Recent surveys show a significant shift towards generative AI in quality engineering, highlighting the need for comprehensive strategies amidst concerns about data breaches and system limitations.
Artificial Intelligence (AI) is progressively being integrated into software quality assurance, attempting to address longstanding issues that have burgeoned since the advent of computing technology. A recent study conducted by Capgemini and Sogeti, surveying 1,755 technology executives, reveals a significant shift towards employing generative AI (gen AI) in quality engineering strategies. The findings indicate that 68% of organisations are using gen AI to bolster their quality efforts, with 29% having fully implemented gen AI in their test automation processes and 42% actively exploring its potential benefits.
The report highlights the evolving capabilities of AI-driven tools, particularly with the integration of large language models and Copilot innovations, within the software development lifecycle. These developments have ushered in new efficiencies and innovations in quality engineering automation, according to the survey authors led by Jeff Spevacek of OpenText.
The perception of AI’s role in software quality assurance has notably shifted over the past year. Where there was once scepticism about the effectiveness of AI solutions in quality engineering, many organisations have now transitioned from experimental phases to real-scale applications of gen AI to support these activities. Despite this progressive adoption, concerns remain. Around 61% of respondents express apprehension regarding potential data breaches when leveraging generative AI solutions. Furthermore, a lack of comprehensive test automation strategies and dependence on outdated systems are seen as substantial obstacles by a notable portion of the executives surveyed.
The report also provides strategic advice for companies looking to advance their automation and AI integration within software quality endeavours. Recommendations include adopting an enterprise-wide perspective to outline objectives and outcomes for quality engineering automation, experimenting with various gen AI solutions before committing to a singular platform, and aligning automation goals with business performance indicators to achieve relevant outcomes like enhanced customer satisfaction and operational cost reductions.
In parallel, a PYMNTS Intelligence survey focusing on the significance of real-time data, conducted in collaboration with Fiserv, underscores the critical role of data readiness for platform businesses aiming at exploiting market potential and fostering growth. The survey findings indicate that 62% of platform businesses consider real-time data pivotal to their growth strategies. Companies utilising real-time data analytics report being 1.5 times more likely to achieve higher revenue growth compared to those which do not.
The advantage of real-time data lies in its ability to facilitate instantaneous decision-making, enabling companies to respond swiftly to market shifts and consumer demands. This capability not only aids in capturing market opportunities ahead of competitors but also enriches customer engagement by tailoring marketing strategies based on immediate insights.
Nevertheless, achieving data readiness poses challenges, with 45% of businesses encountering data silos impeding effective data utilisation, while 37% face issues surrounding data quality. The lack of interoperability among data systems can delay access to pertinent information, stagnating time-sensitive decisions crucial for growth.
To overcome these hurdles, businesses are prioritizing investments in advanced analytics tools to enhance data processing and accuracy, with 58% focusing on such initiatives. Moreover, cultivating a data-driven culture through employee training is identified by 53% of respondents as a significant contributor to improving overall data quality.
Both studies emphasise a technological evolution in their respective domains. The integration of AI into software quality assurance and the utilisation of real-time data for business growth signify crucial steps forward for organisations seeking to remain competitive and innovative in an increasingly data-driven landscape.
Source: Noah Wire Services
