EDITOR ’ S QUESTION
CARL D ’ HALLUIN , CTO , DATADOBI
As Artificial Intelligence ( AI ) and Machine Learning ( ML ) technologies continue to be developed and deployed across virtually every industry vertical in companies of all sizes , the role of the Chief Information Officer ( CIO ) must evolve to help ensure that their organizations are well-equipped to benefit from these powerful tools .
From a technical standpoint , CIOs will need to be ready to spearhead major infrastructure overhauls to support the massive scale of data and computing power required for a performant AI pipeline , particularly unstructured data which already makes up the bulk of most organization ’ s data assets and is only predicted to grow in data dominance . This will likely involve rearchitecting systems to store , manage , and analyze petabytes of data .
As valuable unstructured company data lives in a variety of locations in the data centers and in the cloud , it will also require implementing advanced unstructured data management platforms with analytics and automation capabilities that can process these immense datasets in real-time to deliver actionable insights , and ensure data is where it needs to be , when it needs to be there . These systems must support identifying which unstructured data should be used for training the ML model and which shouldn ’ t . With the advent of GenAI , the generated data should be tagged as well since it is probably not desirable to use that data in future ML training cycles .
Beyond technology , another critical part of the CIO ’ s role in enabling AI / ML adoption is facilitating effective cross-departmental communication and collaboration . As AI / ML projects often cut across multiple business units , CIOs must be able to break down silos and
foster cooperation between teams like data science , IT , marketing , operations , and more . Regular interdepartmental meetings and joint planning sessions can help ensure all stakeholders are aligned on goals and timelines . Collaboration platforms that provide transparency into ongoing work can help avoid duplication of efforts . By promoting interaction and partnership across functions , CIOs can help their organizations develop integrated , enterprise-wide AI / ML strategies that deliver value company-wide rather than just in isolated business areas .
And finally , CIOs must be ready to advise executive leadership and individual business units on developing AI / ML solutions that create tangible business value rather than simply adopting technology for technology ’ s sake .
The CIO role is evolving from purely technical implementation to include guiding business transformation . Those CIOs who can empower their companies to fully realize AI / ML ’ s benefits through scalable platforms , strong governance , and collaborative leadership will set their businesses up for success in the future .
CIOs constantly need to evaluate not only AI ’ s potential as more use cases are developed but also the new set of tools supporting them .
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