Who Leads the AI Transformation within Companies?

How Product, CS, and IT Teams Partner to Operationalize AI in Real Workflows

AI capability is accelerating. But adoption is fragile. According to reports, many AI tools and agents will be abandoned by the end of the year.

Not because companies don’t see the potential, but because most SaaS vendors and their customers are still figuring out how to embed that potential into real workflows.

The bottleneck isn’t the model. It’s the system. And transforming the system means translating between technology and how work actually gets done.

This approach was the one we took at Microsoft when I was leading enterprise adoption against stiff competition against the incumbents - Google and Apple. It’s even more important now with the AI transformation, as everything is going to change.

To make that leap, we need two roles to step up:

• SaaS vendors who understand and redesign customer workflows

• IT and Operations leaders inside customer orgs who deploy and adapt those workflows

  And where they meet? That’s where AI transformation happens.

The Partnership for Enduring AI Transformation

The SaaS Vendor's Role: Build AI That Supports Real Work

The next wave of AI-native software won’t win on novelty, it’ll win on deep understanding. SaaS companies must go deeper than feature development and start owning workflow transformation.

This means investing in the discovery work that’s often overlooked or underfunded—understanding not just what users say they want, but how their jobs actually unfold in messy, human systems.

PMs → Redesign the System, Not Just the Feature

Product managers must evolve from feature shippers to workflow designers. That means:

• Mapping end-to-end user tasks, expanding upon simple Jobs-to-be-Done

• Identifying manual, repetitive, or error-prone steps

• Testing where agents, automation, or intelligence can slot in without breaking trust

PMs fluent in both product strategy and the language of AI orchestration will unlock the biggest gains.

Design Researchers → Find the Latent Friction

Great researchers surface not just pain points, but process. They uncover:

• Shadow workflows

• Workarounds hidden from dashboards

• Tacit knowledge that can be codified or supported by AI

Design research is the lens that shows product teams where and how AI can provide leverage.

Customer Success → Your Customer’s Workflow Guide

CS isn’t just about retention anymore, it’s about transformation. Success teams sit closest to customer reality and are uniquely positioned to:

• Identify which customers are AI-ready

• Educate stakeholders on new capabilities

• Partner with internal ops teams to rewire old habits

In the AI-native era, CS becomes the bridge between product intent and customer transformation.

The Customer’s Role: Operationalize the Change, Don’t Just Buy the Tool

Inside customer organizations, the role of IT and Operations becomes more strategic than ever. No matter how good the AI product, value only gets unlocked when it’s adopted into actual work. This has always been the case, but it’s even more important now.

This is not about installing software. It’s about building confidence, reshaping processes, and learning to collaborate with software that thinks.

IT & Ops → From System Maintainers to Change Agents

These teams have a front-row seat to their company’s:

• Process inefficiencies

• Tooling gaps

• Integration points

• Security and compliance constraints

• Communication and education channels and processes

They know how information flows across the org, and where it breaks. That makes them ideal partners in helping teams pilot AI workflows, validate outcomes, and scale usage. They’re not gatekeepers. They are enablers.

But they can’t do it alone. They need partners.