Moving Past the Pilot Phase in IoT and AI | HiveMQ's Barry Libert | Internet of Things Podcast

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Dec 16, 2025

Barry Libert, Chairman and CEO of HiveMQ and an accomplished serial entrepreneur, dives into the transition from the pilot phase in industrial IoT and AI. He emphasizes the need for companies to view themselves as data streaming entities and highlights the importance of data quality over model selection. Discussing barriers to scalability, Barry outlines how alignment among different employee tiers and full edge connectivity are crucial. He also advocates for a customer-obsessed leadership mindset, urging businesses to evolve from point solutions to unified intelligence platforms.

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INSIGHT

Think Of Your Company As A Data Stream

Companies must see themselves as streaming-data businesses, not just product makers.
Treat data flows between customers, suppliers, and partners as the core product to enable intelligence and action.

ADVICE

Align Buyers Around Data First

Align technical, strategic, and economic buyers around what data you collect and why.
Start by mapping what data you collect, from whom, where, and what it indicates before choosing technology.

INSIGHT

Fix Data Before Blaming Models

The problem causing model errors is bad data, not the model itself.
Decide what data you need to collect for a given decision before selecting models to avoid hallucinations.

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In this episode of the IoT For All Podcast, Barry Libert, Chairman and CEO of HiveMQ, joins Ryan Chacon to discuss moving past the pilot phase in industrial IoT and AI. The conversation covers viewing businesses as data streaming entities, the importance of understanding one's data collection processes, aligning different tiers of employees to achieve success, the shift from connectivity to AI data platforms, the role of agentic workflows, and the type of leadership required to navigate the evolving landscape of data and AI.

Barry Libert is the Chairman and CEO of HiveMQ. He has spent 40+ years as a board member, CEO, and serial entrepreneur. He founded and exited several businesses, advised more than 350 CEOs, and served on more than 35 boards in his career. Most recently, Barry transformed Anaconda into a unicorn, adding $100M in new ARR in 18 months based on a proprietary open- source/open-core commercialization GTM playbook he co-designed and implemented.

Barry is focused on AI platforms with network effects and data moats. He has co-authored 6 books, 20+ ebooks, and 500+ articles in the WSJ, NYT, HBR, MIT, and Forbes. He has appeared on CNN, CNBC, Fox, NPR, and delivered 500+ speeches to 250,000+ people globally. Barry began his career with McKinsey & Company, was a managing director of John Hancock’s $2B Real Estate Equity arm, and was a partner at Arthur Andersen. Barry is a graduate of Tufts University (BA) and Columbia University (MBA).

HiveMQ is the Industrial AI Platform helping enterprises move from connected devices to intelligent operations. Built on the MQTT standard and a distributed edge-to-cloud architecture, HiveMQ connects and governs industrial data in real time, enabling organizations to act with intelligence. With proven reliability, scalability, and interoperability, HiveMQ provides the foundation industrial companies need to operationalize AI, powering the next generation of intelligent industry. Global leaders including Audi, BMW, Eli Lilly, Liberty Global, Mercedes-Benz, and Siemens trust HiveMQ to run their most mission-critical operations.