The demand for high-quality and high-performing applications has never been greater. There are currently over seven million apps available across iOS and Android platforms, and in 2027, we expect to see mobile apps generate almost $674 million in revenue.
But success is not only about bringing mobile applications to market. Organizations must deliver unique, engaging, and easy-to-use mobile applications to grow their user base and boost revenue. While CTOs are acutely aware of this need, testing and development teams have continued to battle with time, accessibility, and productivity constraints that make achieving application quality a slow and arduous process.
In fact, earlier this year Tricentis announced the findings of the 2024 State of Mobile Application Quality Report, which revealed that 90% of senior IT professionals estimate poor mobile app quality costs their business up to $2.49M in lost revenue every year. Mobile app development is at a critical juncture, and technologies such as AI and test automation have a unique role to play in how the industry evolves.
Challenges that have led to poor mobile app quality include competing priorities and a lack of available technology, talent, time, and costs and are severely impacting the overall business success. AI offers a compelling solution by increasing QA productivity to save time and allow for a greater level of testing and coverage for each application release. Organizations dramatically reduce the financial costs and risks created by poor mobile application quality while improving user experience and growing revenue.
Streamlining Testing & Development Cycles
AI is proving to be a revolutionary asset for testing and development teams looking to enhance mobile experiences, and is emerging as a primary solution to these testing challenges. Generative AI offers the power to transform industries by simplifying how we interact with software. In the mobile application space, it helps teams develop applications and create tests faster, streamlining development cycles and helping QA and development teams test applications, processes, and data more efficiently and effectively.
AI-powered, intelligent assistants are now able to help with test creation, optimization, and insight generation. These intelligent assistants not only simplify the testing of complex applications, they also increase test quality and coverage. Put differently, AI not only makes it possible to test faster, it also enables the creation of better tests that provide better coverage and catch more bugs.
What’s more, AI can empower less-technical testers with limited coding experience to achieve more by automatically generating custom code to test complex applications. It can also explain existing test code, making it easier to document and reuse best practices. AI can also analyze this code to identify any problems and provide fixes, simplifying and speeding up debugging. Put simply, AI plays a significant role in upskilling testers and QA teams. AI-based chatbots also can make it easier to find answers to critical questions or locate documentation and additional resources. All of this means that less time is needed to create high-quality software, allowing time and space for greater innovation.
With senior IT professionals citing productivity bottlenecks and access to talent as key challenges that reduce mobile application quality, AI has the power to step in and lend a helping hand. Indeed, Forrester predicts a 15% increase in productivity for testers who use AI.
Adoption and Integration
Tricentis’ State of Mobile Application Quality Report also revealed that just under half (49%) of the senior IT professionals and application developers surveyed stated that AI is already a part of their mobile app testing strategy and only one fifth (21%) plan to implement AI tools within the next six months. This finding demonstrates a need for greater adoption of AI solutions among testers and an investment priority among business decision makers.
The secret to achieving mobile application success with AI is to create a strong synergy between AI-powered tools and the testers who know how to use them. AI is not, and should not be treated as, a replacement for testers, but a catalyst that amplifies human ingenuity, driving productivity and innovation.
This synergy is, of course, not the only concern with adopting AI in testing and mobile app development. AI tools are not infallible; they hallucinate, display overconfidence, and lack critical questioning. Therefore, taking a responsible approach when considering and using the responses from an AI-powered intelligent agent is a must. Also, AI solutions must ensure privacy, security, and compliance standards are met with any user-provided data. Finally, AI-integrated solutions need to provide useful value by easing the productivity burdens and amplifying best practices and knowledge across the software development team.
We expect organizations will increase their integration of AI-powered mobile application testing, tapping into its potential. IT leaders are showing high levels of interest, that if successfully converted into investment adoption, we expect will reduce the costs of poor mobile application quality, improve productivity, and get QA teams back to driving innovation that improves businesses bottom lines.
