The AI productivity gap between executives and employees
The hosts opened with news about a disconnect in perceptions of AI productivity. According to research cited in the episode, 40% of executives reported that AI saves them more than eight hours of work per week, while 66% of staff said AI saves them less than two hours per week or no time at all.
Andy attributed the gap to the nature of the work. Executive tasks like writing notes and conducting analysis fit AI tools well. Operational work, which often involves specific processes that AI has not been trained to handle, is more difficult to automate. In some cases, using AI for operational tasks takes longer than doing the work manually.
The hosts also noted that executives may be insulated from the realities of AI adoption. When a staffer cleans up AI output before presenting it to leadership, the executive sees only the polished result and assumes the tool worked smoothly. Brian added that there may also be wishful thinking at play, with executives eager to justify their AI investments.
Why trust matters in B2B
The hosts turned to the main topic: trust in the age of AI. Andy cited research suggesting that trusted brands are 1.6 times more likely to receive personal data from customers, users are 5.5 times more likely to allow AI agents to make major purchases when they trust the underlying technology, and 40% of consumers will stop doing business with a company immediately after a single trust violation.
If you trust this brand and the way they’re using AI, you’re one and a half times more likely to give them your data, which by the way is a lot of the gain here.
Andy Hoar, Master B2B
With AI raising new questions about what is real and what is generated, trust has become more relevant. The hosts argued that B2B companies need to understand not just that trust matters, but how to build and maintain it.
The four pillars of building trust
Andy outlined four established ways to build trust, noting that while they sound obvious, they are easier to state than to execute.
The first pillar is transparency. Companies should be open about their strengths and weaknesses. The hosts compared this to job interviews: candidates who offer a genuine answer about where they struggle are more believable than those who give a rehearsed non-answer. Companies that hide weaknesses undermine their credibility across the board.
The second pillar is honesty. In the age of AI, it is easy to twist facts or find statistics to support any position. The hosts noted that AI tools can even make a case for false statistics. Companies need to be proactive about ensuring their content is accurate, both in substance and in perception.
The third pillar is consistency. Andy cited Tom Brady’s observation that he succeeded not by being the most talented, but by being the most consistent. Trust is built through repeated delivery over time, not through a single impressive result.
The fourth pillar is product quality. None of the other elements matter if the product or service does not meet the brand promise. A brand is a promise, and companies that talk about trust while delivering a poor product create a disconnect that undermines everything else.
How to maintain trust once you have it
Building trust is not enough; companies also need to maintain it. The hosts identified three practices for sustaining trust over time.
The first is demonstrating follow-through. Andy cited the philosophy of Zingerman’s, a deli in Ann Arbor, Michigan: understand what customers want and go the extra mile. Exceeding expectations, even in small ways, reinforces the relationship.
The second is acknowledging vulnerabilities. Perfection is not relatable. Customers respond better to companies that admit limitations than to those that claim they never make mistakes. There may be legal constraints on admissions, but the principle holds: authenticity builds trust.
The third is showing up during difficult times. It is easy to maintain a relationship when everything is going well. Trust is built when a company helps a customer solve a problem they did not cause. Brian noted that Amazon exemplifies this approach, with fast delivery, clear communication, and customer-first policies.
When you see somebody who’s delivered, somebody who tells you the truth, that’s a lot more important than somebody who might be good.
Andy Hoar, Master B2B
Lessons from Tylenol and Wells Fargo
The hosts contrasted two case studies in crisis response. In 1982, Tylenol faced deaths linked to contaminated capsules. The company recalled 31 million units, acknowledged the problem immediately, and prioritized customer safety over short-term costs. Brian cited research suggesting that Tylenol built more customer loyalty after the crisis than it had before.
Wells Fargo, by contrast, initially denied that employees had been opening fake accounts. The drip-drip disclosure damaged trust far more than the initial misconduct. Andy emphasized that the first rule of finding yourself in a hole is to stop digging. Admitting a mistake fully and moving on is more effective than denial followed by incremental revelations.
Amazon’s approach to exceeding expectations
Andy shared a personal example. He ordered a blood pressure monitor from Amazon with a noon delivery window. When the package arrived at 12:18, he sent a message asking for an ETA. Amazon not only confirmed the delivery but also refunded the order because it was 18 minutes late, despite Andy’s insistence that a refund was unnecessary.
The hosts attributed this to a long-term customer value perspective rather than a transactional mindset. Amazon calculated that the cost of the refund was worth the loyalty it would generate from a Prime member. Companies that think in terms of lifetime value rather than individual transactions are more likely to invest in exceeding expectations.
AI transparency and trust: the poll results
The hosts polled their community with a question: if a company is 100% transparent about how and where it uses AI, how does this affect your trust? The results were clear: 77% said it increases their trust. Nobody said transparency decreases trust. A minority said it makes no difference, with one respondent noting that they assume everyone is using AI these days.
Andy closed with an additional statistic: research suggests that when customers rate an AI system as highly transparent, they are 8.5 times more likely to express high trust in the brand. As AI raises questions about what is real and what is generated, transparency may become the single most important differentiator for companies seeking to build trust.
Transparency rules. Remember that in your business.
Brian Beck, Master B2B