TRENDING
from AI and who needs to be involved in its roll-out will lead to misalignment between departments and fragmentation that limits its potential .”
Acknowledging Low Data maturity the model will deliver inaccurate insights and a negative ROI .
Provisioning for the end-toend lifecycle
Strong AI performance that impacts business outcomes depends on quality data input , but the research shows that while organisations clearly understand this – labelling data management as one of the most critical elements for AI success – their data maturity levels remain low . Only a small percentage ( 6 %) of organisations can run real-time data pushes / pulls to enable innovation and external
Organisations are failing to connect the dots between key areas of business .
A similar gap appeared when respondents were asked about the compute and networking requirements across the end-to-end AI lifecycle . On the surface , confidence levels look high in this regard : 92 % of IT leaders believe their network infrastructure is set up to support AI traffic , while 83 % agree their systems have enough flexibility in compute capacity to support the unique demands across different stages of the AI lifecycle .
Gartner expects : “ GenAI will play a role in 70 % of textand data-heavy tasks by 2025 , up from less than 10 % in 2023 ,” yet less than half of IT leaders admitted to having a full understanding of what the demands of the data monetisation , while just 29 % have set up data governance models and can run advanced analytics .
Of greater concern , fewer than six in 10 respondents said their organisation is completely capable of handling any of the key stages of data preparation for use in AI models – from accessing ( 57 %) and storing ( 51 %), to analysing ( 54 %) to processing ( 52 %). This discrepancy not only risks slowing down the AI model creation process , but also increases the probability various AI workloads across data acquisition , model training and monitoring might be – calling into serious question how accurately they can provision for them .
Ignoring cross-business connections , compliance and ethics
Organisations are failing to connect the dots between key areas of business , with over a quarter ( 28 %) of IT leaders describing their organisation ’ s overall AI
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