On May 19 and 20, 2026, SoftconCIS presented WebCIS 4.0 at the BME eSolution Days at Areal Böhler in Düsseldorf. The event once again brought together numerous solution providers, procurement professionals and experts to discuss current developments in digital procurement.

One topic was particularly present throughout the event: artificial intelligence in procurement. At many booths, in presentations and in conversations, it became clear that AI is becoming increasingly important for procurement organizations. At the same time, it also became apparent that while many companies are actively exploring the topic, practical implementation is still at an early stage.

A particular highlight was our expert presentation by Bastian Wagner on the topic “AI in Procurement: Doing Instead of Talking!”. The high number of participants confirmed that procurement departments are currently looking above all for practical answers:

• Where can AI provide concrete support in procurement?
• What data foundation is required?
• How can price developments, benchmarks and KPIs be evaluated more effectively?
• What role does procurement controlling play in data-based decision-making?
• How can real value be created from existing ERP data?

In the discussions at our booth, it became clear that many procurement departments already have access to large amounts of relevant data – for example from SAP and non-SAP systems, purchase orders, invoices, supplier master data or category structures. However, the challenge often lies in making this data quickly, structurally and decision-oriented usable.

This is exactly where WebCIS 4.0 comes in. As a specialized platform for strategic procurement controlling, WebCIS supports companies in transparently analyzing procurement data, preparing key performance indicators and making potential savings visible.

The event also showed how dynamic the market around AI in procurement has become. Many providers are now positioning themselves with AI functionalities, AI agents or automated workflows. For procurement decision-makers, this creates a new challenge: it is no longer just a question of whether AI is relevant in procurement, but which applications actually deliver measurable value.

Because AI alone does not solve procurement problems. What matters is whether it works on a clean data foundation, can be embedded into existing system landscapes and answers concrete procurement-related questions. For example: Where do price deviations occur? Which suppliers are developing critically? Which categories are affected by market changes? Where are potential savings hidden? And which developments will become relevant to future business results?

From our perspective, this connection will be decisive: AI must not be viewed separately from procurement, but as an intelligent extension of reliable procurement controlling. WebCIS 4.0 provides the foundation for this by bringing together procurement data from SAP and non-SAP systems, analyzing it and translating it into decision-relevant information. AI can build on this foundation, identify patterns faster, detect anomalies and support procurement teams in making more fact-based decisions.

The BME eSolution Days therefore confirmed an important impression: the future of procurement will not be determined by new technologies alone, but by the ability to integrate technology meaningfully into existing processes, data structures and decision-making paths. Companies that want to use AI successfully in procurement should therefore first strengthen their data foundation, KPI logic and transparency in procurement controlling.

We would like to thank all visitors for the insightful conversations, the open exchange and the great interest in WebCIS 4.0.

Der Beitrag AI in Procurement in Focus – SoftconCIS at the BME eSolution Days 2026 in Düsseldorf erschien zuerst auf SOFTCON CIS.

Der Beitrag ERP Integration in Purchasing Controlling: Optimally Connecting SAP and Other Systems erschien zuerst auf SOFTCON CIS.

Between Euphoria and Skepticism

Hardly any other topic polarizes strategic procurement as much as artificial intelligence. On one side are the enthusiasts who see AI as the solution to every challenge, from spend analysis to supplier development. On the other side are the skeptics who distrust AI results and rely on the tried-and-true combination of experience, market knowledge, and their own judgment.

Both camps are right, and both are wrong when they ignore the other side.

Because AI in strategic procurement is neither a panacea nor just hype. It is a powerful tool, but only in the right hands.

What AI can really do in procurement

AI’s strengths lie where humans reach their natural limits: in processing large amounts of data, recognizing patterns, and the speed of analysis.

Specifically, this means the following in strategic procurement:

Price index comparisons at the click of a button. Instead of manual research and time-consuming Excel models, AI can automatically compare market indices such as those from Eurostat or the Federal Statistical Office with your own product groups and immediately highlight discrepancies. What used to take days can now be done in minutes.

Pattern recognition in supplier and pricing structures. AI detects inconsistencies in price trends, illogical tiered pricing structures, or conspicuous volume fluctuations, across all material numbers and suppliers simultaneously. No human eye could sift through this volume of data in a reasonable amount of time.

Predictive analytics for better negotiations. Based on historical price and market data, AI can model price trends and provide the buyer with a fact-based framework for supplier negotiations.

Homogeneity indices for clean product groups. One of the biggest weaknesses of many procurement organizations is an inadequate product group classification system. AI-based homogeneity indices objectively show how consistent the classifications are and make suggestions for optimization.

Where AI Reaches Its Limits

As impressive as these possibilities are, AI cannot replace the strategic thinking of an experienced buyer. And for good reason.

AI works with patterns from the past. It cannot assess whether a supplier is a strategically indispensable partner despite poor metrics. It does not understand political market dynamics, personal negotiation relationships, or company-specific priorities.

AI provides suggestions, not decisions. It highlights potential that would otherwise remain invisible. But whether and how this potential is realized remains the task of humans.

This is not a weakness of AI. It is the natural division of labor between humans and machines, and that is precisely where the real added value lies.

The crucial prerequisite: the data foundation

AI is only as good as the data it works with. This is where many procurement organizations fall short not because of the technology, but because of data quality.

Missing master data, inconsistent product category systems, and data from various sources that isn’t harmonized, all of this makes AI analyses unreliable or simply impossible. Anyone who wants to use AI effectively first needs a clean, complete, and consistent data foundation.

A powerful procurement information system like WebCIS 4.0 creates exactly this prerequisite: consolidated data from various sources, uniform product group classifications, and interactive dashboards as a solid foundation for integrable AI models that deliver real added value.

Conclusion: AI as an Enhancer of Human Expertise

AI in strategic procurement is not just hype, but it’s also not a surefire success. Its true value unfolds where it does what it does best: analyzing data, recognizing patterns, and identifying potential faster and more comprehensively than any human could.

Strategic assessment, decision-making, and negotiation remain the responsibility of the experienced buyer. Not because AI is incapable of doing so, but because procurement remains, at its core, a human endeavor.

The question, then, is not whether AI creates value in strategic procurement. The question is whether your organization has what it takes to leverage that value.

Der Beitrag AI in Strategic Procurement – Hype or Real Value erschien zuerst auf SOFTCON CIS.

Automation and AI open up tremendous opportunities to make processes more efficient and cost-effective. The real question is how we use them. Without human judgment, market knowledge, and creativity, procurement will only get halfway there.

Pattern-based analyses – from price developments to benchmarks, exchange rates, or commodity index tracking – have been standard for years. AI can now deliver these faster and at scale. But whether it will independently create complex, innovative analyses in the future is still an open question.

Intelligence is human

Procurement controlling is more than just a savings machine. It is a strategic steering instrument that shapes decisions. To do that, procurement needs powerful platforms that do not just collect data but also connect and interpret it intelligently. AI plays a key role here, but it is not the only one.

Data is today’s most valuable raw material. But it only creates value when it is analyzed purposefully and translated into clear actions. Systems like WebCIS support this process with modern self-service BI, automated forecasting, and flexible analytics. Still, one fact remains: at the end of the day, people make the decisions, not machines.

Procurement as a driver

A successful procurement function does not just look back; it looks ahead. Data-driven planning, forecasting, and structured bill-of-materials controlling turn procurement into a proactive driver within the organization, directly influencing sales, production, and overall strategy.

WebCIS enables this by speeding up analyses, creating transparency, and opening doors to new questions. In this way, procurement guides AI, rather than being guided by it.

More than just savings

Cost optimization remains a core objective. But modern procurement organizations demand more: flexibility, transparency, and the ability to shape analytics on their own terms. WebCIS delivers this with a broad set of KPIs, adaptable reporting, and more than 20 years of industry expertise.

A key differentiator is the combination of algorithms with customer feedback. Systems do not just learn from data, they also learn from real-world challenges faced by their users. This is how practical, innovative insights are generated, such as variance analyses, global price benchmarks, or best-in-class comparisons.

People and machines together

AI is a powerful tool for detecting patterns, uncovering anomalies, and accelerating processes. But for strategic decisions, creative thinking, and sustainable solutions, human expertise remains irreplaceable.

Success lies in the combination: AI provides the data foundation, people create the value. Today and in the future.

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