Intelligent CIO North America Issue 52 | Page 43

FEATURE : 2025 CIOS ’ PRIORITY breed of tooling emerge to address the observability needs around machine identity creation , permissions , use , and eventual revocation at a global scale .
This will be a challenging road to travel for larger enterprises with thousands of legacy codebases . Still , there is evidence this shift has already begun in the largest organizations . Smaller players and the SMB market will most likely follow once the tool ecosystem expands . Startups are , as always , in the greatest position to leverage technological advancements in this space , as we have previously seen with SaaS offerings , giving them a competitive advantage as they build their platforms faster and safer than larger companies can .
Ali Shaikh , Chief Product Officer , Graphiant
For CIOs , the priority in 2025 is to ensure that enterprise networks are modernized to meet the demands of artificial intelligence ( AI ). As AI becomes pervasive in business operations , networks must be upgraded to facilitate data movement , compliance , and performance .
Business leaders must embrace a network architecture that delivers on privacy and security while accelerating on-demand delivery of new services to their customers . This strategy ensures businesses meet AI ’ s high-speed data transfer requirements while maintaining cost efficiency and agility . CIOs must explore implementing Network-asa-Service ( NaaS ) solutions , which provide scalability , cost savings , and advanced features like AI-driven traffic management and automated provisioning . This model empowers businesses to respond dynamically to AI demands without significant hardware investments .
With increasing use of AI , security and compliance will require increased focus and investment . Leaders should be prepared to respond to real-time threats and have an infrastructure that is ready to meet compliance regulations and global data sovereignty laws . AI models process sensitive data , often involving proprietary information , customer data , or critical business insights . Ensuring the security of this data throughout the AI lifecycle – during data collection , processing and storage – is paramount . p
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