The demand for faster software releases has created new challenges for those that fail to test earlier and more frequently in the Systems Development Life Cycle (SDLC). Bugs found post release instead of in the early stages of the SDLC cost organizations significant sums of money and irreversible damage to their brand, customer retention, regulation compliance, and the overall bottom line. By deploying AI analytics in conjunction with shift left, organizations can increase product release efficiency and minimize costs associated with reactive remediation.
Shift left allows organizations to remain proactive as it pertains to unit, functional, and non-functional testing (performance and security), in order to properly enable both business and technical users to execute tests early and often. This ensures consistent quality, full visibility, security, and faster time to market. By also deploying AI capabilities, QA and dev teams can start testing even earlier, test smarter and streamline critical decision making in the testing cycle.
Watch this webinar with guest speaker Diego Lo Giudice, (VP, Principal Analyst at Forrester) and Guy Arieli, (QA CTO Digital.ai Continuous Testing), for a closer look on how to align distributed teams with unified business metrics. During the presentation, the speakers will discuss the importance of shifting left to create effective, repeatable testing strategies, as well as:
- The benefits of prioritizing testing earlier in the SDLC
- The necessary cultural shift and how to organize teams for success
- Creating synergies to increase productivity between teams
- Leveraging AI and ML to create efficiencies and optimize testing
- Automated test execution for non-technical users