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“ As a CIO , you need to understand your AI account ,” said LeHong . “ You have to understand the cost components and pricing model options , and you need to know how to reduce those costs and negotiate with suppliers . CIOs must create proofs of concept that test how costs will scale , not just how the technology works .”
Data and AI everywhere create new challenges and risks : With the proliferation of AI and data across the enterprise , it ’ s no longer centralized assets that IT directly controls . Gartner research revealed that , on average , only 35 % of AI capabilities will be developed by IT teams . This means that new approaches are needed to manage and secure data access , govern AI inputs and outputs , and deliver value securely .
Data Everywhere and Every Kind
Embedded AI
BYOAI
TRiSM
Built AI
Centralized Data
“ This is where the concept of the ‘ tech sandwich ’ comes in ,” LeHong said when describing the AI tech stack of the future . “ At the base of the sandwich are all the IT data and AI , typically centralized . At the top are all the data and AI coming from everywhere , typically decentralized . And in between are trust , risk and security management ( TRiSM ) technologies that make it all secure . That ’ s what you need to build to accommodate AI and data that comes from everywhere .”
“ As a CIO , your job is to design a tech sandwich that can handle the complexity of AI but still allow you to take advantage of new opportunities ,” Mesaglio said .
“ Companies with a steady pace of AI ( with ten AI initiatives or less ) will govern their tech sandwiches using human teams and committees . AI-accelerated companies will add TRiSM technologies – a set of technologies designed to build trust , monitor risk , and manage security for secure AI at scale .”
Use of AI can positively and negatively impact employee performance and well-being
Some employees may have a strong affinity for AI , while others may feel threatened or resentful . These intense reactions to AI can lead to unintended behavioral outcomes that negatively impact job performance , such as jealousy of those who use AI and over-reliance on AI tools . However , few companies are actively managing these behavioral outcomes .
In the June / July Gartner survey , only 20 % of CIOs said they focus on mitigating the potential negative impacts of Gen AI on employee well-being .
“ Most companies aren ’ t curious enough about how AI makes their employees feel . This is important because AI can lead to a variety of unintended behavioral outcomes ,” Mesaglio said .
“ The critical point is that if you use change management to deal with this , be intentional about who is responsible for which behavioral outcomes . Companies must manage behavioral outcomes with the same rigor as technological and business outcomes .” p
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