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Private Equity funds agree AI will drive Quality Assurance; but how exactly?

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Software testing driven by AI is going to be “A massive leap forwards,” says Charlotte Lawrence, investor at Carlyle Europe Technology Partners, an arm of the giant Washington DC-based Carlyle Group. Carlyle, which manages a portfolio of more than $200 billion of investments, has made its bet in AI for testing with its acquisition of a majority stake in test automation specialist Eggplant (then called TestPlant) in January 2016. “We believed there was an opportunity for a new entrant with a modern offering in this [software testing] market,” said Lawrence. “Eggplant had a product range that was not just about automating functional test execution – it offered end-to-end testing which they extended into AI-driven automation of the entire testing process, from test creation to test outcomes.” Eggplant says that its Eggplant AI product can automatically generate test cases, as well as: “optimise test execution to find defects and maximise coverage of user journeys.” Where Lawrence disagrees in emphasis with some other PE investors is that she sees the potential for AI to automate most elements of software testing. “We are now in a world where businesses have to continuously release and monitor high quality software and therefore companies like Eggplant that can provide a continuous view of the customer experience will be much better placed to deliver positive business outcomes,” she told QA Financial. “Previously, the only shift driven by automation in the sector was a move from manual test execution to automated test execution. However, the entire creation of the tests was still done manually,” Lawrence said. “This doesn’t make sense anymore given the complexity of the systems we’re working with and we’ve seen Eggplant be able to provide a massive leap forward in test coverage through AI-driven test creation.” Through 2017 and the first half of 2018, software testing in firms in the QA Vector® 500 database received around $1.16bn in venture capital funding. The majority of these investments came from private equity firms. Other deals have included CRV (Charles River Ventures) and Amplify Partners each buying into machine learning-based test automation provider Mabl with $10 million in January, as well as private equity investors Accel Partners and Susquehanna Growth Equity each investing $100 million in continuous delivery specialist XebiaLabs in February. This year, Carlyle Group-owned Eggplant acquired NCC Group’s test management division in March, while New York -based Insight Venture Partners-owned Tricentis acquired the Q-up testing platform in June. For Insight Venture Partners, AI-based automation addresses a need created by the advance of Agile and DevOps methodologies in recent years. “Manual testing was beginning to stand in the way of agility,” said Emmet Keeffe, founder of Insight IGNITE – a late-stage, tech venture fund managed by Insight Venture Partners. “Development teams were getting pretty good at Agile from a development standpoint, but when they got to testing, they’d hit a brick wall, because it was still being done manually,” said Keeffe. “We noticed that a number of automated testing businesses were starting to accelerate really fast, and that’s when we made our investments.” Insight Venture Partners has stakes in a number of QA specialists, most notably Vienna-based Tricentis, in which it bought a majority stake in January 2017. The private equity firm also owns controlling shares in QA  Symphony (which it merged with Tricentis in June 2018), as well as  US-based Checkmark, a code quality specialist, and Switzerland-based SonarSource, an enterprise security start-up. Keeffe believes that the winners in the quality assurance market will be those vendors that manage to assemble the largest and most relevant portfolio of tools. But he also agrees with the assessment of Tricentis founder and chief strategy officer Wolfgang Platz that those firms will best be able to apply AI to its “core domain” of specific applications: image and voice recognition and natural language processing. Platz is suspicious of those companies that advertise artificial intelligence and machine learning as an all-purpose solution, despite, by his own admission, seeing great potential in these technologies. “There are a lot of companies who offer miraculous solutions to generate huge amounts of test cases. That’s not going to work,” he said, regarding the potential applications of AI. Other investors share the view of Carlyle’s Charlotte Lawrence that the impact of AI on software quality assurance will be far more wide-ranging. Tim Guleri, the managing director of tech and IT venture fund manager Sierra Ventures, based in San Mateo, is an evangelist for AI in testing, leading  Sierra’s 2017 investment in Applitools, a US-Israeli UI testing start-up. Applitools leverages AI in an way which can be considered part of the technology’s core domain, detecting bugs and inconsistencies in the user interface via image recognition. It performs thousands of scans of an app’s interface before and after a release, in order to detect significant changes and then alert the developer. According to Applitools CTO Adam Carmi, the software learns from previous releases and improves with time, being able to handle both static and dynamic application pages across devices, browsers and form factors. “[The growth of enterprise software] has taken software production and testing from an ad hoc, back office, process to a very critical business function, with billions of dollars tied to it,” said Guleri. “QA and testing, which used to be the redheaded stepchild in software development, has now become very critical both in the pre- and post-production side of launching a new feature or application.” QA is a great launchpad for AI within businesses, according to Guleri. The venture capitalist believes the full potential of AI  technology will be unlocked over the next few years, as tools are designed and built in accordance with specific business needs. “Companies like Applitools are taking billions of dollars of interface testing, which was not automated, and opening up a new market via the vertical application of AI. That is how AI is going to find its way into the enterprise,” Guleri said.