In this special Kiflo Q&A live session, we were joined by Patrick M. Ferdig, Founder of The Power of Partnering, for an eye-opening session on how artificial intelligence is reshaping partnership management. Patrick, who works directly with B2B technology and service providers to develop and execute partner-led growth strategies, shared practical examples of how AI can enhance the work of partnership professionals.
This wasn’t another theoretical take on AI. Patrick focused on real use cases he’s implemented for clients, showing how AI agents and integrated tools can drive efficiency, improve decision-making, and ultimately scale partner programs in powerful ways. Here’s a detailed recap of the conversation and why every partner leader should pay attention.
AI Agents Are the Next Step in Workflow Efficiency
Patrick kicked things off by explaining what makes an AI tool an agent. According to him, it’s not enough to use a chatbot or write prompts manually. A true AI agent is integrated into your existing tools, runs in the background based on workflows, and automates a task from start to finish without human intervention at every step.
An AI agent should meet five key criteria. It must use an AI model or large language model under the hood. It should be triggered by a defined workflow or business process. It should not require live prompt writing every time. It must perform useful work such as analysis or content generation. And most importantly, it should produce output in the right format and within the platforms where you already operate.
The big idea here is that AI is most powerful when it removes friction from your day-to-day tasks, not when it adds another layer of manual work.
A Simple AI Use Case: Generating Joint Value Propositions
One of the first examples Patrick shared was a simple but effective proof of concept using Agent.AI. By feeding in basic inputs about two companies, this tool automatically generated a joint value proposition in seconds. It reused a consistent prompt in the background, eliminating the need to rewrite instructions every time.
Although this example was intentionally lightweight, it demonstrated how AI agents can quickly generate repeatable, standardized outputs. This is especially useful when trying to create uniform partner marketing assets or prepare introductory content.
The agent not only saved time but created more consistent messaging, which is critical when communicating with dozens or hundreds of partners.
A Deeper Workflow: Ideal Partner Profile Assessments
Patrick’s second example moved from a prototype to a real-world engagement with a client building their partner program from scratch. After defining the Ideal Partner Profile (IPP), they needed to apply it practically. That meant profiling a list of potential partners to determine who best matched the IPP.
Using Relevance AI, Patrick created a custom agent that would retrieve relevant information from partner websites, assess that data against the IPP rubric, and assign a relative score to each potential partner. The agent automated research and evaluation, providing a prioritized list that helped a new partner manager plan outreach more strategically.
This use case highlighted the real value of integrating AI with decision-making. It wasn’t just about generating text. It was about augmenting intelligence and providing actionable insights.
The “Easy Button” for AI-Driven Partner Insights
Patrick then presented what he called his “easy button", a powerful workflow that combines multiple AI functions into one seamless action. Using Zoho CRM and Clay (a spreadsheet-style tool with AI capabilities), he built a system where clicking one button on a CRM record would automatically trigger partner research, enrich the data with LLM-powered insights, evaluate the partner against the IPP, and return all that information back to the CRM.
The agent not only researched company websites to identify customers, industries, and partner relationships, but it also generated a joint value proposition and scored the partner in alignment with the predefined profile.
This saved hours of manual work and allowed partner managers to act quickly and confidently. Patrick emphasized that this kind of system turns AI into a force multiplier for partner teams.
Scalable Partner Enablement with AI Video Content
Beyond evaluation and outreach, Patrick also showcased how AI can streamline partner enablement. By using tools like Synthesia to generate video content from text scripts and integrating those videos into learning platforms like Articulate, he created scalable training programs that eliminated the need for repetitive live sessions.
AI-generated videos are not only easier to update and personalize, but they also allow teams to scale enablement efforts without compromising on quality. Partners can receive timely, relevant content on demand, helping them onboard faster and stay aligned with your messaging.
Patrick noted that while some users can still tell the videos are AI-generated, the benefits in agility, consistency, and speed far outweigh the trade-offs.
What Comes Next: Model Context Protocol and Seamless Integration
To wrap up the session, Patrick discussed where AI for partner teams is headed. The future lies in API-based automation and emerging technologies like the Model Context Protocol, which will allow AI agents to directly access and control business tools like Slack, CRM, and project management software. Rather than switching between tools, partner professionals will simply make requests in natural language, and AI agents will take action across platforms automatically.
This kind of seamless, cross-tool interaction is where partner teams can expect even greater leverage from AI, reducing manual work, improving precision, and speeding up execution.
Final Thoughts
Patrick made one thing clear throughout the session. AI is not here to replace partnership professionals. It is here to empower them. When used correctly, AI becomes a teammate that handles the repetitive and research-heavy tasks, freeing up partner managers to focus on strategy, relationship-building, and growth.
Whether you are just beginning to explore AI in your partner program or you are already experimenting with tools, now is the time to learn, test, and iterate. AI is evolving quickly, and those who start building today will have a significant advantage tomorrow.
