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AI-enabled software risk management remains aspirational


Firms are having big strategic conversations about AI – but in reality, few have applied these techniques in their QA practices. For the most advanced group of developers at FinTechs and eCommerce providers, AI-enabled QA and full DevOps are still a way off.

These lessons learned are based on insights gleaned from our recent Automation and AI for Mobile App forum in London, speaking to 120 people at 57 different organisatons.

When we asked firms how they are using Automation and AI, most largely are not. Up to 70% of firms have over half the journey to embed RPA into the quality dimension remaining. Fewer than 5% have deployed AI in QA.

DevOps people are focusing on integrating the coding capabilities of their development and testing resources. But many remain cautious. Though many firms aspire to become more agile, the business is yet to be fully integrated into DevOps practices in over 50% of cases.

For now, budget and effort priorities are to improve testing infrastructure. More than six in seven firms take a tactical approach to their value stream management in QA. Overwhelmingly, firms measure test outcomes and defects in development escaping to production.

To secure the funding required to embed AI-driven QA, quality leaders must evolve their approach to value stream management. AI-driven software risk management will enable firms to focus their effort on mission-critical workloads, thus avoiding the proverbial ‘airline crash.’

Registered QA Vector 500 subscribers can learn more about deepening their DevOps integration with the business and effective value stream management as part of an effective Quality Process Architecture.