AI Is Here, But Is Your B2B Business Ready?
AI is transforming B2B commerce, but only for companies that have built the right foundation. In this episode of Lessons for Tomorrow, guest host Brendan Cameron, Head of Manufacturing and Distribution at Americaneagle.com, sits down with Aaron Sheehan, VP of Strategy and Partnerships at OroCommerce, to separate hype from reality. As AI adoption accelerates across industries, manufacturers and distributors face both massive opportunity and real complexity. Drawing from real-world implementations, Brendan and Aaron break down the biggest mistakes companies make, what's actually working, and what B2B teams must build now to stay competitive.
For captions, click "CC" within the video player. To read the transcript of this episode, click the transcript link within the description of the video on YouTube.
Where AI Actually Fits in B2B Manufacturing & Distribution
Across B2B manufacturing and distribution, AI has become a practical tool embedded in everyday workflows, not a standalone solution. Modern AI systems, especially large language models, excel at understanding user intent and transforming unstructured data into structured, usable formats. This is critical in B2B environments filled with SDS sheets, purchase orders, pricing files, and potentially decades of fragmented documentation. AI can streamline product data enrichment, improve search accuracy, and support sales teams with faster quoting and insights. Unlike B2C, B2B relies heavily on complex, often messy data sources, making AI particularly valuable in organizing, interpreting, and activating information that was previously siloed or inaccessible.
The #1 Question B2B Leaders Are Asking About AI
The most common questions B2B leaders ask about AI center on two things: “How real is this?” and “How can it actually help my business?” With heavy hype and investment flooding the space, many are unsure what’s practical versus exaggerated. Leaders want to know where AI can deliver real improvements, whether through automation, better customer experiences, or reducing operational friction. At the same time, there’s tension between the fear of falling behind and the risk of investing too early without the right foundation. Much like early internet adoption, most organizations are still in the early stages, trying to understand how to apply AI in meaningful, results-driven ways.
Garbage In, Intelligence Out: Why Data Is Everything
AI is only as effective as the data behind it. The adage “garbage in, garbage out” still applies. Many B2B organizations rush into AI without first building a strong data foundation, leading to poor results and wasted investment. Product information is often scattered across PDFs, spreadsheets, and internal knowledge, making it difficult to use effectively. Distributors frequently receive incomplete or unclear product data, requiring significant enrichment before it’s usable. Before adopting AI, businesses must define clear use cases and ensure their data is clean, structured, and centralized. In many cases, improving data quality delivers faster ROI than implementing AI, because it enables both digital commerce and future AI success.
How OroCommerce Has Evolved with AI
OroCommerce has evolved from a traditional ecommerce platform into a more intelligent commerce engine by layering AI on top of a strong data and context foundation. Rather than replacing core functionality, AI enhances it, using rich customer, product, and order data to deliver smarter search, personalized recommendations, and more automated workflows.
This shift enables application-based buying, where customers describe problems instead of searching SKUs. It also empowers newer sales reps with instant insights, reducing reliance on years of experience. The result is a more efficient, intuitive buying experience that improves conversions, builds trust, and better serves both customers and internal teams.
The AI Use Case B2B Companies Should Avoid (For Now)
One AI use case B2B companies should approach cautiously is fully autonomous purchasing and “agent-led commerce.” While the concept is compelling, most organizations aren’t ready to hand over complete buying decisions to AI. B2B transactions involve approvals, frequent order changes, and high stakes, where mistakes can be costly. There’s also a lack of accountability, as AI systems still operate like black boxes. Trust, accuracy, and human oversight remain critical. Instead of full automation, businesses should focus on AI-assisted workflows that reduce friction, support decision-making, and enhance both customer and employee experiences, keeping humans firmly in the loop where it matters most.
What AI Will Make Obsolete & What Will Become Invisible
Over the next few years, AI will quietly shift from a visible feature to a fully embedded part of everyday B2B operations. Manual data entry, rigid catalogs, and traditional keyword-based search will begin to fade, replaced by more dynamic, AI-assisted experiences. Natural language interactions, predictive recommendations, and application-based buying will become standard. However, this evolution will be balanced by growing concerns around data privacy, security, and control. As AI becomes more powerful, businesses and users alike will demand stronger safeguards, leading to tighter data governance. Ultimately, AI won’t disappear, it will become infrastructure, seamlessly powering workflows while remaining largely invisible to the end user.
The One Lesson B2B Leaders Need to Take Away
The key takeaway for B2B leaders is simple: AI is not the goal. Better business outcomes are.
Treat AI as part of a long-term process, not a quick fix or box to check. Real success comes from improving data quality, governance, and internal workflows before layering in AI. While the technology has transformative potential, it requires thoughtful implementation, testing, and iteration to deliver value. Companies should focus on solving real problems, measuring outcomes, and ensuring user adoption rather than chasing hype. AI is powerful, but it’s not magic. Achieving success will still come down to disciplined strategy, strong foundations, and consistent execution over time.
Turning AI from Buzzword into Business Value
AI in B2B commerce is most valuable when grounded in reality, not hype. While the technology offers powerful capabilities—from data transformation to smarter customer experiences—its success depends on strong foundations and clear use cases. Companies that take a thoughtful approach have a real opportunity to gain efficiency and competitive advantage. The path forward starts with auditing and organizing your data, then identifying one or two high-impact areas where AI can deliver measurable results. From there, build momentum through testing and iteration. The businesses that win won’t be the fastest adopters, but the ones who apply AI with purpose, discipline, and a focus on real outcomes.
Listen to Lessons for Tomorrow, Today!
Start listening on Apple Podcasts, Spotify, or wherever you get your podcasts. You can also watch the episode recorded in the Americaneagle.com Studios on YouTube.
This podcast is brought to you by Americaneagle.com Studios.
Connect with:
- Lessons for Tomorrow: Website // Twitter // Instagram // Facebook // YouTube
- Brendan Cameron: LinkedIn
- Aaron Sheehan: LinkedIn
- Resources: OroCommerce – Website | OroCommerce Development Partner
About: The Lessons for Tomorrow podcast is centered around conversations between industry experts sharing insights from the past, to apply in the present, to achieve success in the future. This podcast is the "motivational poster" in your ear; each episode is centered around conversations which motivate you to tackle new initiatives at your organization. We will be talking with some of the best and brightest minds in technology and marketing and will hear from the experts themselves about their latest experiences, their most recent challenges, and the road ahead. Every episode has a different story, a different answer, a different approach.
