From Manual to Autonomous

Learn how customer self-service exposes hidden gaps and prepares SAP environments for AI-driven automation.

Executive Summary

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Most manufacturers are closer to SAP's autonomous enterprise vision than they think, but they're blocked by a problem that has nothing to do with AI readiness. The problem is operational: customer-facing workflows that still live in service reps' judgment, email approvals, and manual exception handling rather than in governed, executable SAP logic.
"But technology alone, and plugging AI agents into your existing system landscape will drive zero value. Moving to the Autonomous Enterprise requires serious change management." Christian Klein, CEO, SAP | SAP Sapphire 2026
That challenge has a concrete answer. This paper describes it. SAP's Autonomous Enterprise vision is clear. Joule Assistants and Agents are meant to coordinate data, applications, and workflows, then execute complex business work with governance, auditability, and enterprise context.2 SAP is equally clear about what that requires: accurate, structured business data, proven workflows, and established governance models. For most manufacturers, those preconditions are only partially in place. This paper argues that Corevist functions as an operational forcing mechanism. Because it exposes customers directly to live SAP-backed self-service including pricing, availability, order history, shipments, invoices, and order placement, any hidden inconsistency becomes visible at the moment of customer demand. That visibility forces the business to make a decision, codify the authoritative rule, and place it in a governed layer. Over time, hundreds of such decisions accumulate into a more structured, observable, and repeatable operating environment. The practical sequencing is straightforward: use Corevist to move customer operations from manual to structured; then layer AI assistance; then expand to supervised autonomy. Corevist's BTP certification matters here because it keeps the self-service layer on the right side of SAP's clean-core direction as that roadmap matures.
Customer Story

Emmerson Packaging put this into practice — and eliminated manual order entry for 60% of their customer base in the process. Read how they did it.

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The Problem

When customers cannot reliably self-serve against accurate ERP data, they call or email. Emmerson Packaging3 learned this the hard way. When their prior portal was lost during an ERP migration, customers flooded service with questions. The team nearly doubled customer service headcount. A static once-a-day replacement site left customers, in their own words, "flying blind." The fix wasn't more headcount. It was putting customers directly against live SAP data. Consider what it actually takes to fulfill a customer order correctly in SAP: a pricing rule must apply, a ship-to location must be valid, a split-shipment preference must be defined, an approval threshold must be set, and an ATP exception path must be governed. For most manufacturers, some of those conditions are handled in SAP and some are still handled by people. The order record stored in SAP is only the final artifact. The authoritative path that produced it may still run through human judgment. This is why "AI can read SAP order history" is true but incomplete. Reading history is easy. Acting on it reliably requires that the underlying workflow be defined, governed, and executable, instead of reconstructing from memory or email every time a customer asks.

What This Looks Like in Practice

Consider a representative customer request:
Request Repeat last quarter's order. Ship half to Dallas immediately. Balance next month. Use the agreed promo pricing.
This single request touches six distinct workflow conditions. Here is what happens before Corevist, during the first self-service attempt, and after the rules are codified:
Request Element Before Corevist First Attempt in Corevist After Codification
Reorder last quarter's order A service rep knows which items are still valid. Some items are hidden, blocked, or not reorderable. Reorder eligibility and product visibility rules are defined.
Ship half immediately The rep decides how partial shipment should work. The system has no clear split logic. Partial-shipment and ATP rules are standardized.
Ship to Dallas The rep uses an informal workaround for a new facility. Dallas is missing or fails validation. Ship-to hierarchy and master data are corrected.
Use the agreed promo pricing The rep applies an email-based override. The portal shows standard price or rejects the discount. Pricing condition or approval workflow is formalized.
Balance next month The rep coordinates delivery timing manually. Backorder or date-handling behavior is unclear. Scheduling and backorder rules are defined.
Submit and confirm The rep resolves errors off-stage and explains the result. The customer sees an SAP exception or ambiguous confirmation. Exception routing and customer-facing status messaging are standardized.
The first broken interaction is not a setback; it is the mechanism of progress. Each surfaced failure forces an authoritative business decision. And a decision, once made, can be codified in a governed layer where AI can act on it reliably.

Why the Problem Never Stops Growing

Customer-facing operations have a predictable tendency: exceptions, workarounds, and new demands always arrive faster than the formal systems that are supposed to govern them. New facilities get acquired. Promotional pricing programs are negotiated. Partial-shipment preferences change. Substitute products become acceptable in one region but not another. A strategic account gets special handling during a launch. None of this is abnormal. SAP itself says process automation is needed because businesses face unique requirements and changing market conditions. The recurring requests in manufacturing are easy to recognize:
  • Use the approved substitute if inventory is short.
  • Split the order across our East and West plants.
  • Apply Canadian contract pricing to this Quebec ship-to.
  • Do not ship partial hazardous-material orders.
  • Route anything above $50,000 through procurement approval first.
The point is not that any one request is exotic. It is that they never stop arriving. And before Corevist, each one is absorbed quietly by a service rep, which means the business never has to decide the rule. Manufacturers often feel uneasy when customers begin interacting directly with SAP master data, because that data was not configured with customers in mind. That discomfort is actually the signal that the forcing mechanism is working. The operational environment is not static, and a customer-facing system reveals that immediately.

How Corevist Forces the Issue

Corevist sits on top of SAP and gives customers real-time access to pricing, availability, credit, order status, shipments, invoices, and reorder-from-history capabilities. Customer orders flow directly into SAP. Catalogs are driven by SAP master data. Product restrictions and account-specific views are enforced automatically. Access aligns to SAP authorizations. In operational terms, that means the customer is no longer asking a person to interpret the workflow; the customer is exercising the workflow itself. Before self-service, a service rep bridges gaps quietly and the business never has to decide the rule. After self-service, every broken price, invalid ship-to, and ambiguous policy becomes a visible failure that the customer sees. That visibility forces a decision. And a decision, once made, can be codified.

The Forcing Function Loop

The sequence is not a theoretical architecture diagram. It is the practical operating loop created when customer demand is placed directly on top of live SAP logic:
Step Stage What Happens
1 Customer Request Customer places a request through Corevist self-service against live SAP data.
2 Gap Exposed The system cannot execute cleanly. A broken price, invalid ship-to, unclear split logic, or missing approval rule surfaces as a visible failure.
3 Business Decides The failure forces an authoritative business decision. The rule can no longer be deferred to a service rep's judgment.
4 Rule Codified The decision is placed in the correct governed layer: SAP pricing, master data, BTP workflow, or Corevist configuration.
5 Repeatable Workflow The transaction becomes structured, observable, and executable by the system, and eventually by AI.
6 AI Acts With governed rules in place, AI can validate, route, explain, and auto-execute low-risk transactions reliably.
Corevist exposes the issue, the business resolves the rule, the workflow becomes repeatable, and only then does AI have a trustworthy surface for execution.

Where Rules Live

Note Codification does not mean every rule must live inside core ERP. In practice, the authoritative rule may land anywhere in the governed stack including SAP pricing, master data, workflow logic, or Corevist configuration. What matters is that it lands somewhere explicit, not in a person's judgment. The strategic objective is governed execution, not dogmatic placement.

Corevist and SAP Company Memory

At SAP Sapphire 2026, SAP named this problem directly.4 Introducing Company Memory as a new layer inside the Autonomous Suite, SAP described the challenge as tribal knowledge: the operational logic that lives in long email approval chains, exception handling patterns, and process workarounds that no agent can see or act on. SAP's answer is to extract that knowledge into structured process atoms that agents can reason against. Corevist is the mechanism that produces that raw material. Every time a customer request exposes a gap like a pricing rule that lives in a rep's inbox, a ship-to workaround that exists only in someone's memory, or a split-shipment preference never codified in SAP, Corevist forces the decision that converts tribal knowledge into a governed rule. That is exactly the input SAP's Company Memory layer is designed to work with. The two are not competing approaches, they are sequential ones.

Maturity Model and Sequencing

A practical maturity model has four stages. The progression matches SAP's own separation between workflow automation, agentic execution, and governance.
Stage What It Looks Like Corevist's Role AI's Role
1. Manual Orders via phone, email, and spreadsheets. Service reps bridge every gap. Not yet deployed. Hidden workflows accumulate. Limited to summarizing records. Must escalate constantly.
2. Structured Customers self-serve directly against live SAP data including pricing, availability, order status, invoices, and reorder. Forces gaps into visibility. Drives rule codification in SAP and governed layers. Can validate requests against defined rules. Explainability improves.
3. AI-Assisted AI validates requests, recommends next steps, prepares approvals, explains exceptions. Provides the structured, governed substrate AI requires to act reliably. Routes approvals, orchestrates multi-step logic, handles supervised execution.
4. Autonomous Agents handle low-risk end-to-end workflows under enterprise controls. Escalate only where policy requires. Clean-core and BTP-certified layer ensures self-service and automation stay aligned. Executes low-risk transactions autonomously. Humans handle exception and policy.

Sequencing Recommendation

The practical implementation sequence:
  1. First, digitize the highest-volume customer interactions against live SAP data: order status, invoices, reorder, pricing, shipments, and basic order entry.
  2. Second, use each failure to define the authoritative rule and place it in the correct governed layer.
  3. Third, instrument exceptions and monitor which scenarios recur.
  4. Fourth, once a critical mass of transactions is structured, SAP's automation and agentic tooling has a governed surface to work on including routing approvals, orchestrating multi-step logic, and extending into supervised AI execution.
Corevist's BTP certification is relevant to this sequence for one practical reason: it ensures the self-service layer doesn't become a dead end as the underlying SAP architecture evolves.

The Pattern Holds Across Industries

The dependency on structured data as a precondition for automation is not unique to manufacturing or SAP. GS15, whose standards are used by more than two million companies, describes its work as creating a common digital language for trusted supply-chain communication. The first barcode scan in 1974 produced step-change improvements in checkout efficiency, visibility, traceability, and confidence in underlying data. The lesson is not that barcodes are AI. It is that automation only scaled after identifiers and data structures became standardized enough for machines to act on reliably. Amazon's Just Walk Out technology illustrates the same reality from a different angle.6 Amazon deployed computer vision, sensor fusion, and AI into live retail stores and discovered that operational fit mattered more than technical sophistication. Reuters reported customer confusion, missed items, and delayed receipts. Behind the scenes, human reviewers were doing work the AI was supposed to handle. Amazon pulled Just Walk Out from its U.S. Fresh stores entirely, replacing it with Dash Carts, a simpler solution that gave customers what they actually needed: real-time visibility into what they were spending. The technology was not the problem. The operational layer underneath it was.

Conclusion

The implication is simple: autonomous execution cannot be layered on top of informal operations. That is Corevist's strategic role. It takes the customer-facing workflows that manufacturers often manage through service rep judgment, email approvals, pricing exceptions, manual workarounds, and unwritten customer preferences, and puts them against live SAP logic where they have to become visible. AI may be able to read SAP order history, but it cannot reliably act on business logic that has never been made explicit. When customers self-serve through Corevist, the hidden gaps in the operating model can no longer stay hidden. A missing ship-to rule, an informal pricing override, an unclear approval path, or a judgment-based exception becomes visible as an operating issue the business has to resolve. Once resolved, those decisions become governed rules. And governed rules are what make automation trustworthy. They give AI something concrete to validate against, explain, route, and eventually execute.
"But technology alone, and plugging AI agents into your existing system landscape will drive zero value. Moving to the Autonomous Enterprise requires serious change management." Christian Klein, CEO, SAP | SAP Sapphire 2026
Klein's challenge is not rhetorical. SAP's Autonomous Enterprise requires structured data, proven workflows, and governance. Serious change management is the prerequisite, and it has to happen at the operational level, where customer-facing workflows either work or they don't. Corevist is the mechanism that makes it happen: at the point of customer demand, against live SAP data, continuously. That is what turns the Autonomous Enterprise from a vision into an operating reality.

About Corevist

Corevist delivers B2B self-service portals built for SAP manufacturers and distributors. Its platform supports direct integration with SAP ECC and SAP S/4HANA, with an SAP BTP-certified option for companies aligning with SAP's clean core roadmap. Corevist gives customers real-time access to pricing, availability, order status, invoices, and ordering directly from SAP, without middleware, batch syncs, or data replication.7 It is designed for manufacturers with B2B ordering, customer service, and account management needs. Learn more here: corevist.com

References

  1. Christian Klein, CEO SAP — Sapphire Orlando Keynote Transcript, May 2026
  2. SAP Autonomous Enterprise Vision — SAP Business Suite
  3. Corevist — Emmerson Packaging Customer Story — Read the customer story
  4. SAP Sapphire 2026 Keynote — Business AI Platform and the Autonomous Enterprise — Read the SAP article
  5. GS1 — Global Supply Chain Standards — Visit GS1
  6. Reuters — Amazon Pulls Just Walk Out from U.S. Fresh Grocery Stores — Read the Reuters article
  7. Corevist — SAP Customer Portal Solution — View the solution page