Leaders explore AI in the $8.7 trillion distribution sector
The inaugural Applied AI Symposium at Texas A&M University united distribution industry experts and policy makers to examine how organizations can move artificial intelligence from experimentation to enterprise-wide impact.
Teesee Murray provides concluding remarks at the symposium.
As organizations across industries race to integrate artificial intelligence into their operations, Texas A&M University is helping shape the conversation around what it takes to build AI-ready workforces and translate emerging technologies into a lasting competitive advantage.
To advance that discussion as it applies to the wholesale distribution sector, Texas A&M hosted the inaugural Applied AI Symposium on June 10, bringing together leaders from business, government and academia to explore how distributors can move AI from experiment to enterprise scale. The event was a joint effort between Texas A&M, the National Association of Wholesaler-Distributors and the Applied AI Consortium, with presenting sponsors InstaLILY.ai and SAP America.
The collaboration arose through Texas A&M’s Artificial Intelligence for Industrial Distribution research consortium, part of the Thomas and Joan Read Center for Distribution Research and Education.
Dr. Malini Natarajarathinam, director of the Read Center and Texas A&M industrial distribution professor and program coordinator, said the symposium was designed to create meaningful dialogue among leaders navigating similar challenges.
“Moving the needle on important topics most often doesn’t happen on large stages in front of thousands, but rather with focused, genuine conversations among leaders who are navigating the same inflection points from different vantages and who have a lot to learn from one another,” she said.
Texas A&M’s role in advancing AI innovation
Opening the symposium on behalf of the College of Engineering and the Texas A&M Engineering Experiment Station (TEES), Dr. Jodie Lutkenhaus highlighted the university’s growing investment in artificial intelligence research and education.
She pointed to the Texas A&M University System’s recent launch of a $45 million NVIDIA DGX SuperPOD, one of the highest performing AI supercomputers at any North American university. Combined with future investments in next-generation computing infrastructure, the initiative positions Texas A&M as a hub for AI research and workforce preparation.
Lutkenhaus described the symposium as reflecting the commitment of the university, its college of engineering and its industrial distribution program to connecting industry leaders and policy makers as organizations adapt to rapidly changing technological landscapes.
AI as a core business capability
A recurring theme throughout the day was the idea that AI is no longer a standalone technology initiative but a foundational capability that must be integrated into business strategy.
Konrad Konarski, trustee and chairperson of the Applied AI Consortium, described AI as a disruptive innovation that will reshape virtually every aspect of business. He encouraged organizations to experiment quickly, learn fast and adapt as technology changes.
“The organizations that succeed will be those willing to challenge established ways of working and redesign how value is created, decisions are made and work gets done,” he said.
Dr. Satyam Priyadarshy, retired chief data scientist at Halliburton and trustee of the Applied AI Consortium, challenged attendees to view AI not as a capability layered on top of existing systems, but as the connective tissue between finance, supply chain, customer data and operations.
“AI by itself is already dead,” he said. “You have to think business first, technology second.”
Priyadarshy asserted that the organizations winning in the transition to AI will not be the ones with the most sophisticated models, but those that start with the simplest, most explainable models tied directly to business value.
Aligning strategy, policy and workforce readiness
Speakers emphasized that as AI adoption accelerates, organizational success depends on leadership and culture as much as technology.
Tony Sauerhoff , executive director and chief information officer for the State of Texas, said organizations that thrive will be those that connect AI initiatives directly to strategic priorities and workforce development efforts.
“AI is no longer a technology conversation,” he said. “It is a leadership conversation.”
Panelists discussed how regional economies, public institutions and private organizations can position themselves to compete in an increasingly AI-driven environment. While public policy conversations often focus on long-term vision, attendees noted that leaders today must make practical decisions about talent, governance and organizational readiness.
Holton Stringer, associate vice president at Van Scoyoc Associates and federal AI policy expert, advised to not wait for federal guidance before building governance practices and that businesses should quickly implement AI literacy courses for their workforce.
Designing organizations for an AI-augmented workforce
Participants explored how AI is changing the nature of work itself. While early conversation around generative AI focused heavily on productivity tools, speakers suggested the deeper transformation lies in how organizations redesign workflows, decision-making structures and leadership roles as AI capabilities expand.
“The line between technical and business roles is collapsing,” said David Wascom, industry executive advisor for SAP Americas and faculty member in Texas A&M’s Master of Industrial Distribution program. “Reliance on purely technical skills is shrinking. Problem solving and adaptability aren’t just valuable anymore, they’re mandatory.”
Amit Shah, CEO of InstaLILY.ai, explained that successful AI adoption is not so much a skillset outcome as a mindset outcome. He shared how AI has opened the ability to create the ultimate productivity improvement but has also opened the idea that you can work on many things simultaneously. He said what you choose to do as a company is equally as important as the skills on your team.
“I think there is an arms race to just think about how to build an AI workforce, or how do I transform my company,” he said. “People are not asking the more foundational question of what mindset do I need.”
He encouraged leaders to rethink how work is organized and to approach AI transformation from a first-principle basis rather than simply layering new technologies onto existing processes.
Date readiness as a journey
Another key theme was the importance of acting despite imperfect conditions.
Elias Brown, North American data manager for Vallourec, compared AI adoption to Tesla’s Autopilot technology, suggesting that the relevant question with AI isn’t if it’s perfect yet, but rather if you’re comfortable enough to take your hands off the wheel.
Participants agreed that waiting for data to be perfect is unlikely to be a successful strategy. Instead, leaders must build organizational capacity while continuously improving the quality of their data, processes and governance.
Looking ahead
Organizers intend for the Applied AI Symposium at Texas A&M to become an ongoing forum for collaboration among industry, government and academia.
“Industry is hungry for AI strategy and solutions that can impact the day to day,” said Natarajarathinam.
Teesee Murray, Turtle’s chief strategy officer and president, echoed the importance of continued collaboration.
“Learning is done best through networks,” she said. “My challenge to every executive here is to carry this conversation forward. This is a voyage into uncharted territory, and we need each other to navigate it.”
The symposium worked to reinforce Texas A&M’s role as a leader at the intersection of technology, workforce development and industry transformation. As artificial intelligence continues to reshape organizations and economies, university leaders emphasize the importance of collaboration across sectors to prepare the workforce of the future.
