When AI reshapes how companies manage partner networks, there is one thing many forget: if your AI can’t be trusted, it’s not really helping. It’s just creating another risk, and becoming yet another thing that partner managers need to take care of.
First things first: AI is reshaping how channel-sales companies do business, but the pace differs. For example, McKinsey’s research on scaling gen AI in the medtech industry shows that adoption of gen AI in regulated industries remains low, especially in areas like knowledge management, marketing and service operations. But this doesn’t necessarily mean that regulated industries are falling behind. They just can’t afford an AI that gets it wrong.
The hallucination problem is very, very real
And generic AI is wrong sometimes. You’ve probably experienced it yourself: whatever AI you use spits out a confident-sounding answer that is either partly, or completely, wrong. This is what we call a hallucination – and it comes from a structural problem in how many large language models work.
Now, this might be alright for personal use, like when you’re having coffee with a friend and debating what movie made Timothy Chalamet famous, and finally just ask the AI. But for the important things, like when a partner asks for the latest product specifications, it just doesn’t cut it. Especially if you and your partner work in a regulated market, when an inaccurate answer won’t just be embarrassing (like telling your friend that Timothy got his breakthrough in Marty Supreme), but could have some very real consequences.
Why generic AI isn’t good enough
Need another reason not to use generic AI tools? Consider this: these tools were built to answer any question, for any user. This is their reason for being. And they will pull information from mixed sources to accomplish it. Sometimes, they even pick things out of thin air, because not answering would mean failing at their job.
But you need something more than that. You have no use for an AI that gives everyone anything they ask for. What you need is an AI that gives the right people the right information, and can explain exactly why they gave some specific answer. In other words, you need an AI that is accurate, and can provide an explanation, with sources, if and when you need it.
Meet PAM
At SP_CE, we’ve spent a long time developing and testing our PAM AI before launch – specifically because we knew and know that trust has to come first. This is why PAM knows nothing at the start, not until you give her access to your approved knowledge base. What’s more, she will never pull information from anywhere else, which means no hallucination, no guessing. Just total accuracy.
And, while partners get quick support, and information, based on their market or geography, you can review ever response and train PAM to provide even better answers in the future.
If you’re curious, here are a couple of things that make our purpose-built AI different:
Four things that make PAM accurate
- 1Human-in-the-loop by design
- 2Source citations on every answer
- 3Hard answer boundaries that prevent misuse
- 4Approved documents as the only knowledge base
Five things that make PAM explainable
- 1
Every answer references an approved document or file
- 2The document version is always known and current
- 3
Access rights are enforced at every level
- 4
Confidence levels and boundaries are visible
- 5
Humans can override or validate when needed
Are you ready to meet PAM?
Book a demo or reach out to us directly to talk more.
This is a part our series on AI-powered partner management.
Previously: Why Partner Account Management breaks at scale, → Partner Manager everyday problems and → The hidden cost of manual Partner Account Management
