Cisco Uses AI to Refactor Legacy Code

The company is launching an AI-driven initiative to modernize its internal software architecture over two years.

Updated on Oct. 30, 2026 in Artificial Intelligence

Isometric editorial illustration of a geometric server cluster, representing large-scale digital architecture modernization. — Cisco has launched a two-year AI-driven initiative to modernize its internal legacy software architecture, aiming to replace 98% of older systems. AI Illustration. Upload story photo >

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Cisco is deploying artificial intelligence to refactor its legacy code base in a major organizational update. The tech giant aims to replace 98% of its older systems within the next 24 months.

Why it matters

Updating aging infrastructure is a critical step for large technology firms to remain competitive and improve system efficiency. By leveraging AI to manage this massive technical debt, the company hopes to accelerate its development cycles.

The initiative targets the replacement of 98% of existing legacy code over a 24-month period. Teams will first utilize a four-week proof period to evaluate the efficacy of the AI-driven approach.

The players

Cisco

A multinational technology conglomerate that designs, manufactures, and sells networking hardware and software solutions.

EzDubs

A technology company recently acquired by Cisco to integrate new digital capabilities into its existing portfolio.

Padmanabhan Krishnamurthy

The 27-year-old co-founder of EzDubs who is now integrated into the broader Cisco technical ecosystem.

The details

Cisco is using a two-person team structure to manage the AI-assisted code transformation. This project follows the company's recent acquisition of EzDubs on Nov. 25, 2025, which brought new technical expertise into the organization.

Nov. 25, 2025: Cisco completed its acquisition of EzDubs.
Next 24 months: The company plans to address 98% of its legacy code.

The Tech Race

Cisco's project follows the industry trend of adopting AI-assisted software development to automate the time-consuming process of refactoring legacy code. This marks a strategic shift from manual maintenance toward automated scalability, positioning the company against competitors streamlining their own technical debt.

This transition to AI-refactored systems may lead to faster feature rollouts and improved stability for customers using Cisco services. Developers and enterprise clients should expect potential workflow improvements as the internal architecture becomes more modern and responsive.

The takeaway

Large-scale code modernization is becoming increasingly reliant on automated tools to manage complexity and reduce the time spent on technical debt. Organizations looking to refresh their own systems should prioritize a proof-of-concept phase to validate how AI integration performs against existing workflows.