Hosted by Jeff Walter, Founder and CEO of LatitudeLearning
In this episode of the Training Impact Podcast, Jeff Walter sits down with Kevin Trost, Owner and President of Adminify AI, for an in-depth conversation about how artificial intelligence is changing the way organizations scale, support channel partners, and design business processes. The discussion goes far beyond surface-level AI tools and instead focuses on how AI assistants can operate as a true execution layer across customer engagement, sales, operations, and franchise enablement.
Throughout the conversation, Jeff and Kevin repeatedly return to a familiar Training Impact Podcast framework: people, process, and technology. Kevin’s perspective challenges the traditional boundaries between those three elements. AI is no longer just a system that supports people executing processes. In many cases, AI is beginning to execute parts of the process itself, creating a new category of digital assistants that act as a force multiplier for growth.
This episode is particularly relevant for franchisors, partner-driven organizations, and multi-location businesses that are trying to scale without adding layers of headquarters staff or increasing operational complexity.
Kevin begins by sharing his entrepreneurial background and how his career has focused largely on customer acquisition, system design, and scalable business platforms. Before Adminify AI, his work involved helping technology-centric companies such as Amazon, Uber, and DoorDash connect their platforms to real customers. That experience shaped a critical insight. Even the most advanced technology still requires intentional systems to acquire, engage, and retain customers.
Adminify AI emerged from an unexpected experiment. Kevin and his team launched an artificial turf company not as a long-term business, but as a proof of concept. The goal was to test whether AI could automate a complex customer journey end to end. Within months, the business had AI handling referrals, lead capture, customer engagement, scheduling, payments, and review management. The only part that remained manual was the physical installation of turf.
That experience revealed something powerful. AI could do far more than answer questions or generate content. It could actively run meaningful portions of a business. At that point, Kevin and his team faced a choice. They could continue operating service businesses or they could build a platform that enabled other organizations to implement AI effectively. Adminify AI was created to do the latter.
A recurring theme in the episode is Kevin’s insistence on starting small and practical with AI. He acknowledges that AI can feel overwhelming. The possibilities are vast, and many business leaders are unsure where to begin. Rather than chasing every potential use case, Adminify AI focuses on identifying the most obvious friction points in a customer journey.
One of the earliest and most impactful areas is speed to lead. Kevin explains that in industries such as HVAC, home services, and emergency repair, customers often choose the first company that responds. If a business misses that initial interaction, the opportunity is usually lost. AI provides a clear advantage by ensuring that no inquiry goes unanswered, regardless of the time of day or channel used.
This principle extends beyond new prospects. Existing customers also benefit from faster engagement, whether they are asking questions, rescheduling appointments, or following up on services. AI becomes the first line of engagement, ensuring responsiveness while preserving human involvement where it matters most.
Rather than positioning AI as a replacement for people, Kevin describes it as an assistant that works alongside them. Adminify AI maps the entire customer journey from initial contact through resolution and identifies which steps can be automated responsibly and which require human interaction.
The goal is not to remove humans from the process. The goal is to use AI to handle repetitive, time-consuming, or transactional tasks so that people can focus on moments that require judgment, empathy, or relationship building. When AI completes its portion of the interaction, it hands off a clear summary to a human team member, allowing them to step in efficiently without starting from scratch.
This approach reframes efficiency. Instead of asking how many conversations one employee can manage, organizations can ask how AI can filter and prepare interactions so employees are only involved where their input truly adds value.
One of the most memorable moments in the episode is Kevin’s story about a mattress retailer using Adminify AI. The retailer received hundreds of inquiries daily but only converted a small fraction into sales. AI was implemented to engage leads, check inventory, schedule pickups, and collect payment automatically.
Late one night, AI completed a full sale and scheduled a pickup. The next morning, the customer expressed hesitation about meeting alone at a warehouse. Without being explicitly trained for this scenario, the AI identified the underlying concern and adapted its responses. It explained the warehouse setting, offered to have another person present, and ultimately referenced shared social connections to build trust.
The result was a completed sale and a comfortable customer. For Jeff, this example highlighted something critical. AI was not following a rigid script. It understood the goal, recognized objections, and tested multiple strategies to overcome them. That level of contextual problem solving represents a shift from traditional automation to true assistance.
Kevin emphasizes the importance of transparency when deploying AI. Customers should know when they are interacting with an AI assistant. Trying to disguise AI as a human often creates frustration once the truth becomes apparent. Instead, Adminify AI encourages businesses to be upfront and even creative.
Kevin shares an example of a company that embraced a pirate-themed AI assistant, complete with personality and humor. Rather than feeling robotic or deceptive, customers enjoyed the interaction. This creativity helped humanize the experience and made the AI feel like a natural extension of the brand.
Jeff connects this idea to his own experience with LatitudeLearning’s AI assistant, Norm. By giving the assistant a personality and identity, users engage more willingly and trust the experience. The lesson is clear. AI adoption is not just a technical decision. It is a design and experience decision.
A critical insight from the episode is the comparison between AI and human employees. Kevin points out that most organizations are willing to train a new hire for weeks or months. They provide feedback, refine behavior, and invest time to get the employee aligned with company culture and goals.
By contrast, many leaders abandon AI tools after minutes if they do not perform perfectly. Kevin argues that this mindset limits results. AI improves dramatically when it is trained intentionally, given clear goals, and refined over time. Once trained, that AI assistant works continuously without fatigue or turnover.
Jeff builds on this point by noting that traditional software systems are deterministic. They behave exactly as configured. AI systems are different. They require ongoing guidance and oversight, much like a junior employee gaining experience. Organizations that embrace this mindset unlock far greater value from AI.
As the conversation turns toward franchising and channel enablement, the implications become even clearer. Kevin explains that Adminify AI was redesigned early on to support multi-location and franchise environments. Corporate teams can deploy consistent AI assistants across hundreds of locations while still allowing customization at the local level.
For franchisors, this creates a powerful advantage. Instead of simply providing a tech stack, organizations can provide an AI-powered operating layer. Franchisees receive assistants that handle lead engagement, scheduling, reputation management, collections, and follow-up automatically.
Jeff highlights how this changes the value proposition for prospective franchise owners. Risk is reduced because key processes are already built, proven, and running. Training time decreases because franchisees are not learning how to execute every task manually. They are learning how to work with their digital assistants.
This approach directly addresses one of the biggest barriers to franchise growth. Finding operators who can manage every aspect of a business is difficult. AI reduces that burden, allowing franchisees to focus on leadership, customer relationships, and differentiation.
One of the most strategic takeaways from the episode is a redefinition of the technology stack. Traditionally, stacks are evaluated based on tools such as CRMs, billing systems, and marketing platforms. Kevin and Jeff argue that organizations must now also evaluate their AI assistants.
Two companies may use the same tools, but the way they train and deploy AI can create vastly different outcomes. One organization may use AI only for basic chat responses. Another may use AI to execute entire workflows. In competitive environments, that difference matters.
For franchisors and partner organizations, the AI layer becomes a key differentiator in recruitment, scalability, and consistency.
The episode also touches on financial operations, including accounts receivable and collections. Kevin explains how AI can handle follow-ups, overdue payments, and routine financial interactions. This reduces stress for owners and improves consistency without eliminating human oversight.
Jeff connects this capability to franchise training, noting that many new owners struggle with financial management. AI assistance can reduce the learning curve and provide guardrails while owners build confidence.
As the episode concludes, Kevin offers a clear message. Businesses should learn how to work with AI, not resist it. There is rarely a perfect time to adopt new technology. Waiting only increases the effort required later.
Organizations that invest time now in training AI assistants will gain efficiency, improve customer experience, and create a sustainable competitive advantage. Those that do not risk falling behind as others redefine what scale and consistency look like.
For leaders focused on training impact, channel enablement, and growth, this episode offers a practical blueprint for how AI fits into the future of business.
To learn more about Adminify AI, visit https://www.adminify.ai
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