A different format from traditional conferences
The hosts opened with a recap of the 2026 Master B2B Mindshare Summit, held at the University of Chicago on March 10th and 11th. Now in its fourth year, the event brought together approximately 200 B2B digital leaders from manufacturers and distributors across industries.
The format is intentionally different from traditional conferences. Instead of a trade show floor with booths and badge scanning, the summit uses roundtable discussions where practitioners and solution providers work together on real problems. Brian noted that this approach initially faced resistance from solution providers who expected the usual booth-and-scan model, but after four years, nobody is asking for it back.
Practitioners know their circumstance and they know it really well, but they don’t know anybody else’s circumstance very well. Solution providers have what I call the God view where they get to see multiple implementations.
Andy Hoar, Master B2B
Similar challenges across different industries
The summit included attendees from companies like Motion Industries, Lipton Teas and Infusions, HB Fuller, Restec, Affiliated Distributors, ULE Group, and Schneider. Despite operating in vastly different industries, the challenges they discussed were remarkably similar.
Every company is thinking about AI adoption. Every company is thinking about staying relevant in the age of LLMs. Data quality, organizational alignment, hiring, getting sales team buy-in, and preventing implementations from failing appeared as recurring themes across all 24 roundtable sessions.
The hosts counted 24 breakout discussions over the two days, each with 15 to 20 people. Topics ranged from negotiating with Amazon Business to solving data problems to hiring strategies. Brian noted that facilitating one of the roundtables on Amazon Business produced three pages of notes, with manufacturers generating over $100 million on Amazon sharing perspectives alongside major distributors.
AI is saving money through avoided hiring, not layoffs
Andy ran a roundtable on making money versus saving money with AI. The discussions revealed that most companies are not laying off employees because of AI. Instead, they are choosing not to fill positions they had planned to hire for, or shifting employees into different roles.
The difficulty of attributing revenue gains to AI came up repeatedly. Cost savings are easier to measure: a position not filled is a concrete number. Revenue gains invite attribution debates where sales, customer service, and digital teams all claim credit for the same lift.
One recurring theme was the distinction between production and productivity. Several attendees mentioned that AI allows them to produce more content, but when asked whether the content was good, they acknowledged it was not as good as before. Producing more is not the same as producing better, and the hosts argued that conflating the two leads to a form of information slop that does not serve customers.
Answer-engine optimization as the next frontier
A workshop on answer-engine optimization (AEO) with Ntara was described by multiple attendees as eye-opening. The exercise involved searching for company products in various LLMs and observing what appeared.
Several attendees discovered problems they did not know existed. Some found false information about their companies. Others found competitors’ products appearing when their own should have been recommended. One attendee from a school furniture supplier asked an LLM for a chair for a middle school science student and received a recommendation for an office chair instead, because the product content was not tagged for the correct use case.
The phrase I heard repeatedly was eye-opening. Because many of them did not realize how they were being characterized in these LLMs.
Andy Hoar, Master B2B
Early movers in LLM optimization will have lasting advantage
Brian compared the current state of AEO to the early days of SEO around 2005, when a new website could rank number one in Google within two weeks for a furniture category. The opportunity is similar with LLMs, but the hosts warned that the window will not stay open forever.
Andy noted that LLMs tend to favor content with longevity and permanence. Companies that establish accurate, well-structured content now will build an accumulated advantage. Getting it wrong in the present not only hurts current visibility but creates a deficit that will be harder to overcome as the engines mature.
One practical insight from the workshop: ask the LLM itself how to appear in its results. Companies can query the engine about what content and formatting will help them rank for specific types of questions. Brian tried this approach after the summit and found it surprisingly effective.
The value of peer-to-peer transparency
The hosts reflected on why the roundtable format works. The key ingredient is trust. When practitioners feel comfortable sharing their challenges openly, others can offer solutions they have already tested. One attendee mentioned struggling with a specific data cleansing problem; another immediately shared what had worked for them.
The table topic discussions, where attendees rotate between tables discussing different subjects, are now approaching 90 minutes in length. Each year, attendees ask for more time. Brian noted that one year an attendee suggested making the entire event just table topics. While the hosts have not gone that far, the feedback underscores how much value practitioners place on unstructured peer discussion.
The event also included panels with practitioners leading discussions on topics like IT and marketing alignment, ROI documentation, and getting executive buy-in. These featured leaders from large companies sharing how they have driven change within their organizations.