Richard Ward - 4 June 2019
In the first post in our MythBusters series, we examined the misperception that testing is solely a compliance activity and showed how it’s actually a business critical function with bottom-line impact. In this installment, we’re looking at the role AI plays in the industry, the numerous misconceptions that abound, and why it’s important that companies cut through the noise to understand how the technology can benefit them today.
Myth #2: AI Is Not Delivering Tangible Benefits
Stanford computer scientist Andrew Ng recently likened AI to electricity, calling it a general purpose technology that is revolutionizing numerous industries. Enterprise software is one such sector, and we believe one of AI’s chief benefits lies in its power to transform traditional approaches to app development and testing.
And we aren’t the only ones. In an AI-focused survey released earlier this year, Chris Howard, research vice president at Gartner, said, “If you are a CIO and your organization doesn’t use AI, chances are high that your competitors do and this should be a concern.” The survey found enterprise AI adoption has tripled in the last year alone and grown a whopping 270 percent in the past four years.
So why are we still seeing so many articles suggesting AI has yet to deliver any real value? I think a lot of it comes down to confusion over what exactly AI is, and what we should realistically be expecting from the technology at this stage of its development and adoption.
In testing, AI can be employed today to automate numerous functions, driving benefits in the form of error reduction, predictions of likely quality issues and increased time for manual testers to perform exploratory testing, to name just a few. This approach enables companies to meet the continuous delivery expectations of the digital enterprise while continuing to ensure a high-quality user experience. Among the AI benefits Eggplant delivers are:
- Expanded test automation
- More productive testing within the shrinking windows associated with continuous delivery
- Coverage of more applications and user journeys without any additional manual effort
- Faster time to value
As the above underscores, AI in testing is not a magic technology that solves every complex test problem with little human collaboration or oversight. Those that mistakenly have that viewpoint will no doubt be disappointed by the reality of how and what AI can deliver. But I challenge anyone to argue that the benefits listed above aren’t improvements that could positively impact the pace of software releases, user satisfaction and revenue.
We’re still a long way from expecting AI to wholly solve complex tasks—a fact acknowledged by both Gartner’s Chris Howard and Andrew Ng. However, the technology is a transformative force that is already proving invaluable in app development and testing. Any notion to the contrary is simply misguided.
Learn more about AI in testing here and keep an eye on this blog for more in our MythBusters series.