Whitepaper · Free download

Only 18% of network-automation projects are rated a complete success.

Most vendors won't tell you that. The ROI Case for AI-Driven Network Operations breaks down what separates the 18% from everyone else, and what agentic AI returns when it's engineered for a live fiber network.

Download the whitepaper

Get your free copy of The ROI Case for AI-Driven Network Operations.
  • Benchmark ROI data
  • A $590K/yr case study
  • A vendor evaluation framework
Fiber operators running on AEX
  • Arrive Internet
  • Evotel
  • Foam Internet
  • Foothills Broadband
  • LinkLayer
  • Magnolia Tree Fibre
  • MFibre
  • OpenFibre
  • Prime One
  • Redrock Telecommunications
  • Residence Fiber
  • Ripple Fiber
  • Unifybr
  • ZoomFibre
What most vendors won't tell you

The demo looks good. A live network is a different test.

Generic AI breaks on a live network in four specific ways, and that is why most automation underdelivers. This whitepaper shows what separates the 18% of projects that succeed from everyone else, and what it's worth when you get it right.

Judge an AI vendor on whether its claims hold up, not on whether the demo looks good.

Where the return shows up
  1. 1
    Faster resolutionBenchmark data on resolution times
  2. 2
    Lower capex and opexBenchmark cost data
  3. 3
    Provisioning savingsA $590K/yr case study
Inside the whitepaper

Four things you'll take away

What agentic AI returns when it's engineered for a live fiber network, and how to tell whether a vendor can deliver it.

  1. 1

    The real economics

    Benchmark data on faster resolution, lower capex and opex, and a $590K/yr provisioning case study.

  2. 2

    Where generic AI breaks

    The four specific ways it fails on a live network, and why that is the reason most automation underdelivers.

  3. 3

    A vendor evaluation framework

    How to test whether an AI vendor's claims actually hold up, not just whether the demo looks good.

  4. 4

    Responsible autonomy

    What it looks like in production today, and how operators prove it works before trusting it with more.