6.5 days. That’s how much time each demand planner at Evergreen Garden Care now gets back every month, thanks to an AI agent called Ask Lily.
On 7 October, Evergreen Garden Care and Bolders Consulting Group told that story together on stage at Transformation NOW! 2026, NTT DATA Business Solutions’ customer event, held at the Inspyrium in Cuijk for more than 180 guests. NTT DATA’s recap of the day singles out the session as an example of getting value from AI quickly. Here’s how the project came together.
Start with the work, not the technology
The day’s message was blunt: stop talking about AI and start experimenting. Evergreen didn’t start by asking what AI could do. They asked a narrower question: which recurring manual work in demand planning can we speed up as much as possible?
Every planning team knows that work. Pulling the same figures together every cycle. Chasing down why a forecast moved. Building the report that has to go out before the S&OP meeting. None of it is the planner’s real job, which is judgement, yet it takes up a big share of every month.
What Ask Lily does
Ask Lily is an AI agent that helps Evergreen’s planners with their research and reporting. Two choices made it work:
- It runs inside the Microsoft environment the planners already use. There’s no new system to learn and no separate tool to open. Lily works in the tools the team already has open all day.
- It was built with a team of students. A small, fast team took it from idea to working agent without the overhead of a large IT project.
The result: 6.5 days saved per planner, per month. That’s time that goes back into the decisions planners are there to make. We’ve written before about why the human judgement part of forecasting is where planners add the most value. Lily frees up the hours for it.
The first win is the one that matters most
The time saved is only half the story. Once colleagues saw Lily working, they wanted their own. Evergreen now has forty ideas from different departments, and is looking at each one to see where AI can support the business next.
That’s the pattern we see again and again. A big AI strategy document rarely gets people moving. One small, visible win that saves real time in a real team does. As one attendee put it at the end of the day: start small, because a small victory is how you bring people with you.
What we’d take from it
If you’re wondering where AI fits in your own planning process, Lily suggests three rules:
- Pick a recurring, painful task, not a moonshot. If it happens every cycle, the saving compounds.
- Build where people already work. Adoption is the hardest part of any tool. Remove it.
- Keep it small enough to finish. Weeks, not quarters. Then let the result do the selling.
And don’t make everything an agent. As NTT DATA’s Danny Groothuis said in his session, a plain workflow is often the better choice. Use AI where the work needs it, and use automation everywhere else.
Want a Lily for your planners?
Lily isn’t a one-off. We build the same kind of agent for other planning teams, inside the Microsoft tools they already use, and we start the same way: one recurring task that eats planners’ time.
Most teams can name that task within five minutes. If you’re curious whether Lily fits yours, get in touch. A real person replies, not a bot. Talk to us about Lily →
Thanks to NTT DATA Business Solutions for a great Transformation NOW! 2026, and to the Evergreen Garden Care team for building this with us.
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