AI Leadership Insights: How Generative AI Is Transforming Partner Alignment with WorkSpan’s Sam Gong

ai video series. I'm your host, Mike Bazaar. Today we're talking with Sam Gong, who's vice president of Marketing for Work Span.

And we're talking about this whole issue that emerges. It's called the Partnering Tax. We all have experienced it.

We don't necessarily call it that, but once we get into it, you'll know exactly what we mean. Hey, Sam, welcome to the show. Thanks, Mike.

Happy to be here. So, partnering tax, we see this especially among big tech companies, but I think we see it everywhere. It's when a couple of companies get together two or more, and they kind of agree to work on something with a customer, involves them meeting each other.

And all too often from the customer's perspective, it feels like all these folks are meeting at the first time when they come to their office. And it's not exactly a great outcome. 'cause nobody knows what the left hand or right hand, or any other hand is doing.

So Sam, how will AI help us get around this or avoid this situation? Because it does lead to a lot of lost productivity, for sure. Yeah, thanks Mike.

And I think, uh, ai, AI is a part of the solution, but if we think about how we got here for a second, this is a, this is a problem that I think has been coming for a long time. And if you go back all the way to the beginning, uh, we used to have verticalized businesses, right? You'd own the supply chain, you'd own the resources, you'd own manufacturing.

The goal for the business magnets of the last century was let's put it all in one stack and own all of it. And then we can control quality for the customer and we can control margins and prices. And I think, uh, the trend in our century has been for problems to get more complicated, for technology, to get more complicated, and especially in the last 15 years.

And now with ai, not only as part of how we work together, but as what we're offering to our, our customers, the pace of innovation has accelerated to the point where there is no one company in the world, not not Amazon or Google or Facebook or Meta or any of these companies that can, can own innovation at every layer of the stack. And, and so what that necessitates is, if I want to provide the best solution to my customer, I need partners to come in there with me. I might need Nvidia for hardware and, and the the chip set that's gonna run the foundational l uh, LLMs.

I might need Anthropic or Amazon Bedrock or Google Gemini, right? Like, you've gotta piece together a solution that's best in breed for your customer, and that means that you're gonna work with partners. And so now when you present that, that solution to customers, uh, the complexity tax comes in because your sales team, your marketing team, everybody that wants to position and describe that solution to customers, they're not only trying to keep keep up with what you're doing as a business and what you're building, they're trying to keep up with how is that current in the market?

How does that leverage our partner's strengths? How have we put all these things together? And, uh, it just gets stuck, uh, in a single person's brain.

There's too much input to, to stay on top of all of it. So that's what we mean with the, with the complexity tax. And, uh, of course this is, um, this is a really hard problem to solve.

You're not gonna fix this with a SaaS application with if this, then, then that logic. Uh, you need cognitive tools, you need the, the benefits of, well, I can read a, a customer briefing from, from this partner and know how to digest that and boil that down so this salesperson can say the right thing at the right time on that deal. So that's where we see the intersection of, of AI and the acceleration of innovation, creating this, this pressure to go to market with partners, whatever layer of the, the stack, whether you're a service provider or a software provider or an infrastructure provider.

Uh, and then if you're an individual in that role showing up in that that room, like you said, uh, when partners come together, you don't want it to feel like this is happening for the first time. You want it to feel like there really is a joint value prop and a joint solution. And we see AI having a big role to play in helping those partners collaborate as a, a unified front Your point, um, can I reduce the number of salespeople required for that meaning in the first place?

'cause I think that's also part of the problem. But if one salesperson might be able to, uh, accurately represent the others and then the others can go do something else more interesting. Exactly.

And I, and I don't think it's about reducing the number of people. I think it's about maximizing the leverage for people, right? And so all the, the customers that work span talks to that are running sales orgs and partner orgs, uh, you want to provide the best experience you can to every buyer.

You want to provide the most support you can to every partner. You never wanna say, oh, well that account's too little for us to, to take a look at, right? Or that partner's too little for us to take a look at.

And so what AI helps with is you can take your people that have that subject matter expertise and they can divide and conquer, right? We wanna put the individuals in the driver's seat and say, well, I can put 20% of my time into all these accounts if AI can help answer some of the basic questions and I can focus on these big deals or these big accounts. So it's, it's not about reduction as much as it is about leverage and being able to spread every person in their role to cover more deals and more accounts and more partners.

And we'll also work. Conversely, I assume that when there is an issue, it'll be easier to sort out, well, who might be the most likely one of this partnership who might be the issue or the root cause of said issue. And uh, we can kinda cut down that whole customer service conversation.

And, uh, exactly. This isn't just a pre-sales problem. Pre-sales of course gets a lot of attention.

Everyone wants to increase revenue and, and money coming in the door. This is a full customer lifecycle problem, right? And so if you succeed in selling that joint solution, you have to have a plan to provide joint support for that solution.

And that that doesn't just make the sales person's job more complicated. It makes the support team and the success team and the delivery team's job more complicated. So we, we say it's a complexity tax and we start with the initial sale, but it's the full customer lifecycle.

Every single person that's involved in delivering that joint value to the customer needs this support in their role to be able to pull in those partner solutions and and deliver the joint success in today's market. Will it become easier to onboard people onto these teams? 'cause I think one of the issues that a lot of organizations encounter is when they lose somebody from these teams, it, it's, uh, it's heart wrenching to them because it takes six months or more to replace them.

Even if I, once I find the person, I, I think both things are true, right? When you increase the leverage for each person in their role, that's a good thing. But it also means that potentially that person leaving means a lot of the knowledge walks out the door with them.

And, and so what we're finding is, especially with partner managers, right? You think about, I'm sitting at the intersection of all the complexity of my company and my company's products and structure and how we go to market and then trying to unlock my partners, uh, solution and, and the value they can bring, but understanding their complexity and product and go to market and all of that. You are, you are highly leveraged at that intersection.

And it has not classically been a well documented process. It's a lot of emails, it's a lot of, uh, PDFs and, and agreements that get shared back and forth in, in spreadsheets and PowerPoint. And uh, there, you, you can have a partner relationship management portal, you can have places where some of this stuff lives.

But that true understanding of how are we driving this partnership very much ends up in, in people's heads and we're, we're, we're still early, but I think what you're saying will come true, where as that person who sits at that intersection works more closely with ai, then that person will have flexibility. Not if they want to change careers and go do something else or change companies, but also if they want to build another partnership and shift where they, they focus their time having AI act is that repository and they're working buddy buddy with, uh, with an AI teammate that they're training that not only increases their leverage, but it increases their, their flexibility to spend their time on another partnership and give the business more ability to bring in backfills or staff that role with less of their time if they decide to do something different. Do you think as part of this, that the AI is essentially gonna function a little bit like the institutional memory?

Can we all have people in the company who've been around for a long time and they serve that role, but um, you know, when they go, so goes the knowledge? Yeah, I think, uh, institutional memory is a great way to put it, right? And, and if you look at any process today, I, I work in marketing and even in the, I haven't even been at work span two years, right?

But in my two years, I'm still uncovering institutional knowledge that wasn't part of my formal onboarding. It's not easily accessible to me. It's three clicks down in some folder hierarchy that I just haven't explored yet.

And we go to launch some program and I ask the team, have we done something like this before? And it takes a lot of digging to surface institutional knowledge. And, and so I think one of the things AI will do across functions, not just with partnering, is help people and businesses understand each other faster and, and shorten the onboarding and, uh, make it so you can provide value with more context sooner.

Because there's an AI that can answer your questions and do all that digging for you. How do I get started with this? I mean, do I just kinda like deploy some sort of AI agent and then it kinda monitors this until I get that level of institutional memory or memory?

When is the length of time to get value in this whole approach? Uh, so with, with work spend ai, we, we launched this last quarter and we've, we've been taking our first customers through onboarding. Now, uh, it really comes down to how accessible is your knowledge.

And if you have all of the questions and answers and you've built really good field enablement programs, you can feed those field enablement, uh, uh, call recordings, training decks, the AI will pick those things up and then very quickly be able to disseminate that knowledge to the field. If your data's in good shape and you can feed it quickly, you get value very, very quickly. It doesn't take a long time of passive listening to be able to provide value.

And if you haven't had that, then you need to do some digging. You need to go back through your Slack threads and your emails, find the, the questions and answers so the AI can, can provide the answers that you would provide. You need to do more cleanup if you haven't already organized that data.

But then I think, um, and again, I'm speaking with my own experience using AI and marketing as well as our, our partners using AI in, uh, in their roles. You get into the habit very quickly where you say, oh, if I stay organized, I get this immediate benefit. And I'm not an organized person by default.

You know, I, I have a million sticky notes here on my desk. It takes me a lot of effort to stay organized. And one thing that's really helped me is when I see that immediate return on here's what happens.

If I can provide all these inputs to the AI that then helps my team, the AI trains me to, to provide better inputs and stay organized because the benefits are so immediate. And so we've gotten great feedback from, uh, from our first partner managers that are training their AI and seeing that immediate, oh wow, I can, I can turn all of these questions that I used to have to go and answer on Slack over to my AI teammate now. 'cause I'm confident it, it'll say what I would've said in that situation and take those base level questions from my sales team and then I can go provide better support on the big swing deals that need to close this quarter.

I think every salesperson probably has this experience where they have a call with a customer and then they hang up and about a few hours later they start kicking themselves and say, I should have said this, or I should have said that, or I shouldn't mention this. Well, the AI agent essentially remind them of things that they should say as the conversation's going along. Yeah, I think, um, across, across sales we're seeing this compression where as a seller, you wanna provide as much value in every touchpoint, right?

You're an ambassador not just for your product, but for what it's like to work with your company. And so tools like Zoom and Gong and all these call recorders, I think we're seeing what used to be a very long cycle of let's go back and let's do our QBR and look at our deals that we've won and lost and kind of do some, some introspection on why that happened. All of that is being surfaced into a much more real time immediate feedback.

Let's dissect this call and have the AI look at your talk time. io surfaces for every sales manager to coach their team on. Are you doing too much talking or are you opening up the, the space for your prospects to tell you what, what they need?

And so, uh, with partnerships, same as with the rest of the sales cycle, that that kicking myself, uh, did I say the right thing? Uh, I think all of that coaching now with AI and workspaces, AI teammates is gonna be at the level where you're not just running better deal cycles, you're learning to run better deal cycles with a much faster feedback loop. So I think there's, there's two orders of acceleration here, right?

It's not just the availability of that information in the deal, it's also the availability of those best practices for sales managers to coach the team on, Hey, we could win more deals with our partners if we applied what worked over here on these other, other opportunities that we have in the pipeline. All right, folks, well, hey, sales has always been a game of confidence. And if you have an AI agent that's helping you figure out what your partners are doing and what your customer needs and what's going on in the industry, you're gonna be a lot more confident.

Sam, thanks for being on the show. Thank you so much, Mike. ai video series.

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