SAP S/4HANA Readiness Assessment with Agentic AI

SAP S/4HANA Readiness Assessment: Know Your SAP Estate Before You Migrate

Ask an SAP team how many custom objects they run and the answer is an estimate. Ask which of those still work unchanged on S/4HANA, which have not executed in a year, and what each one costs to fix, and finding out becomes a project in itself.

That uncertainty is why S/4HANA programs go over budget. The budget was approved against a guess, and the guess was low. A SAP migration assessment closes the gap before the money is committed, by reading and scoring every object rather than sampling a representative few and extrapolating from them.

What the SAP Agentic AI Assessment Analyzes

The SAP S/4HANA assessment reads code and metadata. It does not need your business data. Three things are analyzed.

Custom Code and ABAP Assessment

The SAP custom code assessment covers every program, report, function module, class and include in the custom namespace, plus the enhancements and user exits layered onto standard SAP. Each object is scored against S/4HANA simplification items and the changed data model, so you know what breaks before testing finds it.

SAP Integrations and Dependencies

Interfaces, integration points, custom tables and data dictionary objects, mapped into a dependency graph showing what calls what. This is the part manual assessments rarely finish, because tracing what calls what across a fifteen-year-old estate is exactly the kind of exhaustive work a person runs out of patience for and software does not. It is also the part that decides the order the work has to be done in: you cannot retire an object that something you are keeping still calls.

S/4HANA Readiness Scoring

Every object in the SAP custom code inventory is classified as compliant, needs remediation, or retire, and the estate as a whole gets a readiness rating with the specific blockers named. Runtime statistics show what actually executes, which is usually how teams discover that a large part of the estate has not been used in years.

Remediation Effort and Cost Estimation

Each object that needs work carries an effort figure in hours and a cost derived from it. The total is built up from the objects themselves rather than divided down from a budget.

This is what makes an S/4HANA migration assessment usable in a budget conversation. A readiness percentage tells a steering committee nothing it can act on. A line-item cost, with the heavily enhanced programs that carry most of it identified by name, does. Where remediation is the next step, the same scored inventory feeds straight into automated ABAP code remediation, so nothing is analyzed twice.

What You Receive

• A scored custom object inventory. Every custom program, enhancement, table and interface, classified compliant, remediate or retire. No sampling, the full repository.
• An overall SAP readiness assessment rating with the blocking items named.
• Effort and cost per object. When someone asks how the number was reached, the answer is a list, not a methodology.
• A dependency map showing what has to move together, so sequencing is based on evidence.
• A recommended migration path — brownfield, greenfield or selective transition — with the reasoning stated and chosen from what the assessment found rather than from preference.

The output is designed to survive a board meeting. If someone asks why the remediation estimate is what it is, the answer is a list of objects.

How the Assessment Works

Scope. Agree what the agents read, where analysis happens and what is retained. Extraction can be limited to specific packages.

Extract. Pull the custom repository, enhancements, interfaces, dictionary objects and runtime statistics. No production business data required.

Classify. Score every object against S/4HANA as compliant, remediate or retire, and build the dependency map.

Cost. Attach effort and cost to each object needing work, so the total is evidence-built.

Review. An SAP architect walks the findings, removes the false positives, and hands over a report that survives a board meeting.

Who Should Use This Assessment?

• Teams facing the 2027 ECC deadline who need a defensible number before committing to a program.
• Organizations mid-way through a business case where the custom code figure is still an estimate.
• Teams who have had an assessment that sampled and want every object scored instead.
• Anyone choosing between brownfield and greenfield who wants the decision made on evidence.
• Programs already underway where the remediation backlog is growing faster than planned.

In each case the SAP transformation assessment does the same job: it replaces an estimate with a counted figure.

SAP Agentic AI Assessment Use Cases

• Building the S/4HANA business case. The custom code line is usually the least reliable number in the paper. A SAP AI landscape assessment makes it the most reliable one.
• Choosing the migration path. Brownfield, greenfield or selective transition, decided against what your code will actually survive rather than against a preference.
• A second opinion on an existing assessment. Where an earlier assessment sampled and extrapolated, this one counts. The two are usually some distance apart.
• Carve-outs and divestments. Establishing which custom objects belong to the entity being separated, and what follows it.
• Cleaning up after a conversion. Estates that converted under time pressure carry remediation debt nobody inventoried. This finds it.
• An annual technical debt review. Run against a stable estate, the same analysis shows what grew, what died and what is now worth retiring.

Three patterns come up in almost every estate we assess. Dead code is larger than anyone expects: a substantial share of custom objects have not been executed in years, and every one of those is remediation effort you can decline to spend. The expensive objects are not the obvious ones: remediation cost concentrates in a small number of deeply enhanced programs rather than spreading evenly across the repository. Performance problems are already visible: the same analysis that finds S/4HANA blockers finds the anti-patterns behind slow reports, which is why assessment and performance optimization are usually bought together.

Results and Case Studies

The same agentic approach applied to production SAP estates has produced:

• Up to 99% faster SAP reporting for a global footwear manufacturer
• Up to 80% faster ABAP reports for a global cement manufacturer
• 70% faster dispatch and billing workflows for a global steel manufacturer

In each case the functional output was unchanged. Only the time taken moved. Read the case studies.

Why 2iSolutions

Twenty years of SAP delivery sits behind the agents. We have been a certified SAP partner since 2005 and have run implementations, conversions and support across the United States and Canada since then.

Every change an agent proposes is reviewed by an SAP architect before it reaches you. The agents compress the reading; the judgment stays with people who have done the work.

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