Smaller models, better chips and renewable power help. So does only using AI when you need to.
Concentrandosi sulle applicazioni, sui dati e sui processi più importanti per l’azienda è possibile ridurre i rischi e risparmiare denaro.
Focusing on the apps, data, and processes that mean most to the business can reduce risk and save money.
While good for fast experiments and automating routine tasks, low code/no code tools can lack scalability and security. Here are some top use cases, and those where they might miss the mark.
Businesses are employing enterprise architecture to improve product delivery, risk management, and even employee retention, among other business-critical uses.
Leading CIOs are doing u201cjust enoughu201d enterprise architecture to balance speed with long-term, strategic insights for better business value.
Doing too much too fast, under-communicating, failing to focus on the businessu2026 as with so many IT initiatives these common mistakes can undermine ITSM effectiveness.
AIops speeds IT discovery and troubleshooting, but it isnu2019t magic. And operations staff must still prepare the data for machine learning and manually solve some issues.