up of program beneficiaries, and robust fraud prevention tools that protect both funds and privacy. One of the standout takeaways was how Brittany views trust and transparency as core features, not afterthoughts. Governments rely on Aidkit to deliver programs with high stakes and public scrutiny, and that trust is earned through a combination of technical competence, clear communication, and reliable systems. AidKit is already supporting over 200 agencies and nonprofits, has processed more than half a million applications, and recently surpassed 330 million dollars in aid disbursements, including nine million dollars in a single week. This conversation is not just about scaling a social impact startup. It is about leading with conviction, refusing to compromise mission for growth, and using the best of what technology offers to serve communities with care. How can your tech strategy support social outcomes without losing sight of the people it's built for?

When we talk about the future of enterprise software, AI is front and center. But behind the buzzwords, real transformation is happening in how businesses plan, execute, and deliver professional services. In this episode, I sat down with Raju Malhotra, Chief Product and Technology Officer at Certinia, to explore how AI is shifting from theory to practice in high-scale environments. Certinia, a native ISV on Salesforce, is helping global tech and service firms like Cisco, Siemens, and PwC automate their services operations. With over two million users and six million active projects, the platform isn’t just adding AI for the sake of it. It’s embedding it directly into workflows to solve tangible business challenges. Raju shares a clear framework for understanding how different types of AI are being implemented. Predictive AI is already deeply integrated into enterprise processes. Generative AI is gaining traction for simplifying content and communication. Agentic AI, the most recent frontier, enables digital agents to complete complex tasks independently within enterprise guardrails. What stood out in our conversation was the emphasis on outcomes over features. Raju makes a compelling case for starting every technology decision by understanding the customer's goals. Certinia’s approach avoids chasing trends for the sake of headlines. Instead, the focus is on delivering results like improved margins, higher resource utilization, and smarter project delivery. We also discussed Certinia's early adoption of Salesforce’s Agent Force and how their team works closely with Salesforce engineering to align on AI strategy. Rebranding their ERP Cloud to Financial Management Cloud was another move that reflects their sharper focus on services-centric financials, rather than trying to be everything to everyone. There’s a clear message in this conversation. Innovation in AI must be matched with investment in performance, latency, scale, and user experience. For any tech leader navigating the AI landscape, Raju’s insights provide a grounded, real-world guide. How are you aligning your AI investments with measurable business outcomes?