Colt tests agentic AI with Microsoft for enterprise pricing

Colt tests agentic AI with Microsoft for enterprise pricing is profiled by BTW Media because published evidence links it to internet infrastructure, governance, operational dependencies, or market visibility.

• Colt Technology Services and Microsoft have developed an agentic AI engine to simplify enterprise network pricing.
• The system reportedly cuts quotation time from days to around 10 minutes, though human oversight remains.

What Happened

Colt Technology Services has worked with Microsoft to build a proof-of-concept agentic AI engine designed to automate parts of its enterprise sales process. The tool focuses on one of the more complex steps in telecom procurement: generating accurate pricing quotes for large infrastructure deals.

Pricing global connectivity services can be complicated. Enterprises often operate across multiple countries, with different service levels, network routes, and contract terms. According to Colt, this complexity can slow down negotiations and delay service deployment.

The new AI system aims to streamline this step. Colt and Microsoft trained the agent in just three days to generate pricing proposals across most of the company’s markets. Early results suggest the engine can deliver quotes with around 99% accuracy, reducing turnaround times from several days to roughly 10 minutes.

The quotes generated by the AI are still reviewed by Colt staff before being sent to customers. The companies describe the tool as a proof of concept rather than a fully deployed product. Colt says it plans to expand agentic AI across the customer journey, potentially covering areas such as onboarding and service management.

Agentic AI refers to systems capable of performing tasks autonomously, making decisions, and executing workflows without constant human direction. Such technologies are increasingly explored in enterprise operations, although many deployments remain experimental.

Also Read: https://btw.media/en/allit-infrastructure/o2-telefonica-germany-adopts-ai-for-network-operations/

Why It’s Important

Telecom providers face growing pressure to simplify enterprise procurement. Large connectivity deals often involve multiple stakeholders, long pricing cycles, and complex service configurations. Automation tools could reduce administrative overhead and speed up sales.

If agentic AI systems work reliably, they might also improve transparency for enterprise customers by generating consistent pricing logic across markets. Faster quotations could help telecom providers compete more effectively in global connectivity services.

However, the benefits are not guaranteed. AI systems still depend heavily on training data and oversight. Pricing mistakes in telecom infrastructure contracts could be costly, which explains why human teams remain in the approval loop.

There are also broader concerns about agentic AI in enterprise environments. Critics note that many AI agent systems are still experimental and can produce unpredictable results. Security, governance, and accountability are additional challenges when automated tools handle sensitive commercial decisions.

For Colt and Microsoft, the project reflects a wider trend across the telecom industry: using AI to automate operational processes rather than simply analyzing network performance. Whether agentic AI becomes a mainstream enterprise tool will depend on how reliably it can manage complex workflows without introducing new risks.

Also Read: https://btw.media/en/allit-infrastructure/private-networks-go-mainstream-as-deployments-hit-6500/