Episode 121 | The AI Hat Podcast
Hosted by Mike Allton
Most revenue leaders are paying their best closers to do their cheapest work. Your top reps are not selling. They are onboarding new hires, rebuilding the same playbook from scratch, and fielding the same questions every quarter. The uncomfortable part is that traditional sales enablement does not scale, because you cannot clone your top performers. And while you are stuck in that loop of manual knowledge transfer, the cost is brutal: roughly $30K a month per top rep, gone.
Vernon Ross has lived both sides of this. As an enterprise account executive he drove 75 to 85% increases in new client acquisition, carried a multimillion-dollar pipeline using MEDDPICC, and closed deals with Procter & Gamble, GE, and AT&T. Then he did what most sellers never do: he built the AI training systems that scale a top rep's knowledge without burning their quota. In this conversation, he walks through how to architect AI sales enablement your team will actually use, from the first diagnostic question to the one automation you can ship this quarter.
You'll Learn:
- The single diagnostic question Vernon asks before recommending any AI tool, and why it starts with your top reps' worst hours
- Why AI pilots die when they add friction, and how to design workflows that remove steps instead
- How to scale onboarding with NotebookLM, private podcasts, and voice cloning, cutting top-rep training time from 30 hours down to 10
- Which parts of a MEDDPICC deal AI can accelerate, and which still demand human judgment
- How to connect content consumption to rep performance so leadership sees real P&L impact
- The first automation to build with no six-figure budget and no data science team
Chapters:
- 00:00 Top Rep Pain Points
- 00:59 Podcast Theme Intro
- 02:08 Show Mission Setup
- 03:15 Guest Vernon Ross
- 05:11 Sales Enablement Gap
- 07:34 AI Adoption That Sticks
- 10:58 AI Hosted Training Podcasts
- 13:46 NotebookLM And Voice Clones
- 16:28 MEDDPICC With AI
- 18:52 Onboarding Without Teaching Jail
- 21:25 Shadow AI Sponsor Break
- 22:33 Measuring Podcast ROI
- 28:38 Fast Time To Value
- 30:37 Compliance And Risk
- 33:48 First Automation To Build
- 36:34 Where To Find Vernon
- 37:18 Final Wrap Up
If your team is buried in onboarding and your AI pilots keep stalling, the problem is rarely the tool. It is the process underneath it. Start by governing the shadow AI your reps are already using. Download the free Executive Guide to Shadow AI at theaihat.com/shadow-ai, your blueprint for turning ungoverned risk into a sanctioned advantage.
Full Episode Transcript
(Lightly Edited)
Stop Losing $30K a Month Per Rep: The AI Sales Enablement Playbook with Vernon Ross
[00:00:00] Vernon Ross: What is it that your top reps are doing? Or like what are the top things that they're doing that they absolutely hate on a week- that they spend like 10 plus hours a week on doing? What's that one thing that they all complain about? That's usually the first question that I ask. I'm like, "Okay, that's where we can apply looking at is AI the solution for what it is that you're doing."
[00:00:23] I try to find like the most painful thing that they're dealing with that's taking their top reps, because that's who's gonna be the measurement of where they get the most impact, is if we can save those top reps that 10 plus hours, you're gonna make a huge impact. Like one of the numbers I did, if you have a rep that's doing about 2 million annually and they're spending 30 hours a month, so if they're spending 10 hours a week or a little more, a little less, that's, that's about 300K in lost revenue.
[00:00:55] If you can free up that time, you're gonna see an automatic increase in the bottom line
[00:00:59] Mike Allton: Mike's got the hat, the AI kind. Unlocking power in business, you'll find. Cut through the hype, explore the tech. Every week, new ideas to check
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[00:02:08] Greetings program. Welcome to the AI Hat Podcast, the resource for revenue teams who are ready to stop being the bottleneck in their own business. Every week, we architect some simple AI operational systems that eliminate admin drag and can reclaim your time that are freeing you up and your team to focus on the high-value work that truly scales your revenue.
[00:02:27] I'm your host, Mike Allton. Subscribe and let's build your digital team together. But here's the reality most revenue leaders won't admit. Your best sales reps are spending more time teaching new hires than closing deals. Every onboarding session is an hour stolen from your pipeline. Every repeated product demo to a struggling rep is revenue left on the table.
[00:02:49] And the brutal truth? Traditional sales enablement doesn't scale. You can't clone your top performers, so you're stuck in this endless cycle of manual knowledge transfer while your competitors are building AI-powered learning engines that run 24/7. This isn't a theoretical problem. It's a quota killer, and today's guest didn't just identify this bottleneck.
[00:03:09] He built the solution that Fortune 500 companies are using right now to fix it. Vernon Ross is a senior account executive who drove 75 to 85% increases in new client acquisition with a 32% lead conversion rate at Supporting Cast, closing enterprise deals with Procter & Gamble, GE, and AT&T, including the company's largest deal to date.
[00:03:31] But here's what makes Vernon different. While managing a multimillion-dollar pipeline using MEDDPICC methodology, he was simultaneously building AI-driven podcasting solutions that increased client engagement by 35%. He didn't wait for the perfect AI tool to arrive. He architected the workflow himself, integrating platforms like Wondercraft.ai to create AI-hosted training content that scales expert knowledge without burning out quota carriers.
[00:03:57] As president of Vernon Ross Consulting and Enterprise Podcaster, he's generated over $500,000 in enterprise SaaS sales while advertising and advising Fortune 1000 companies on podcast-driven learning initiatives and AI-enhanced employee engagement. Vernon is that rare practitioner who's carried quota, closed enterprise deals, and built the AI infrastructure that makes other sales teams faster.
[00:04:20] Hey, Vernon. Welcome to the show.
[00:04:23] Vernon Ross: Hey, man, what an introduction. I'm like, "Who is that guy?" That's awesome.
[00:04:31] Mike Allton: Like I tell folks all the time, you did all the hard work to accomplish everything I talked about. Claude wrote that script. I just delivered it. Kudos to you, man. Thanks for coming on the show.
[00:04:42] Vernon Ross: Hey, thanks for having me, man.
[00:04:43] I'm excited to have this conversation.
[00:04:45] Mike Allton: That's right. That's right, and it's great because you and I have known each other now for almost 10 years, I think. Yeah, almost 10 years. We're getting close to a decade. Yeah. Uh, and this is the first time we've had the, been able to have this kind of conversation. Uh, and I'm, I'm particularly excited to really showcase your PaaS expertise.
[00:05:04] For the folks listening, you've closed, like I said, enterprise deals worth millions while building simultaneously AI solutions for your clients. Kind of walk us through how you identified sales enablement as a workflow that maybe needed AI automation or maybe even needed it first.
[00:05:19] Vernon Ross: Yeah, you know, what's funny about that is, you know, typically with sales enablement, you know, you go through your steps and you're trying to identify, you know, who the economic buyers are, and your ma- marketing qualified leads and sales qualified leads, and oftentimes those two things are kind of separate.
[00:05:37] Sales int- isn't talking to marketing, marketing isn't talking to sales, and nobody's really looking at the data to figure out exactly what you need to work on. It was just a gap that I noticed, and because the company I was working at at the time was Supporting Cast was small, and I was the founding, uh, you know, sales account exec, working with marketing was pretty much non-existent.
[00:06:01] They had two sides to their business, a public side where they deal with subscription-based stuff, and I was working with, you know, all of the private stuff. And so just through some simple AI stuff, just ChatGPT was able to kind of take the sales enablement playbook that we were current- that we were following and modify that some so that marketing and sales, me, were actually talking to each other to figure out what we should be talking about, how we should change our decks, uh, how we sh- we should be looking at potential clients, current clients, and doing some land and expand opportunities and really maximizing those leads that were coming in.
[00:06:43] Mike Allton: I can completely relate. I've been at Agorapulse for almost as long as I've known you, and it wasn't until last year that we- Mm-hmm ... actually moved to combine sales and marketing into one revenue team. They were very much siloed, and I've always been a silo within marketing. So I'm a silo within a silo guy.
[00:07:01] But it's, it's great to finally have that, that cohesive team and that communication that goes back and forth, you know, instead of just, you know, a one-off from a sales rep that says, "Hey, I talked to this guy, he needs this." Um, you know, or marketing asking sales, "What do you need? What can we do for you?"
[00:07:14] There's that more constant communication. But I also know a lot of revenue leaders, they're drowning in AI pilots, in these tools. They- they're, they're trying things that nobody uses, which isn't necessarily a new story right? I mean, so many, you know, organizations have, you know, installed CRMs and plugins and that sort of thing, but it's a little bit different, I think- Mm-hmm
[00:07:33] in some ways. So what do you think, like, the fundamental difference is between an AI experiment that dies and one that drives measurable adoption, like some of the increases that you saw?
[00:07:44] Vernon Ross: Yeah, you know, the ones that die are the ones that cause friction. Mm ... when they add steps When, when they add more things that the reps have to do, when you're, you know, creating all of these things that they have to do, it...
[00:07:59] That, that friction kills it. So if you can remove friction by doing the stuff with, with AI, that's gonna help. So you need to be shortening processes and shortening steps. So when things happen, maybe you get an automatic list of responses. So for instance, you know, you're developing an email sequence in HubSpot, and often what you'll do is you'll get that boilerplate sequence or you'll copy a sequence that was working, something like that, and then the rep has to go in and modify for each client.
[00:08:33] They have to go out, they have to build, you know, a profile for each potential prospect that they're looking at if they're doing some targeted stuff and not just spray and pray. Hopefully, they're doing targeted outreach. So when they're doing the targeted outreach, they're spending sometimes hours putting together this target list and then trying to modify the email sequence to go out and maybe find a fact here or there.
[00:08:58] With building the right workflow, you can literally give AI the list of people or the description of the companies of the list of people that you wanna contact, get something back, use one of the contact tools like a ZoomInfo or an Apollo, build a quality list, put that list into your tool. The workflow goes through, creates all of the stuff that you need, and then the human-in-the-loop process reviews all of that stuff, and then you can send out those targeted, you know, outreach sequences in HubSpot and know that you actually have something that's unique for every person that you're trying to qualify or that you're trying to reach out to.
[00:09:37] Just leveraging AI like that, and it's a one email thing. It'll, it'll take you some time to build it, but if you can say, "Hey, rep, all you have to do is put in these qualifications, put in these criteria, and we're going to give you a sequence and a list, and then all you have to do, check it out, make sure that everything is right, send it out, and follow up," that's a lot different than, "Go research, go do this, go do that, go do this," and you're spending, you know, 20, 30 hours doing, not selling.
[00:10:06] So that's, that's kinda... Hopefully that answers that question. I, I went a little far into detail with that one
[00:10:12] Mike Allton: No, but that's great. That's ex- that's exactly right. We need to look at the processes first, not just buy a new tool and, uh, you know, some shelf ware that nobody's gonna use. We need to look at what the reps are doing today.
[00:10:24] Like, you have a lot of reps who maybe they're not updating the CRM after a call with a prospect because there's too many clicks, too many steps, and they've already had to go onto the next call and the next call and the next call. Yeah. Well, let's look at, you know, putting in some kind of an AI automation where they can just drop the transcript into a folder or chat window and allow AI to help them perhaps within seconds- Yeah
[00:10:47] fill in the CRM, create the action items, create the next steps and so on. That's the kind of solutions we're, we're talking about on this show all the time, Vernon, so I appreciate you actually going into the weeds and, and showing off that example. Now, when you integrated, uh, Wondercraft.ai- Mm-hmm ... you created some AI-hosted content, and that was for Fortune 500 companies.
[00:11:07] What was, like, the specific enablement bottleneck that you were solving that maybe traditional training platforms, LMS platforms couldn't fix?
[00:11:16] Vernon Ross: You know, taking information that they already had, so there were some newsletter stuff, stuff like that, and creating basically an automated podcast. The first company we did it for was actually, there was a, um, I can't actually mention the name, but there was a- Mm
[00:11:30] medical device company. They have like all of these case studies and white papers from these doctors, and they're using that for selling to other doctors and other hospital systems. But they didn't have a good way to get that information to them, and sending out the mailings and trying to print them and do all the things that they were doing and sending these huge PDFs wasn't working.
[00:11:54] But creating a summary with AI and then using Wondercraft to actually create those podcasts, they were able to then invite doctors in to just listen to a private podcast and get the information that they needed to basically pre-sell them and educate them beforehand, and that improved their outreach workflow.
[00:12:15] Uh, with the Fortune 500 companies, more of it was just automating information that they already had that they wanted to create or giving them an idea of this is how the podcast could sound if you're doing this information. So even if you don't use the AI-created podcast, here is basically a preview of it.
[00:12:34] You can listen to it, kind of get your, your legs under you because you've never done a podcast before of how this can sound and how this can be, and then they can go and produce it on their own.
[00:12:46] Mike Allton: So when you're talking about a podcast, you're not talking about something that's just pushed to Spotify or Apple Podcasts.
[00:12:52] It's a private link type of a situation where only those- Yeah ... within the company or that they allow can listen to it?
[00:12:59] Vernon Ross: Yeah. Uh, not to make it a Supporting Cast commercial, but the cool thing about Supporting Cast is they enable folks to have private podcasts and have them through Spotify or Apple Podcast, so they could listen to them on the go, but it still remained private.
[00:13:16] So it was used more- Mm ... as an internal training tool than an an external promotional tool
[00:13:23] Mike Allton: And I think the key there for folks listening to understand is y- you're using podcast audio content as a medium- Yeah ... because as you said, folks can listen to it on their phone, they can subscribe to a feed, they can get a notification when there's new content.
[00:13:36] They can listen to it while they're multitasking or they can sit and rapt attention in front of their computer if that's what they wanna do. Mm-hmm. But all of that's up to them. So that, that makes a lot of sense to me. So this was kind of like a NotebookLM solution, but pre-NotebookLM if I'm not mistaken,
[00:13:52] Vernon Ross: right?
[00:13:52] Yeah. Actually, it w- it was- Yeah ... it was weeks before NotebookLM launched, and then when NotebookLM came out we were like, "Oh my, look at this. We can actually like just put this in here, get a deep dive and then use that as a script." Because w- what, what most people are doing, they're like, oh, and you'll hear all these NotebookLM podcast everywhere now and it's the same two hosts.
[00:14:16] What Wondercraft end up, ended up doing, they were like, "Oh, we can pull that into NotebookLM and then you can just change the speaker to whoever you want." So the smartest thing to do would be clone your voice, get a really good clone of your voice, use their ... I think they have some system where you can put intonation in and the right way of speaking and all that other stuff.
[00:14:37] They didn't have it at the time, they have it now. But you can pull all that in, clone your voice and then replace the deep dive podcast from NotebookLM with your own voice and push that out internally and so it's not like who in the heck are these hosts that are talking about our stuff? Oh, this is our normal host giving an update.
[00:14:59] It wasn't perfect, but it was definitely a way to do it once NotebookLM came out. But yeah, this was pre-NotebookLM, just creating deep dives into case studies and informational things. I put together a thing for town halls for folks to do town halls- Mm ... stuff like that. Pull all of that in, automate it and free up the executives to not have to sit down for a 30 to 45-minute podcast that they didn't wanna do.
[00:15:25] Mike Allton: Yeah, this is such, to me, a beautiful use of artificial intelligence. And for folks listening who maybe you haven't experienced an AI created podcast like NotebookLM, in fact I did a whole episode just about NotebookLM- Sounds great ... you're creating a repository for AI by giving it the PDFs, the white papers, the case studies and that sort of thing.
[00:15:42] This is creating what's called a RAG, retrieval augmented generation system where the AI knows how to speak the language and has general knowledge, but any facts and information are restricted to that content. Right. So it's not hallucinating, it's not making up anything. But it's also at the same time summarizing and if you give it the right context it's focused on your target audience.
[00:16:03] If it's physicians it's great, it's talking to them from their perspective. What do they need to know about X, Y and Z, these products? They might not need to know really, really highly technical specifications but they may need to know applications and the results of past studies and, you know, trials and that sort of thing.
[00:16:20] So- A brilliant use of AI. But let's bring it back to something I mentioned at the outset 'cause I, I wanna help folks get to this point. Mm-hmm. We talked about you being, using MEDDPICC to navigate complex, like, multi-stakeholder deals for folks, maybe the marketers in the audience are listening. You know, that's metrics, economic buyer, decision criteria, decision process, paper process, identify pain champion, and competition.
[00:16:44] It's a whole framework for basically how a salesperson, an AE, or even an SDR should approach a sales conversation. These are the things that they wanna ask about, right, in the conversation. So what parts, Vernon, of that entire methodology do you think can be AI enhanced versus which parts do you think still absolutely require human judgment and relationship capital?
[00:17:06] Vernon Ross: Yeah. You know, what's interesting about MEDDPICC you can, you can use that methodology to identify a lot of how you approach a deal. So, you know, some folks will be familiar with the Challenger Sale or the Challenger Customer really goes into that type of... It, it's not really MEDDPICC, but it goes into the methodology of it a little bit.
[00:17:26] One of the biggest things that I use it for, particularly at Supporting Cast, and I'm also working, I, I, well, I, I used to work with them, but there's a company out of Germany called Hypecast that I also work with, is to look at past deals to predict the likelihood of success if you reengage those deals, or looking at past deals and using AI to find other deals that are similar to it so that you know exactly who it is that you need to talk to.
[00:17:58] Because one of the problems with MEDDPICC is identifying those economic buyers, and it's not the same in all companies. And finding those, those people specifically and then targeting those people can be a bit of a challenge. So you can use AI to help you get to who your potential folks are and exactly what it is that you wanna communicate with them.
[00:18:20] Because all the time it's not exactly clear with each prospect of what do you wanna communicate to that economic buyer, or how do you best align with the issues and the pain points that they're actually having so that they can become your internal champion?
[00:18:36] Mike Allton: Got it. Got it. So we can use AI to help identify buyers.
[00:18:40] We can certainly use AI to help research them, and that, and that usage, I think, of AI is going to help train new hires, new AEs, new BDRs, and so on, uh, because it's speeding that entire process. But I think still we have a bit of an issue with what I call teaching jail, where we've got some of our best performers, we wanna duplicate their success, right?
[00:19:01] So we're asking them to spend time, valuable sales time, onboarding new hires. Mm. How do you... H- Let me ask you this. How much revenue do you think the average sales org is losing because some of their top performers are stuck onboarding these guys instead of working pipeline?
[00:19:20] Vernon Ross: Yeah, I mean, if you spend 20 to 30 hours doing that, I did some numbers, and you're...
[00:19:24] It's about 30K. It's about 30K- Mm ... uh, of revenue that you're losing in op- lost opportunities per month, not per year. You're missing about 30K of possible revenue per month by having your top agents, your top reps train and onboard new folks when most of that stuff can be done with AI. It can be done with podcast. It can be done with podcast using AI. Uh, for instance, you mentioned NotebookLM. There is a feature in NotebookLM where you can create flashcards that walk people through individual things that they need to learn.
[00:20:05] Or you could put all of that knowledge into a database that's in NotebookLM, and then your new folks can do some of their onboarding with NotebookLM. They could listen to a deep dive. You could put together a slide deck in NotebookLM, all with the knowledge that you create as, as resources for those new folks to onboard.
[00:20:27] And so maybe they spend their first two days going through NotebookLM so that they have a basis to work from, and then instead of 20 to 30 hours of your top reps spending that time, maybe they're only spending five to 10 hours of actual time working with them, and then it's on things that are, like, really valid that they need to talk about, not the basics of who you need to talk to, what do you need to do, you know, all of the basic things that you do when you're onboarding someone.
[00:20:54] You can put all of that stuff into an AI workflow. You could do it with podcasts, which is how I was previously doing it, was just with podcasts. I've created a lot of onboarding podcasts that take folks through all the basic stuff that they need to do so that they don't have to spend those revolutions talking to and pulling in their top folks.
[00:21:15] Mike Allton: Love it. Love it. Folks, we're talking with Vernon Ross about how AI is impacting sales enablement, and I've got a bunch more questions. In fact, we're gonna dig into how do we even know that this is working? But before I get into that, a quick word about Shadow AI.
[00:21:29] Right now, your best people are drowning. They're buried in data entry, meeting prep, and internal reporting, the admin drag that kills momentum. To keep their heads above water, they're turning to AI tools you haven't approved. They aren't trying to be reckless. They are trying to be efficient. They are trying to hit the goals you set for them.
[00:21:52] But this shadow AI creates massive blind spots in your data security. You can't afford to ignore it, but you also can't afford to ban it. You need to architect it. I've created the Executive Guide to Shadow AI to help you bridge this gap. It's a blueprint for turning a security risk into a competitive advantage through proper governance.
[00:22:17] Don't fight the shadow, sanction it. Download the free guide today at theaihat.com/shadow-ai.
[00:22:29] That's theaihat.com/shadow-ai.
[00:22:33] So Vernon, let's talk impact. You built AI-enhanced analytics dashboards to track podcast performance and ROI. How did you connect content consumption metrics to actual sales outcomes so leadership could actually see some kind of P&L impact?
[00:22:49] Vernon Ross: Yeah, that's, that's interesting. So I was looking at this question, I'm like, "Hmm."
[00:22:55] How do I, how do I escape- Did I do that? How do I escape this? So I'll, I'll give you, I'll give you two answers to that. The first was actually pre-AI, and this is how I was doing it pre-AI. Pre-AI, there wasn't a really good way to measure it. I was working with Bayer, and they were creating a podcast for a farming software that they were using, and the reason that they were doing the podcast was to, you know, educate consumers on this software, talk about the things around it, what they could do with, you know, seed utilization, and all this, all this stuff around farming that I had no idea that existed.
[00:23:34] The way that we would measure it, or the way that I told them to measure it so they could actually justify spending all the money they were spending on the podcast, was to put up a custom landing page and have that custom landing page be the driver for where all of their trial signups were coming from, and then wherever they were getting the most listeners from using map data for podcast consumption, they would then know, oh, okay, we're getting more signups and trials from this area or from this state, 'cause you could kind of drill down state to state.
[00:24:08] Very manual process, but you could look at, hey, where is this coming from? And our, our trials went up after this episode in Iowa, so we know that folks are listening to the podcast 'cause they're clicking on the link that's on this site, or, you know, depending on the app, they're clicking on the link that's in the app to go here, and they're signing up.
[00:24:26] And so you could drive, you know, or you could measure signups to listenership, and it was a way to sort of tie that into podcasting. You can, you can do the same thing now with AI, but even easier. You can just automate the process. So if it's internal, it's any of the things that folks are interacting with.
[00:24:46] So if they're listening to the podcast, you can look at podcast consumption data, and then tie that into revenue actions by reps. So if a rep, for instance, at a pharmaceutical company, I did a thing where they did 7 Minute Saturdays. It was a podcast I helped them create, and in seven minutes they would go over what their top reps were talking about, and it's what's working this week is, is actually what the, the episodes were.
[00:25:11] And they would talk about the talk tracks that they were using, uh, the routes that they were taking, the things that they were doing to sell in the field. They would then take that and put that into a podcast and now you can actually measure that stuff with AI about who's doing what, where the performance is coming from, how they're accessing the podcast, whether it's mobile, whether it's on their com- or whether it's on their laptop devices, and really actually tie it- Back to the revenue they're producing based on if they're doing the things that are working.
[00:25:43] So hopefully that, that answers that question.
[00:25:47] Mike Allton: Oh, 100%. Another way to put it, at least, and you can tell me if I'm wrong, is to think first about the behavior that you're trying to change- Mm-hmm ... through the podcast, and then determine how would you measure a change in that behavior, and then you craft the podcast in order to impact that change.
[00:26:04] So for instance if you wanted your sales reps to talk more about other products in your catalog that they don't typically talk about because they're kind of used to selling the things that they sell- Yeah ... and they forget to upsell or cross-sell and so on. So you create podcasts that are specifically deep dives, uh, designed to educate them on those particular products, and then you measure the increase in those product sales relative to consumption.
[00:26:30] Does that sound right?
[00:26:31] Vernon Ross: Sounds exactly right. And you know, the problem is, is that with all of the AI, or not AI, all the podcast platforms out there, you have those stats, but you have to go in, someone has to go in and manually pull a report or look at, okay, where is this coming from? And then try to put it into some tool, Tableau or something like that- Mm-hmm
[00:26:50] and extrapolate that data. That's all automatic now. You can automate that with an AI workflow. So instead of spending 30, 45 minutes trying to compile that information, now it's automatic and it's run via a cron job every week with something like Claude Code or Claude Coworker. You can actually say, "Hey, every week I want you to go out, look at these podcast stats in this platform.
[00:27:13] I'm gonna give you access to it, and show me what's happening with all of my podcasts. And oh, by the way, look at rep performance in this tool and see if those reps who are listening to the podcast," if you track them via AI or via IP address, which you could do, "show me what the performance data is and send me a report weekly."
[00:27:37] You can do, you can automate that now with AI, whereas before that's two and a half, three hours worth of work that you'd have to individually do if you have it just, like, down pat to a workflow and you're not trying to figure it out every probably month when you're looking at it.
[00:27:53] Mike Allton: If, I guess for those listening who maybe you don't have that automated, you're not sure where to start, maybe you don't have budget for that kind of stuff, open up Chrome, open up your podcast or whatever it is that you've got that's got like reporting analytics on consumption, and then you can open up in a completely different tab your sales rep performance data, whether that's in Salesforce or something like that, and you can ask Gemini in Chrome to look at those two tabs and help you analyze that data.
[00:28:21] It's not gonna be automated. You'd have to ask it that every time. But if you can dust some insights out of the data with the use of AI, you can take that to your VP of sales, right? And say, "Hey, this is what we've got going on right now. I could use a little extra budget to automate this." Yeah. So w- Vernon, when you walk into a revenue leader's office and they say, "We need AI for sales," what would you say is like the diagnostic process that you run to help identify which workflow or workflows might deliver the fastest time to value, the, the quickest return for that kind of a pilot project?
[00:28:56] Vernon Ross: Yeah. The first thing that I ask is, you know, what is it that your top reps are doing? Or like what are the top things that they're doing that they absolutely hate on a week, that they spend like 10 plus hours a week on doing? What's, what's that one thing that they all complain about? That's usually the first question that I ask, and I'm like, "Okay, that's what we, where we can apply looking at is AI the solution for what it is that you're doing?"
[00:29:23] I try to find like the most painful thing that they're dealing with that's taking their top reps, because that's who's gonna be the measurement of where they get the most impact is if we can save those top reps that 10 plus hours, you're gonna make a huge impact. Like one of the numbers I did, if you have a rep that's doing about 2 million, 2 million annually, and they're spending 30 hours a month, so if they're spending 10 hours a week or, you know, a little more, a little less, that's, that's about 300K in lost revenue.
[00:29:56] If you can free up that time, you're gonna see an automatic increase in the bottom line.
[00:30:02] Mike Allton: Oh, I couldn't agree more. Some of the stats that I've seen have suggested it's as much as 70% of a sales rep's time that's being wasted on non-revenue driving activity. So that's a big part of what we talk about here, that admin drag is, is basically the concept- Yeah
[00:30:17] that I talk about constantly on this show and with the people that I'm working with. I'm going to sales kickoff meetings and, uh, all over the country and, and helping teams understand how they can use AI for mundane things. These aren't sexy things. This is help me write an email, help me draft a proposal faster, those kinds of things.
[00:30:34] But they add up to so much. Now, one of the things that I know you've done, you've worked with all these big name brands. I talked about P&G, GE, AT&T, all these letters, right? And a lot of these organizations I think are famous for compliance and risk management. Did the idea of shadow AI, this people are using AI but they're not telling their manager, they're not being- Yeah
[00:30:54] sanctioned or trained, did that come up? And h- if so, how did you get buy-in for that, working with those kinds of materials?
[00:31:00] Vernon Ross: The you know, the, the f- the funny thing about compliance folks and a lot of times it, it came from procurement risk mitigation. When you- Mm-hmm ... can talk to, you know, a senior exec and say, one of the things that you tell them, "I understand that we want to implement this, and we want to use something generally like a podcast tool, and there's some AI built into it that your, your risk mitigation is, is minimal," uh, or, "We have risk mitigation in place, and it's SOC 2 compliant with an audit trail.
[00:31:35] They're like, "Oh, wait, wait, what? We've, we've not heard- ... from other AI or podcast-related vendors." And it's like, well, yeah, anything that I use, it's gonna be, there's gonna be some audit trails, I'm gonna mitigate risk, and there's gonna be SOC 2 compliance. And there's, there's very few, you know, like, podcast hosting companies that do that, so I just, I make sure that I'm working with folks that have their SOC 2 compliance, not ones that are actually working on the SOC 2 compliance.
[00:32:05] Or one of the things that some companies will say, because they're hosting the podcast in Amazon three S3 bucket, is basically where you store the audio for the podcast. Because Amazon is SOC 2 compliant, they say that they're SOC 2 compliant, and, you know, it's more security by obscurity, which I'm like, ugh, that's, that's not actually saying that they're SOC 2 compliant.
[00:32:30] But I work with companies that have that SOC 2 compliance in place, and their whatever ISO number it is, that they've gone through all of that, and that they're very careful, and they have audit trails so that big companies like a P&G or an AT&T can produce content with confidence, particularly for internal stuff.
[00:32:51] External stuff goes through a, a number of compliance checks and everything else to make sure that, oh yeah, we can publish this. There's no data going out that shouldn't go out. So if you're hearing a that's public, you don't have to worry about, oh, okay, this, this is, this is what should be out there.
[00:33:10] But if it's a private podcast or an internal podcast where the intended audience is your employees, even if that data were to get out, you wanna make sure that there's an audit trail so you can know what happened, how it happened, and is there a way that we could have prevented it, or at least here's the audit trail of how this thing happened.
[00:33:33] Mike Allton: That is incredibly smart, 'cause to your point, we're usually talking to procurement teams or IT teams they just wanna ban this stuff because It's, it's, it, it seems unsafe. Yeah. And if you can improve the safety and security, well then you've definitely addressed one of their major issues. Vernon, I've just got one more question for you.
[00:33:50] For the revenue leader who's listening, and they know that their sales enablement, their onboarding process is broken, but they don't know where to start, what do you think is like the first automation that they should build this quarter? Something that it doesn't require a six-figure budget or a data science team.
[00:34:06] Where should they start?
[00:34:09] Vernon Ross: You know, I, I think am, I, I wrestled with, with kind of how to answer this, but one of the most valuable things that I put into place was voice-to-text CRM field completion. It's really easy to do. You can use something, I think there's a tool called Wispr Flow that does some of that- Yeah
[00:34:29] Where reps can talk through what they need to put into the CRM. It speeds up entering stuff. It doesn't cost a ton of money. You can find a number of apps that are text-to-speech. You can even do it with something as simple as like an Otter.ai, and then just copy and paste. I don't recommend that necessarily, but there are a couple tools out there to just auto-populate the fields in your CRM.
[00:34:54] That's just one quick thing that you can implement that'll save your reps so much time, and maybe actually get them to complete the things that they need to complete in the CRM on a re- on a regular basis, 'cause that's, that's huge. You'll see it in almost every job description that, you know, you have to be good at, you know, completing and keeping up with CRM data.
[00:35:13] So yeah, that's, that's probably, like, the one thing that is a pain point for just about everybody.
[00:35:19] Mike Allton: I love that recommendation. We've talked about Wispr Flow a couple times on this show. Mm-hmm. But I feel like I need to do an entire episode, uh, 'cause it, it's, it's very much an underserved or underrepresented tool.
[00:35:30] For folks who you're not really familiar with, it's, it's an app, so it's not a Chrome plugin. It's an app that lives on your computer or your phone or both, and because it's an app, in any text field that you're in, whether it's a web browser or a different app, you can push a button or whatever you wanna do, there's options in terms of activating Wispr Flow, and at that moment, it'll start listening to you wherever you're on it, wherever your cursor is in a text field.
[00:35:55] But it's not like the live speech dictation that we see in OpenAI, where as soon as you speak, it's punching the characters in. It listens to you until you stop talking, and it thinks through what you said, which means if you correct yourself, it will fix it. If you share things that sound like a list, it'll put it into a list, nicely formatted, and of course, everything's spelled right and so on.
[00:36:17] So it's definitely a step up from a lot of the texting, uh, voice texting and dictation things that we've used up until now. So appreciate you calling that out, Vernon. You've been an absolute treasure trove of information. I know folks are really excited to share this with their ops teams and, and get some input on their sales enablement processes.
[00:36:34] But for those who want to learn more, and maybe they wanna reach out to you- Sure ... where should they go?
[00:36:39] Vernon Ross: Well, I mean, the best place to reach me is LinkedIn. It's easy, just in/vernonross. That's the best place to reach me quickly. Of course, you can find me, um, vernonross.com or enterprisepodcaster.com. And I have a, uh, AI planner that I'm releasing, and so you can also find that out on aiplanner.com.
[00:36:58] I've given you enough URLs, but, uh, just reach out to me on LinkedIn. Best place to get me, quickest place to get me is out on LinkedIn.
[00:37:06] Mike Allton: Don't worry about that. As always, we will have all those links in the show notes below. So thank you, Vernon. We'll also include a link to Vernon's brand-new podcast, which will have come out by the time this episode drops.
[00:37:16] So thanks Vernon so much for coming on the show. Thanks all of you for listening. That is, of course, all the time we've got for today. But if you haven't yet talked to your team about how they're really using AI, shadow AI, it's time. Learn what shadow AI is, why you should lean into it, and how to proceed for free at theaihat.com/shadow-ai.
[00:37:35] Check it out, and I'll see you in our next episode. Welcome to The Grid.
[00:37:40] That's a wrap on another episode of The AI Hat Podcast. I hope you've gained some valuable insights and actionable strategies to boost your business with AI. If you enjoyed this show, please subscribe, leave a review, and share it with your network. And don't forget to visit theaihat.com for more resources and to connect with me.
[00:37:58] Until next time, keep innovating, and remember, the future of business is human and it's powered by AI
