A Horse of a Different Color: Alliance Managers and AI

Posted By: Jon Lavietes Member Resources, Collaborative Connections,

The February Collaborative Connection Monthly tackled a question that has been on many an alliance professional’s mind, related to a topic “that has a lot of attention from today’s press and conversations,” in the words of the event’s moderator, Norma Watenpaugh, CSAP, principal of Phoenix Consulting Group: “AI: Gift Horse or Trojan Horse for Partner Managers?” 

To help answer the question, Watenpaugh turned to his month’s featured guest, Will Yafi, who as founder and CEO of ecosystem enablement software vendor TIDWIT has dabbled in artificial intelligence (AI) in both his personal and professional life

Once Upon a Time…Not in Hollywood: AI Reality, from Narrow to Super

In order to answer the event title’s question, Yafi first had to clarify what AI can and can’t do—and even before that, he had to divulge the three main types of AI for the audience:

  • Narrow AI – The use of an algorithm to make very specific decisions, such as an insurance company assigning a risk score based on rules, past history, and other variables, or particular functions, such as facial recognition software
  • General AI – A vast amount of data helps this form of AI think almost like humans. The most prominent application in this category is arguably ChatGPT, the software that scours the internet and summarizes its findings in minutes. General AI is “fascinating a lot of people,” said Yafi. 
  • Super AI – This form conjures up those dystopian visions of robot races taking over the world à la the Terminator movie franchise. But not to worry—Super AI does not actually exist, “except in Hollywood,” said Yafi, who added that even advanced physicists don’t think we will have anything like Super AI for several decades.

Alleviating the Pain of the Mundane

So back to that original question. Even in AI’s relatively early stages, it appears the answer is “gift horse,” in many respects; the early tried-and-true use cases are impacting the alliance manager’s day-to-day job and streamlining alliance practice operations by reducing the pain of the mundane. In fact, Watenpaugh summed up one of both her and Yafi’s principal pieces of early wisdom on the subject when she advised listeners to “automate as much of the process as you can” to free up time for activities that are “value-creating.” Or, as Yafi put it, “We’re seeing the use of General AI in order to gain back some time and invest that time into business relationships.”

Applicable uses start with something as comparatively simple as converting a Word document into a PowerPoint presentation, which saves hours of work. In fact, of the companies that already have fully implemented AI services, 87 percent of those aimed at gathering, integrating, and formatting data have netted an ROI of over 5 percent, according to a recent Deloitte study.   

Getting MDFs, Vouchers, and Partner Selection Under Your Thumb

Yafi disclosed a couple of other uses of AI that apply more directly to alliance management affairs, including: 

  • Dispersal of market development funds (MDFs), which partners use for marketing initiatives related to joint offerings – With limited marketing money and hundreds of partners, machine learning (ML) algorithms “allow [tech companies] to see which partners are performing or are likely to perform much more effectively,” which is “a more scientific way of doing it” than just “sticking your thumb in the air,” quipped Yafi. 
  • Voucher distribution – Similar to MDFs, technology companies usually offer vouchers as a benefit of partnership. In a vacuum, figuring out how many a single partner deserves and delivering those vouchers to the counterpart at the allied organization isn’t an overly onerous task. But: “Multiply that by 10 different providers and 100 different partners. That actually takes tens if not hundreds of hours of work,” said Yafi. AI can expedite the process of stack-ranking voucher eligibility by merit. 
  • Partner selection – With a wide variety of channel partners, distributors, resellers, regional systems integrators (SIs), and strategic technology partners, partner portfolios can run in the thousands. Many tech outfits help streamline partner selection by offering a self-service application form prospective partners can use to submit their candidacy. AI algorithms can help weed out partners that can’t demonstrate basic requirements in the initial screening. “If [applicants] cross that benchmark, [organizations] continue with the process of [partner] selection, or [the prospect] is rejected outright,” Yafi explained. “What you’re doing is essentially filtering out a lot of potential partners that don’t meet that benchmark, saving time in that selection process.”

Once in a While You Get Shown the Light: AI and “Mass Customization” 

More generally, AI helps alliance practices deliver a “mass customization” of the partner experience that balances the efficiency of automation without sacrificing that personal touch for each partner. Yafi acknowledged that adapting processes to each partner’s way of operating “is no easy task” and doing so manually is a “nightmare,” especially since “a lot of these alliance and partner managers are inundated with requests that are fairly mundane,” such as delivering a particular piece of sales collateral or pointing a partner to a relevant training session. Many alliance professionals still aren’t aware of how much AI can streamline these requests while still serving in the way each of these partners, which come in all shapes, sizes, and personalities, prefers.  

“Once they do see this many-to-many approach that allows them to offload [bureaucratic tasks] through artificial intelligence and other automation technologies, giving them back time to invest in business relationships, then they see the light,” said Yafi. 

Tomorrow Never Knows, but AI Delivers Today

Yafi, a self-described “hopeless technologist,” is so enthusiastic about AI, he even wrote a novel titled Fina, a “love story” set later in the 21st century where AI figures more prominently in people’s daily lives. Yafi conceded that it was challenging to write about the future “because I had to imagine a world that doesn’t exist just yet.” Asked if AI could have helped bring the book to fruition quicker, Yafi demurred. 

“Frankly, I am not sure if anyone has attempted to write a novel with ChatGPT-like tools, or has done so. I suspect someone must have tried, although I fear the exercise may yield an easily identifiable and somewhat mundane writing style for a novel,” he said after the event. 

Which returns us, once again, to that question: gift horse or trojan horse? It’s the former, as long as you know where it can be effective.  

“Educate themselves on the possibilities of what they can do with AI and what they may not be able to do with AI,” said Yafi. “Use it for what it can deliver today.”

An Octopus’s “Walled Garden” in the Shade

As for tomorrow, AI use cases will proliferate as the industry improves privacy protections. Individuals and organizations that have fed private data into ChatGPT and other public AI tools have had to grapple with the ramifications of that information being publicly accessible. AI data governance measures are emerging to help balance the privacy and efficacy of AI applications. 

“How do you keep it within the realm of whatever is acceptable to you and keep it private? [Ecosystems] can wall off the data on which the AI brain can be applied,” said Yafi. “[These] ‘walled gardens’ protect the data and keep the knowledge upon which you want to apply AI within the limited sphere you want to apply it.” 

Pretty soon, AI applications that can free up alliance managers to focus on high-level tasks will be so ubiquitous—and safe—they may need eight arms to get their tentacles around them.