Pillir

06/08/2026

Why SAP ECC Customers Are Re-Evaluating Their AI Strategy

TL;DR
Many organizations running SAP ECC want to take advantage of the latest AI capabilities.

The challenge is that AI innovation is accelerating while ERP transformation programs remain complex, expensive, and long-term initiatives.

As a result, many organizations are exploring ways to bring AI closer to ECC environments while continuing their modernization journey.
-----()-----
The conversation around enterprise AI has changed dramatically over the last 18 months.

What started as experimentation with chatbots and copilots has evolved into discussions about agents, automation, and intelligent business processes.

For many SAP customers, that creates an important question.

How should AI fit into an environment that still relies heavily on SAP ECC?

The answer is not always straightforward.

Most ECC environments have been shaped over many years.

Custom business processes.

Industry-specific requirements.

Thousands of decisions embedded into workflows and configurations.

These environments are often deeply aligned with how the business actually operates.

At the same time, executive teams are increasingly asking for AI roadmaps that deliver measurable business outcomes.

Faster procurement.

Improved supply chain responsiveness.

Reduced administrative effort.

Better visibility across operations.

The challenge is that AI expectations are accelerating faster than many ERP transformation programs.

This does not mean organizations should abandon modernization plans.

Nor does it mean that existing ERP systems cannot evolve.

Instead, many technology leaders are beginning to ask a different question:

How can we introduce AI capabilities while continuing to protect the investments already made in existing systems?

That shift in thinking is important.

The discussion is moving away from "modernize first, innovate later."

Instead, it is becoming:

"How do we innovate while modernizing?"

For SAP ECC customers, that may become one of the most important technology decisions of the next few years.

Because business demand for AI is not waiting for project timelines to catch up.

Question: Should AI initiatives be dependent on ERP transformation timelines?

https://bit.ly/3Qm6MDt

05/25/2026

As we observe Memorial Day, Pillir joins the nation in remembering the heroes who laid down their lives for our freedom. We are profoundly grateful for their service and sacrifice.

We hope your day is filled with meaningful reflection, community, and time spent with loved ones.

05/21/2026

One of the biggest shifts happening in enterprise AI right now:

AI ex*****on is increasingly available for modern ERP environments.

But many enterprises still run the business on:
1. ECC
2. Oracle EBS
3. JD Edwards
4. deeply customized installed-base systems

Those environments still power:
1. manufacturing
2. procurement
3. warehousing
4. supply chain operations
5. field ex*****on

The challenge is not whether AI can execute.

The challenge is whether installed-base enterprise systems can participate without a 5-year migration program.

That is becoming one of the most important operational questions for enterprise IT leaders.

https://bit.ly/4eQ1REI

05/19/2026

This is what AI ex*****on inside SAP ECC actually looks like.

Before:
Inventory confirmations updated at shift end.
Now:
Operators confirm work in natural language.

AI executes directly inside ECC.
Inventory updates happen in real time.

For many installed-base ERP environments, this capability still requires:
1. migration
2. middleware
3. major modernization projects

This approach runs directly on the ECC landscape already in place.

https://bit.ly/43kEAUc

This demo shows how Claude Cowork identifies stockout risks directly inside SAP and generates mitigation actions — enabled by Pillir.In one prompt, it:Reads ...

04/21/2026

We’ve solved visibility.

In most enterprise environments, you can see:
what’s happening
where it’s stuck
what needs to happen next

That used to be the hard part.

Now it’s different.

Work doesn’t slow down because we don’t know.

It slows down because it doesn’t move on its own.

There’s always a moment where someone has to step in.

Check something
confirm something
trigger the next step

And that’s where time quietly disappears.

Not inside the process
but between the steps

If this feels familiar, it’s probably worth looking at differently.

What needs to happen nexthttps://pillir.ai/

04/21/2026

A lot of enterprise teams are chasing better insights.

Better dashboards
Better reporting
Better visibility

And those matter.

But in most environments, visibility isn’t the constraint anymore.

You can usually see where things are stuck.

The harder part is what happens next.

Who moves it forward
How quickly it progresses
How many steps it depends on

That’s where time gets lost.

And it’s not always obvious from the outside.

If this is something you're running into, would be interesting to compare notes.
https://na2.hubs.ly/H04_d-Y0

04/21/2026

Most conversations around enterprise AI focus on capability.

What models can do
How accurate they are
How fast they respond

But that’s not where things break down.

The real issue shows up later.

When something needs to actually move forward inside a system.

That’s where delays happen.

Not because the answer isn’t there.

But because ex*****on still depends on how work gets triggered, validated, and completed.

It’s a small shift in perspective.

But it changes where you look for impact. Curious if others are seeing the same pattern in their environments.
https://na2.hubs.ly/H04_fp80

04/15/2026

https://na2.hubs.ly/H04V9LQ0

04/15/2026

Here’s the simplest way to understand the problem. And the shift.

Today:
AI layer
→ generates insights
→ sits outside SAP ECC / Oracle EBS

ERP systems
→ run transactions
→ remain unchanged

So what happens?
AI suggests, People execute
That’s the bottleneck.

Now imagine a different setup:
AI understands the workflow
→ connects to the system
→ executes inside it

No switching between systems
No manual follow-ups
No delays

The system actually changes.
That’s what makes AI useful in environments like ECC or EBS.
Not intelligence.
Ex*****on.
👉 Learn more: https://bit.ly/4epmW8B

04/15/2026

Let’s simplify what this really means.
When people hear “AI in enterprise,” they assume:
+ New platforms
+ ERP upgrades
+ Long transformation timelines

Especially if you're running:
+ SAP ECC
+ SAP Business Suite
+ Oracle EBS

Because these systems are not easy to change.
So AI ends up sitting outside. And the core system stays untouched.
That’s why most initiatives don’t go far.
What if that assumption is wrong?
What if AI could work inside these systems without upgrading or replacing them?

That’s the shift.
Not better models.
Not more tools.
Ex*****on inside the systems you already have.
👉 See how this works: https://bit.ly/4tcZjF1