Artificial intelligence would strengthen intelligence within companies, and would do the same for IT workshops. For example, AIOps (artificial intelligence for IT operations) applies AI and machine learning to data from IT processes, sifting through noise to detect, highlight and prevent problems. AI and machine learning also find their place in another emerging area of IT: helping DevOps teams ensure the viability and quality of software that moves at ever-increasing speeds through the system and to users. . As a recent survey by GitHub indicates, development and operations teams are massively turning to AI to streamline code flow in the software review and testing phase. The survey also reveals that 37% of teams are using AI/ML in software testing (up from 25% previously), and another 20% plan to use it this year.

Are AI-based testing technologies a dream or nightmare for professional software testers? How much testing can (and should) we delegate to AI? What are the true benefits…and risks? Join this webinar to watch a lively panel discussion in which Wolfgang Platz (Tricentis Founder and Chief Strategy Officer) and leaders from Gartner, Wipro and Accenture debate these and other AI-focused topics that are currently polarizing the software testing industry. Is AI real in software testing, or are we just looking at a load of "marketing BS"? How is AI really delivering business outcomes today?

"I may find three bugs, but the way I report information could change the decisions that business people have made, and I think business people will value those who help them make better decisions." On this episode of the Continuous Testing Live podcast, well-known software testing entrepreneur Pradeep Soundararajan shares his views on the opportunities that AI offers to testers who keep an open mind and a strong focus on user experience. Soundararajan also shares two questions that testers should always ask themselves when working to make informed decisions that impact both their customers and the business. Click here to listen to the podcast. Noel: So when I think of AI and machine learning in the software testing industry, I envision people using it to take care of things the same way we think about test automation: something we use for functional testing. But when I read a blog you wrote, titled, "AI-driven Functional Testing," it got into how we might also be able to use AI for exploratory testing, which I had not seen anyone write or talk about before. I'm really curious about the word "driven" in that title and wanted to get you to maybe expand a bit on how AI can be used to not just "aid" your functional test efforts, but really "drive" them.