I believe human leverage is still the edge, and it’s about to become even more valuable.
You’re seeing it every day, AI is reshaping partnerships and GTM at every angle. As org charts evolve, AI takes grunt work off the table and the best partner strategists use it to multiply their impact, not replace it. Partner teams now balance real-time ops platforms, ecosystem strategy, and AI co-sell engines alongside pitch decks, account maps, and collateral AI can help draft. But fundamentals haven’t changed: the winning leaders decode the customer journey, spot market shifts early, and align product, GTM, and partner value tight. Let’s dive in.
How will AI shape partnership roles?
A few months ago, Andy Jassy said Amazon will likely need fewer people in some roles as AI takes over repetitive work.
That stuck with me.
And I’m sure it did for many others. It’s a reminder that while AI boosts productivity, it also reshapes the roles companies need.
So we have to think about where our skills fit in this shift; and how to lean into the new opportunities AI is creating.
What gets me excited
I believe that AI elevates partnerships. AI may take on the grunt work, but it’s people who bring the human element that orchestrates, aligns, and turns it into success. That’s where the real opportunity lies: to shape outcomes for your company, and the trajectory of your own career. This is the part that gets me excited.
Partnerships has long been a notoriously underfunded function. Headcount is hard to justify, and impact is often difficult to prove when resources are thin. But AI changes that. It gives partner teams leverage, automating the busywork, surfacing insights that once took weeks to uncover, and making partner impact visible in ways leadership can’t ignore. Instead of fighting for scraps, partnerships can finally step into a position of influence, proving value at scale and showing up as a true growth engine for the business.
Partner programs have always evolved. From the early days of basic resale agreements and tiered certifications to today’s multifaceted ecosystems, the function has flexed to match shifts in tech, GTM models, and customer behavior. But nothing has changed it faster, or more profoundly, than AI.
I started my career in partnerships before ‘ecosystem’ became a buzzword. Those early years taught me the fundamentals: build trust, drive adoption, and make things work with limited tools. The landscape looks completely different now, but the core hasn’t changed, and AI is the biggest accelerant we’ve ever seen.
Titles didn’t matter. Like many of you, I did whatever was needed: co-marketing plans, enablement calls, pricing approvals, pipeline reviews, even cold-calling from partner lead lists. Because partnership work has always lived at the intersection of what we sell and how others help sell, service, or integrate it.
What are you seeing in your world? Share your experience and predictions, I read all subscribers’ emails.
Today, AI is reshaping that motion from every angle
Partner teams now live in two worlds:
We’ve got more infrastructure and visibility than ever: Partner ops, ecosystems strategy, co-sell engines, account mapping tools, agentic partner marketing platforms, advanced PRMs, and more.
We’ve got AI tools that can spin up pitch decks, map accounts, score pipelines, draft collateral, create tables, and personalize outreach before we’ve even met the partner.
But the fundamentals haven’t changed. Great partnership leaders still:
Understand how customers buy today and where partners influence that journey
Anticipate where the market and tech (especially AI) are headed
Align product, GTM, and partner value at the seams.
What’s Changing: Center of Gravity, Not Mission
Where do partner teams sit, under Sales, Strategy, or the CEO?
How is partner value measured? Source, influence, integrations, AI reach?
What does co-sell mean in a world where SDRs could be AI agents and account overlap is surfaced automatically?
These questions are shaping today’s org charts and partner motions.
Market Correction, Role Expansion
Between 2022–2024, partner hiring slowed across tech. Budget discipline was back (remember Meta’s year of efficiency?), companies adjusted accordingly. But leaders didn’t pull back, they pivoted.
AWS streamlined incentives and launched GenAI partner tracks
ServiceNow invested in partner-led vertical plays
Microsoft rolled out Copilot designations and improved Partner Center analytics
Snowflake focused on AI-native apps from partners
Some Partner roles are also evolving at some companies:
From Alliance Manager → Partner GTM Architect
From CAM → Partner Success Lead
From partner ops → Ecosystem Revenue Strategy
AI Elevates Partnerships
AI is already doing the grunt work, so partner leaders can focus ion high value items and driving the strategy:
Writing boilerplate one-pagers
Formatting account plans
Pulling contact lists
Building initial QBR slide drafts
What it can’t do is:
Build trust across teams and companies
Navigate channel politics or align incentives
Spot whitespace early or course-correct a stuck co-sell
Design a GTM play that actually gets picked up by sellers
That’s where the human leverage lives. The best partner leaders will use AI not to replace themselves, but to multiply their reach and impact.
What Leading Teams Are Doing Differently
What We Used To Do | What We Do Now |
|---|---|
Send one-pagers and do webinars | Run co-sell campaigns aligned to ICP |
Ask for co-marketing | Co-design plays around mutual value props |
Manual account mapping | Use AI-powered partner intelligence |
Static enablement decks | Build dynamic, AI-powered partner hubs with personalization |
Obsess over deal reg | Track partner velocity, win-rate, and impact |
Final Take: AI Rewrites the Playbook
You don’t need to get the highest grade in prompt engineering, but you do need to:
Understand how AI changes the buyer journey
Redesign how and when partners show up
Speak the same language as your CRO, CMO, and RevOps teams
Hot Take: Anyone can build a partner program. The winners? They get partners to use it.
While we’re at it … Leadership Prompts for Your Next QBR
Where are we using AI to improve how partners execute?
Which parts of our motion rely on hustle instead of scalable systems?
Do we reward influence and ecosystem value, or just deal reg?
Are we training our team on AI-powered tools for partner work?
If we had to 3x partner-sourced pipeline without headcount, what would we change?