Four posts ago, we started with a pattern we’d seen before. A new capability enters the ERP market, organizations assume the built-in tool will be enough, and most find out otherwise after spending time and money to learn it the hard way. We’ve walked through why an AI feature bundled into your ERP isn’t automatically the AI solution your organization needs, why so many initiatives stall before they get anywhere, and what separates the ones that don’t.
This last post looks at what comes next, for the market and for us.
This isn’t a moment. It’s a direction.
AI in ERP environments isn’t a feature cycle that settles down once the hype cools. It’s a shift in what organizations can expect their systems to do for them, and that shift compounds. The organizations pulling ahead right now are doing the unglamorous work: cleaning up their data, getting specific about which problems are actually worth solving, choosing technology built to grow with what comes next instead of just what’s needed today, and finding a partner who knows the platform. That work doesn’t just put them ahead this year. It’s what keeps them ahead as the tools keep improving, because the foundation is already there.
Andrew Bediz, our AI and UX practice lead, put it simply when we talked about what makes enterprise AI valuable in the first place:
“The real magic is rather than having to check in on four different systems, the AI is doing it all for you. It aggregates it, compares it, contrasts it, joins it together, and gives you an answer.”
Reaching that kind of system takes both a product built for it and a partner who knows how to make it work inside a live enterprise environment. Neither one gets you there alone. The product has to be built right. The methodology behind it is what makes sure it’s applied right.
We’ve been building toward this for a decade
Gideon Taylor didn’t arrive at AI because the market did. Andrew Bediz and the team behind Ida have been building enterprise AI since 2016, years before most of the market treated it as more than a novelty, and that same team is still the one building it today. That depth is what makes the technology capable in the first place. Alongside that AI depth is more than two decades of hands-on PeopleSoft process automation experience, the same expertise that’s always set GT apart. Together, they’re why we can speak to what good AI looks like in an ERP environment with the same credibility we’ve always brought to ERP itself.
That combination shows up directly in how Ida.Next works. It’s agentic-native, meaning it reasons through each request and takes action rather than following scripted steps someone has to build and maintain ahead of time. Running it takes up to 95% less manual effort than it used to. That’s what decades of ERP experience paired with deep AI expertise buys you.
Ida.Next’s reach also extends well beyond PeopleSoft. It can connect to Oracle Fusion, ServiceNow, Salesforce, and Workday, so organizations running a mix of systems get one platform instead of one per system. And it’s built with enterprise data handling in mind from the ground up, including automatic redaction of sensitive fields before any data reaches the underlying model.
Paul Taylor, our CEO, described where the product itself is headed:
“I think Ida.Next will be that corner turn where people really can buy the product, get the training, and do it themselves from there. You’d still get more value if you used us as a partner, but the product is crossing that threshold.”
Crossing that threshold doesn’t take the partner out of the picture. It just moves where the partner adds value. Ida.Next now carries more of what we used to have to deliver by hand, built directly into the product. What a partner is still for is the piece no product can do: designing the processes your organization runs on, so the technology fits how you operate instead of the other way around.
What this means for you
If there’s one thing this series should leave you with, it’s this: the organizations we’ve watched succeed didn’t try to build it alone, and they didn’t settle for whatever AI happened to ship with their system. They got specific about the problem in front of them, invested in the groundwork, and brought in people who had already done it. That’s not a complicated model to follow. It’s just one a lot of organizations skip, usually because one of those two paths looked easier at the time.
This is the final post in our five-part series, Steady in the Storm: What We’ve Learned About AI in ERP. Thank you for following along.
Ida.Next is built to put this into practice: one platform that connects across the systems you run, backed by a team that’s done this before. If you want to see what that looks like for your organization, reach out below.
Gideon Taylor has spent more than two decades helping higher education, public sector, healthcare, energy, and enterprise organizations navigate change in their ERP environments, and more than a decade building the enterprise AI that stands alongside that experience today.
