EDITOR ’ S QUESTION

From private LLMs for code generation to improved decision-making , AI is fundamentally changing how CIOs operate and lead .

Automation is one clear workload difference . The question right now for many CIOs is just how much they can confidently automate .

But with ever-more-capable algorithms , AI is handling repetitive tasks and complex technical processes that free up the office of the CIO for more strategic and business-growing initiatives .

Tasks such as provisioning and managing IT infrastructure , monitoring system performance , and resolving network issues are now expedited with AI , allowing CIOs to focus even more of their time on highlevel planning and decision-making .

Another big workload difference : CIOs are taking advantage of what AI is bringing to their organization ’ s software development lifecycle .

The result here is faster project delivery , which is helping CIOs demonstrate more value to their organizations .

Critically , AI is also empowering CIOs with improved decision-making capabilities .

CIOs are using AI ’ s analytical power to predict future IT needs , optimize resource allocation , and identify potential risks .

The ability to make data-driven decisions has always been a game-changer , of course , but CIOs who are now smartly tapping advanced AI tools to help with this are particularly well positioned .

Another change to a CIO ’ s workload is their own research and experimentation with bleeding-edge AI technologies .

CIOs are using AI ’ s analytical power to predict future IT needs , optimize resource allocation , and identify potential risks .

CIOs at larger enterprises , in particular , are working to develop private LLMs for code generation across their companies .

CIOs currently using public LLMs like OpenAI ’ s ChatGPT might be fine for some lower-priority use cases , but public LLMs pull source data from , well , the wild internet – meaning output can be very risky for critical or sensitive tasks .

There are so many new AI capabilities and startups emerging , seemingly daily , that many CIOs I work with are setting aside dedicated time for putting different AI technologies through the proverbial wringer to determine viability .

It ’ s no small task , and most CIOs understand the value of being able to adapt quicker than competitors to business-improving AI solutions .

CIOs now getting the private LLM strategy right are automating key parts of the software and application development lifecycle while ensuring far more security than public LLMs ( and reducing the burden put onto a CIO ’ s engineering teams ).

Finding the signal in the noise isn ’ t easy right now , but CIOs devoting the time and getting it right are certainly being rewarded . p

BRIAN SATHIANATHAN , CHIEF TECHNOLOGY OFFICER , ITERATE . AI

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