Infor CloudSuite consulting

Putting AI agents to work on Infor CloudSuite delivery

7 min read

July 8, 2026

By Rakhita Samarakone

Most people who have run an Infor CloudSuite programme don’t need a definition of ‘slow’. They have felt it – the go-live that quietly slips a quarter, the spec that waits three weeks on the one consultant who understands it, the test cycle that balloons because everything is built by hand. None of it is dramatic on its own. It’s the accumulation that hurts.

So before talking about AI, it’s worth being honest about what slow delivery actually costs.

The real cost of slow delivery

A delayed ERP implementation isn’t just a line on a project plan. It shows up as:

Working capital tied up in a system that isn’t live yet
Finance running parallel processes for months longer than planned
The warehouse, the merchandisers, the planners; all waiting on a platform that was meant to make their jobs easier last quarter

And the quieter cost: ERP programmes run on a small number of experienced people, and those people spend a surprising share of their time on work that is necessary but repetitive. It’s skilled work but not the work that only a senior consultant can do. Every hour spent on it is an hour not spent on the design calls, the edge cases, and the client conversations that genuinely move a programme forward.

Delivery rarely slows for lack of expertise. It slows because expertise is tied up doing work that doesn’t need all of it.

Where AI agents enter the picture

That framing is what pointed us toward agents. Not a flashy use of AI – a narrow question: Could an agent do the first draft of the repeatable, documentation-heavy work well enough that a consultant only has to review and refine, rather than start from a blank page?

The principle underneath it matters more than any single tool:

Change what the consultant starts with. A senior person editing a strong draft is faster and sharper than the same person producing that draft from scratch.
Consistency is as valuable as speed. On a large programme, output that looks the same across the whole team is a quality gain in its own right.
The consultant stays in charge. Anything an agent produces is validated by a senior consultant before it goes anywhere near a client. That isn’t a pilot constraint – it’s how we believe this technology should be used in professional delivery.

What we tested

We ran a controlled internal pilot across our Americas consulting practice – deliberately a test, not a launch. We wanted evidence before changing how we deliver. Consultants used the agents on live delivery work over a fixed window and logged, task by task, how much time was saved and how good the output was.

The findings were strongly directional:

Meaningful time savings on the repeatable work the agents were pointed at
Output good enough to use – most drafts needed refinement, not rework
Every participant would keep using them given the choice

We’d call that consistent enough to act on, and honest enough to keep measuring. What the numbers don’t capture is the shift in how the work felt: less blank-page grind, more time on judgement. That’s the change we were really testing for.

Where this goes next

The pilot settled the question we started with – agents belong in CloudSuite delivery. The bigger one is what happens when they stop being individual helpers and start operating as a system.

We are building toward a delivery model where AI isn’t a tool a few consultants reach for, but part of how the practice works – where the intelligence gathered on one programme compounds into the next, and the distance between a business requirement and a working solution keeps shrinking. Picture delivery teams where the routine is handled and human expertise is aimed almost entirely at the decisions that need a human: the design, the trade-offs, the relationship.

None of these changes the fundamentals. CloudSuite programmes still succeed or fail on understanding the business, designing the right solution, and getting the details right. Agents don’t replace any of that – they give experienced people more room to do the work only they can do, and a faster path through everything else.

For teams delivering complex ERP programmes, that’s a meaningful shift.

FAQ

Which areas in Infor CloudSuite delivery need agentic assistance?

The pilot focused on repeatable, documentation-heavy work: first drafts of specs, test scripts, and delivery documentation that consultants currently write from scratch. These are high-volume, low-judgment tasks where consistency matters as much as speed. As the model matures, we expect agents to extend into configuration documentation, data validation, and status reporting, always with a senior consultant reviewing before anything reaches a client.

Does Velocity Suite help with the delivery side of things?

Not directly. Velocity Suite is Infor’s agentic AI package for running a client’s business processes (sales, finance, supply chain) once CloudSuite is live. The agents in this pilot work on the delivery side instead, drafting the specs and documentation consultants produce during implementation. Together they cover different halves of the same programme: one speeds up building the system, the other speeds up running it.

What does faster delivery actually mean? What's the value?

Faster delivery isn’t about cutting corners, it’s compressed cycle time on the repeatable work, freeing senior consultants for design decisions and edge cases. In the pilot, that meant shorter turnaround on drafts and more consistent documentation across a programme. The value shows up as earlier go-lives, less parallel-running cost for finance, and consultants spending more hours on the judgement calls only they can make.

Where to start if you are thinking about using agentic AI in your Infor ecosystem?

Start narrow. Pick one repeatable, high-volume task, whether that’s delivery documentation or a process like sales order entry, and pilot it with a clear way to measure time saved and output quality. Keep a senior person reviewing everything at first. Once that’s proven, expand deliberately rather than rolling agents out everywhere at once.

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