AI made content creation instant. Everything after it? Still slow. Work waits in queues, reviews crawl, and good ideas go stale before they go live.
Road Scholar hit that wall too. Thousands of product pages all have to meet the same written guidelines, and checking them by hand was work measured in months, not hours.
So they built an agent to do it. One person now runs the audit, the same people keep the same oversight, and the agent catches more inconsistencies than the manual process did, so the error rate came down.
So they built an agent to do it. One person now runs the audit, the same people keep the same oversight, and the agent catches more inconsistencies than the manual process did, so the error rate came down.
In this session, Road Scholar, Nansen, and Optimizely show how it happened, what it took to get the first version accurate, and how to find the right first use case in your own team.
Road Scholar brings the proof. Nansen brings the method. Optimizely brings the platform.
Road Scholar brings the proof. Nansen brings the method. Optimizely brings the platform.
What you'll walk away with
- Why saving time is the wrong goal, and how to manufacture it instead
- Where to look: repetitive and codified work, high-volume work with slight variations, and anything reviewed against a standard
- How to score a use case on business impact, operational effort, and organizational readiness
- Why to start small: the first agent is the most expensive, and by the fourth the team has time back
- How governance, guardrails, and human sign-off keep it safe
- What Road Scholar did with the time it got back
Who it's for
Marketing leaders and operations teams who are:
- Looking for their first AI use case, or the next one
- Stuck with slow reviews, approvals, or manual checks
- Trying to scale AI without losing oversight
Whether you're evaluating AI for the first time or scaling what's already working, you'll leave with concrete examples and a framework for choosing your next opportunity.
Start with one task
Pick the review, approval, or check your team repeats every week. Then find the agent that could take it on, with your people still signing off.