MaKo is not just another process — it is the nervous system of the German energy market
In the German energy market, market communication (Marktkommunikation, MaKo) is not a secondary administrative flow: it is the nervous system that keeps suppliers, network operators, metering operators and customers connected. Every supplier switch, every new installation, every master data correction and every consumption reading passes through MaKo processes defined by the Bundesnetzagentur under standards such as GPKE, GeLi Gas, WiM, MaBiS and MPES.
In 2024, according to Bundesnetzagentur, there were 7.1 million electricity supplier switches and 3.3 million contract changes with the existing supplier. Each of those events generates dozens of MaKo messages between multiple actors. A failure or delay anywhere in the chain translates into billing errors, customer disputes and regulatory exposure.
“MaKo does not tolerate improvisation. It is a regulated process where traceability and deadline compliance matter more than speed.”
Why MaKo is a critical and often underestimated area
Many utilities treat MaKo as an invisible back-office process while it works. The problem shows up when it stops working well: massive message rejections, blocked supplier-switch processes, discrepancies between master data and contracts, and regulatory deadline breaches. At that point MaKo stops being invisible and becomes the most urgent issue on the CIO’s desk.
Three factors make this area especially demanding: regulatory rigidity (EDIFACT formats, deadlines and business rules evolve every year), integration complexity (a typical MaKo message connects SAP IS-U, CRM, portal, EDM, metering systems and accounting) and volume (a mid-sized utility can process millions of MaKo messages per year).
Where AI belongs — and where it does not
A quick contrast before going into detail. AI does not replace MaKo systems, and there are parts of the process that must remain fully deterministic.
✓ Where AI adds real value
Classification and prioritisation of message rejections, early anomaly detection on message flows, and assisted customer communication about MaKo cases. AI operates on extracted data and returns structured signals — categories, priorities, drafts.
✗ Where AI does NOT belong
Generating binding MaKo messages, deciding contract states, activations or terminations, reconciling master data across systems. These operations demand deterministic EDIFACT rules, human governance and full auditability.
Three concrete AI use cases around MaKo
Three use cases concentrate most of the practical value of AI around market communication in German utilities.
01 · Rejection classification
EDIFACT rejection codes are interpreted automatically by root cause (master data, deadline, format, contract) and prioritised by regulatory and financial risk.
02 · Anomaly detection
Unusual patterns in message volumes, abnormal queues or growing counterparty delays are flagged before they escalate into regulatory incidents.
03 · Assisted customer replies
Personalised replies grounded in real MaKo case status, reviewed by an agent, reduce call-centre volume without touching process logic.
How to integrate AI with MaKo without disrupting operations
The pattern that works is the same we apply in billing: AI lives around the MaKo system, not inside it. Market systems (SAP IS-U, Powercloud, specialised MaKo platforms) keep their deterministic logic and full traceability. AI operates on extracted data, produces structured signals (categories, priorities, drafts) and returns those signals to the human operator or to the system — without executing autonomous actions on regulatory messages.
This approach allows a utility to accelerate daily operations without compromising its compliance with Bundesnetzagentur or adding audit risk.
Where Principal33 fits
At Principal33 we combine two capabilities that are rarely found together: real MaKo experience within the SAP IS-U, FI-CA, Powercloud and specialised market-communication stack, and an AI-agnostic Data & AI practice that evaluates per use case where AI adds real value and where it does not. Teams are senior, German-speaking and nearshore DACH, which reduces regulatory misunderstandings and accelerates coordination with IT, regulatory and operations inside the utility. Principal33.
With this introduction of MaKo as a practice area, Principal33 completes an end-to-end offering for German utilities covering billing, market communication, forecasting, customer portals and Data & AI architecture — always under the regulatory framework of Bundesnetzagentur, BSI and KRITIS.
The shift in perspective
MaKo is an honesty test for any consultancy talking about AI in the energy sector. There is no margin for experiments here: processes are regulated, deadlines are inflexible and errors are immediately visible to Bundesnetzagentur. AI applied with judgement frees capacity and improves response time; AI applied without judgement adds regulatory risk to a process that cannot absorb it. Knowing the difference is exactly what separates real AI capability from a marketing label.
