In today’s volatile environment, your customers, partners, and employees are more dependent than ever on your ability to deliver reliable digital services. To rise to the challenge, Change and Release Management leaders must balance competing priorities for speed and reliability. Unfortunately, traditional Change Management processes struggle to balance the need for increased change frequency and shorter lead times with the risk of IT service disruptions. At the same time, Release Management must ensure that the higher volume of deployed changes doesn’t cause unexpected issues. The result is that in the face of increased volatility, organizations often resort to a change freeze. How can AI-powered Change and Release Management improve the quality, availability, and performance of these mission-critical services?

Join Joe Foley, Digital.ai Insights Architect, and Neal DeBuhr, Digital.ai Solution Architect, to learn how to:

• Bring together DevOps, IT Service Management, Application Performance Monitoring, and other data to fuel Change and Release Management success
• Predict risky changes and identify root causes both upstream and downstream of change with Machine Learning
• Find and eliminate the systemic causes of change failure across people, processes, and technologies

Apply these principles today, like your peers in Fortune 500 organizations. Get started, even if you don’t have data scientists in your organization