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    Home » Sections » Enterprise software » BBD white paper: why shift-left testing is the future of software quality

    BBD white paper: why shift-left testing is the future of software quality

    Promoted | BBD’s new white paper urges a shift-left approach, integrating AI to modernise software testing.
    By BBD23 September 2025
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    BBD reveals strategic imperative of modern software testing in AI eraBBD has launched its new white paper, “Shift Left, Think Ahead: The Strategic Imperative of Modern Testing”. The report reveals a fundamental shift in the software development landscape, arguing that traditional testing practices are no longer sufficient to meet the demands of modern, fast-paced development cycles.

    The white paper asserts that as software becomes the new infrastructure for global commerce and human connection, the cost of poor quality extends far beyond financial losses, impacting brand reputation, customer trust and team morale. Citing industry analyses, the paper notes that the global economic impact of poor software quality runs into trillions of dollars annually. To counter this, BBD advocates for a “shift-left” approach, which integrates testing early and continuously throughout the software development lifecycle.

    Download the white paper now

    The report introduces BBD’s proprietary packaged testing services – a holistic and outcome-driven approach that combines functional and non-functional testing into a single, unified framework. This model addresses multiple quality dimensions, including accessibility, performance and security, directly within the development pipeline. It details how this approach has led to tangible results, citing a case study with a financial sector client that saw a 30% reduction in testing efforts by combining functional and accessibility checks.

    The report explores how AI is moving testing from a reactive function to a predictive one

    A cornerstone of BBD’s approach, and a key focus of the white paper, is the application of artificial intelligence in quality assurance (QA). The report explores how AI is moving testing from a reactive function to a predictive one. BBD’s in-house developed, AI-powered test automation agent is highlighted as a gamechanger, intelligently creating, maintaining and optimising automated tests across diverse technologies. The report details how this agent leverages machine learning for self-healing automation and seamless cross-framework migration, resulting in up to a 40% reduction in test maintenance overhead. A separate case study with a telecommunications provider demonstrates how BBD’s AI agent enabled the team to achieve 95% automation coverage of core business workflows in just two weeks, accelerating a major customer relationship management migration.

    The white paper also provides a forward-looking view on the future of quality engineering, predicting the rise of autonomous testing pipelines, predictive analytics and the evolution of the tester’s role into that of a quality strategist.

    Rapid digital transformation

    “For too long, software testing has been seen as a final checkpoint, but that philosophy is failing businesses in the age of rapid digital transformation,” explains Akshay Deole, executive for testing services at BBD.

    “Our white paper is a guide for organisations to not only understand the risks of this outdated model but to embrace an intelligent, integrated and indispensable approach to quality. By shifting left and leveraging the power of AI, companies can stop chasing bugs and start building faster, more resilient and more trustworthy software.”

    The “Shift Left, Think Ahead” white paper is an essential read for technology leaders, development teams and QA professionals seeking to modernise their approach to software quality and leverage advanced technologies to secure their digital future.

    Download the white paper now and learn more about BBD’s packaged testing solutions.

    • Read more articles by BBD on TechCentral
    • This promoted content was paid for by the party concerned

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