As a participant in KonnectHouse’s Agentic AI in Procurement event at Tobacco Dock, London on September 4, 2025, I found myself immersed in a vibrant ecosystem of forward-thinking procurement professionals and AI innovators. The event delivered a powerful mix of interactive demos, strategic dialogue, and a clear emphasis on real-world impact and a little bit of fear of the unknown..

But one key theme that resonated with me throughout the day: startups shouldn’t get bogged down by the labels—whether “Generative AI” or “Agentic AI.” In truth, these technologies are evolving, often overlapping—and what truly matters is what they accomplish.

1. Labels will Evolve because Technology Evolves

During the demo hub sessions, presenters demonstrated tools that straddled multiple AI paradigms. For instance, one provider offering AI-powered systems was generating RFX content (a hallmark of generative tech), while also autonomously managing supplier negotiations (an agentic capability)—plus everything in between.

What’s clear is that AI solutions are converging. Packaging them under rigid labels can hamper their perception, undervalue hybrid functionalities, and—and most critically—undermine clarity regarding their actual value.

Startups at the event showed why rigid tech labels fail to capture the ingenuity and breadth of modern procurement AI. Each provider demonstrated the challenge of simple categorization—and illustrated the risks of letting outdated labels define a startup’s positioning. For example – 

• askLio blends generative and autonomous capabilities: it handles free-text requests and guided buying while also deploying intelligent agents for tasks like order confirmation, risk monitoring, and supplier negotiations in real time.

• Delvo brings adaptive sourcing and compliance bots to the table, scanning market shifts proactively and streamlining RFP cycles. Its platform fuses generative document creation with agent-driven supplier management.

• Omnea offers a category management suite that adapts to evolving supplier and transaction data, enabling smarter decisions over time. Generative tools power dynamic reporting and analytics, translating complex insights into accessible, actionable outputs.

• Sligo connects spend analysis, contract reviews, and supplier performance scoring in a single workflow—pairing generative documentation insights with AI-augmented sourcing routines that evolve with usage, without locking into rigid categories.

2. Stakeholders Want Results, Not Definitions

Procurement leaders attending the event also weren’t asking whether a system was necessarily “agentic” or “generative”—they wanted to know: Can it draft an RFP? Flag risk proactively? Save us time and money while ensuring compliance? The key is to demonstrate outcomes—autonomous sourcing, decision orchestration, proactive risk identification—that define Agentic AI’s real value.

3. Hybrid Approaches Are Practical—and Powerful

Some innovative startups are even opting for hybrid solutions, blending generative AI’s language fluency with agentic AI’s autonomy and decision-making. This pragmatic approach allows for more robust feature sets—initial content generation, intelligent evaluation, strategic planning, and downstream execution—all embedded in one workflow.

These hybrids let startups offer “the best of both worlds,” enabling procurement functions to quickly adopt tools that generate, reason, and act—without forcing customers to choose a specific AI label.

4. Messaging Over Monikers: Clear Communication Wins

One challenge discussed at the event was AI buzzwords fatigue. If every solution is tagged “AI,” the term loses meaning. I observed how clarity in messaging—focusing on the problem solved or the benefit delivered—had more impact than catchy labels.

As a startup, say: “Our solution auto-generates and evaluates supplier responses, highlights non-compliance, and manages approvals in real-time.” That’s far more compelling than, “We’re a generative/agentic AI platform.”

5. The Event’s Takeaways: Focus, Practicality, and Impact

Here are the key takeaways I carried from the conference:

• Outcome > Terminology: Design and present solutions based on what they achieve, not on AI categorizations that get caught in marketing babble.

• Be transparent and direct: Clarify what’s automated, what’s autonomous, and what’s still overseen by the human team.

• Start small, deliver value: Choose use cases where impact is immediate—like risk flagging or contract drafting—and scale from there.

• Hybrid solutioning is your ally: Mix and match AI techniques to build richer, more adaptable solutions for procurement needs.
  

Conclusion: The Future Is Defined by Utility

Events like KonnectHouse’s Agentic AI in Procurement are invaluable for one key reason—they ground lofty AI concepts in tangible procurement realities. But they also remind us that while labels like “Generative” or “Agentic” may hold technical value, they take a backseat to impact.

To startups navigating this evolving space: don’t get bogged down by definitions. Concentrate on business outcomes that focus on clarity, efficiency, savings, risk mitigation, and strategic insight. Let your messaging reflect what you deliver, not what buzzword you align with. That’s how you turn attention into adoption.

This is where Liberis Consulting can help.