Workday Vice President and Deputy General Counsel for Product and Technology Andy Cannon shares how embedding legal and compliance into product development from day one can accelerate timelines, reduce friction, and build customer trust.
Emily Faracca
Multimedia Content Writer
Workday
This episode is available as audio only on Spotify and Apple Podcasts.
Perhaps this pattern sounds familiar: A new product or feature nears completion. Deadlines are looming. Customer anticipation grows.
Then, legal is brought in.
And legal, instead of being a strategic partner, becomes a roadblock. When concerns arise, legal is forced to act as the “bad guy”, held at fault for slowing down launches, triggering last-minute rework, and creating organizational friction.
This pattern often happens when legal is brought in at the end of the development process—after features are built, key decisions are made, and proposed timelines are locked.
Andy Cannon believes in taking a different approach.
As a former developer and now vice president and deputy general counsel for product and technology at Workday, he has a keen understanding of what it takes to build innovative technology. That familiarity shapes how he partners with product teams—not as a gatekeeper, but as a strategic contributor from day one.
In this Workday AI Masterclass, Cannon breaks down how integrating legal early accelerates adoption, strengthens trust, and helps teams ship AI products responsibly and efficiently.
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Adoption doesn’t happen on intention alone. It happens when customers feel technically, legally, and operationally confident that they can introduce and adopt a product at scale.
The introduction of AI raises new questions in a customer’s adoption journey:
When those answers aren’t easy to find by the time of launch, trust erodes. What seemed like a promising product becomes a harder sell.
That’s why Andy Cannon sees legal and compliance not as a post-launch checkbox, but as one of the clearest paths to adoption. When legal is embedded from the start, product teams can anticipate the questions customers will ask, then build the answers into the product experience and supporting materials.
At Workday, that includes privacy summaries, documentation aligned to GDPR and the EU AI Act, and AI-specific factsheets that legal, sales, and product teams can all use with confidence.
By taking this approach, compliance becomes a key driver of customer trust instead of a blocker.
When legal is embedded from the start, product teams can anticipate the questions customers will ask, then build the answers into the product experience and supporting materials.
Too often, legal is viewed as reactive.
Cannon’s team works differently. Legal doesn’t just assess risk after the fact. They help shape how products are designed, discussed, and documented from the beginning.
That mindset is especially important in AI, where legal standards are evolving in real time. Regulations are still taking form, but expectations around transparency, explainability, and responsible use are already here. If product teams aren’t prepared, they fall behind.
Cannon recommends teams can operationalize early legal engagement by:
1. Integrating legal counsel into early product planning: Legal is an active participant in roadmap discussions and design reviews, not just a final QA.
2. Establishing a pre-launch AI feature review process: No AI feature ships without a cross-functional check against privacy, security, and compliance requirements.
3. Providing guidance on feature UX: Legal advises on how to visually indicate when users are interacting with AI, including labeling and icons.
4. Creating centralized collateral: Each feature includes AI factsheets that explain legal principles, privacy posture, and data handling.
Cannon’s team works across the entire ecosystem—from engineering and design, to sales and security.
That cross-functional model matters because customers don’t experience AI features in isolation. They evaluate them across contracts, documentation, data flows, and support. Every touchpoint is an opportunity to reinforce trust.
For business leaders, Cannon offers three key takeaways:
This kind of collaboration gives legal a panoramic view of how products are built, sold, and supported, and helps every team stay aligned.
That cross-functional model matters because customers don’t experience AI features in isolation. They evaluate them across contracts, documentation, data flows, and support. Every touchpoint is an opportunity to reinforce trust.
Not every organization starts with a product legal team, but most reach a point where they need one.
If you’re wondering when the time is right, Cannon offers two questions for legal and business leaders to ask:
1. Does your legal team struggle to understand what the product team is building?
2. Is there frequent friction between product and legal teams that slows down delivery?
If the answer is yes to either, it may be time to embed product counsel.
When a strong product counsel exists, they should be able to proactively reduce friction, along with a few other key outcomes:
Translation between legal and engineering. They make legal language actionable for product teams—and make product decisions understandable to legal stakeholders.
Ownership of AI-specific collateral. They produce factsheets, documentation, and customer-ready narratives that answer tough questions upfront.
Support during escalations. They reduce the load on product and engineering during customer conversations and contract negotiations.
Early identification of risk. They flag legal or compliance concerns during planning—not after the code is shipped.
The most effective legal teams don’t operate in isolation, but rather, in sync with the builders.
That’s been Cannon’s experience across years of partnership at Workday. When legal understands the product, and the product organization understands the legal landscape, decisions are faster, launches are smoother, and trust becomes a shared goal.
Cannon leaves business and legal leaders with four clear takeaways:
1. Prioritize deep product understanding: Legal must know the product catalog and underlying tech to anticipate challenges and guide decisions.
2. Collaborate early and often: Involve legal at the beginning to minimize rework and accelerate delivery.
3. Invest in transparency: Create AI-specific collateral that clearly communicates what a feature does, how it works, and what standards it meets.
4. Stay ahead of the curve: Anticipate regulations before they’re enforced, and build the right controls before they’re required.
What Cannon outlines for legal-product partnership applies across enterprise AI: success doesn’t come from last-minute reviews, but from systems built on alignment and trust. Whether you're launching AI features or scaling innovation across the stack, the path to adoption is the same: early integration, clear documentation, and mutual understanding.
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