Stop procuring AI. Start using it.

Here’s a question that should keep every telco executive awake at night: 

How do you buy something that doesn’t exist yet? 

While you’re spending 18 months evaluating artificial intelligence (AI) vendors through requests for proposals (RFPs), Totogi customers are already running AI in production—optimizing pricing, detecting revenue leakage, and processing real data with measurable results.

I recently posted on LinkedIn that it’s almost useless for Totogi to respond to telecom RFPs anymore. Not because we don’t want the business, but because whatever AI capabilities we describe today will be fundamentally different tomorrow. Artificial intelligence isn’t just moving fast—it’s moving at a pace that makes traditional procurement a waste of time AND money.

The post hit a nerve (especially with my procurement buddies). Let me explain.

The AI procurement paradox

Traditional telecom procurement was built on a simple premise: you’re planning to buy something expensive that won’t change much over its operational lifetime. A cell tower is a cell tower. Packaged enterprise software is packaged enterprise software.

AI obliterates this logic.

Imagine if you had an RFP out that was due on August 1st. Here’s what happened THE NEXT WEEK after vendors submitted their responses:

• OpenAI released gpt-oss open-weight models on August 5th, nearly matching their previous top models
• Anthropic announced Claude Opus 4.1 on August 5th with industry-leading coding performance
• OpenAI launched GPT-5 on August 7th with unified reasoning and fast response capabilities
• Microsoft integrated GPT-5 into Azure AI Foundry within days of OpenAI’s announcement

Every vendor that responded to that RFP described capabilities that were immediately outdated. Not incrementally outdated—fundamentally obsolete due to advances that happened while the RFP was in flight.

This isn’t a software update cycle problem. This is an AI evolution problem. When models evolve overnight, when new neural architectures emerge monthly, when cloud providers launch game-changing AI services weekly, your 12-month procurement cycle isn’t just slow—it leads you to make wrong vendor selections for your organization.

This creates what I call the “AI procurement paradox”: the longer your RFP cycle, the more likely you are to make the wrong selection. Though your procurement team thinks six-month evaluation cycles reduce risk; instead, they’re creating hidden risk by not picking the best vendor for the job. Your legal team thinks detailed technical specifications in RFPs provide protection. In practice, they’re locking you into yesterday’s architecture while modern telcos are leveraging the latest technical breakthroughs.

The counterintuitive reality is that rapid AI vendor selection, testing, and deployment (what feels risky to traditional procurement) is actually the lowest-risk approach in a world of AI velocity. When you can test AI capabilities with real data in real-world scenarios within weeks, you’re reducing risk through actual validation, not simply reading a document about what the software can theoretically do.

How modern telcos are breaking free

Modern telcos have figured out that AI evaluation is done by USING the AI software yourself.

Instead of six-month evaluation cycles, modern telcos run six-week pilots. Instead of detailed requirements documents, they define success metrics and let AI vendors show what’s possible.

Lester Thomas, speaking on the Telco in 20 podcast, explained how his team completely ditched RFPs for software procurement. Instead, they just try software out. If it works for them, they use it. If it doesn’t, they know quickly (and with low investment) and can move on to the next vendor. Smart executives like Lester call companies like Totogi directly—no RFP required.

These modern operators understand something crucial: you learn more about an AI system in two weeks of testing with real transaction data than you do from six months of vendor slideware.

Skip the RFP. Call Totogi.

While other vendors are yapping about theoretical AI capabilities, Totogi has working AI deployed in production today. Our customers see results right away instead of waiting 18 months.

We don’t just talk about AI features; our AI is actively optimizing pricing in real-time based on customer behavior, network conditions, and competitive dynamics. We don’t theorize about revenue leakage detection; our machine-learning algorithms are already catching patterns that humans miss in live billing systems.

Want proof? Bring it! We’ll show you what our AI can do for you today—not in six months, not after an RFP process, but THIS WEEK.

We can set up live AI environments in 48 hours because our entire platform runs cloud-native on Amazon Web Services (AWS). No hardware installations, no months-long deployments, no theoretical demonstrations. Just real AI processing on your actual data with measurable results NOW.

Operators who call us directly typically go from initial contact to production deployment in under 60 days. Compare that to 18-month traditional RFP cycles, and ask yourself: what are we waiting for?

AI speed as a competitive advantage

Modern telcos are already adopting this new approach, and it’s becoming the de facto standard of AI procurement. Not six vendors jumping through hoops while you whittle the field down to the one you’ve already chosen. Not year-long evaluation cycles. Not 40-page RFP responses that are obsolete before they’re submitted. Just: does this solve our problem better than what we have today?

In this environment, your procurement process isn’t a back-office function—it’s a strategic capability that directly determines your competitive position. Every month you spend evaluating vendors via document reviews is a month your competitors spend optimizing operations with AI in production.

The telcos that will dominate the next decade are the ones who can identify, test, and deploy AI capabilities faster than their competition. In the age of AI velocity, procurement speed IS strategic speed.

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