INTELLIGENT BRANDS // Software for Business
African enterprises may fail to understand compute and networking demands of AI life cycle
In a research report commissioned by Hewlett Packard Enterprise , nearly half , 44 % of IT leaders surveyed believe their organisations are fully set up to realise the benefits of AI . The report reveals critical gaps in their strategies , such as lack of alignment between processes and metrics , resulting in consequential fragmentation in approach , which will further exacerbate delivery issues .
12 months ,” said Sylvia Hooks , VP , HPE Aruba Networking .
“ AI is the most data and power intensive workload of our time , and to effectively deliver on the promise of GenAI , solutions must be hybrid by design and built with a modern AI architecture ,” said Dr Eng Lim Goh , SVP for Data and AI , HPE .
The report , Architect an AI Advantage , which surveyed more than 2,000 IT leaders from 14 countries , found that while global commitment to AI shows growing investments , businesses are overlooking key areas that will have a bearing on their ability to deliver successful AI outcomes – including low data maturity levels , possible deficiencies in their networking and compute provisioning , and vital ethics and compliance considerations .
The report also uncovered significant disconnects in both strategy and understanding that could adversely affect future return on investment , ROI .
“ There ’ s no doubt AI adoption is picking up pace , with nearly all IT leaders planning to increase their AI spend over the next
From training and tuning models onpremises , in a colocation or in the public cloud , to inferencing at the edge , GenAI has the potential to turn data into insights from every device on the network . However , businesses must carefully weigh the balance of being a first mover , and the risk of not fully understanding the gaps across the AI lifecycle , otherwise the large capital investments can end up delivering a negative ROI .
These findings clearly demonstrate the appetite for AI , but they also highlight very blind spots that could see progress stagnate if a more holistic approach is not followed . Misalignment on strategy and department involvement – for example – can impede organisations from leveraging critical areas of expertise , making effective and efficient decisions , and ensuring a holistic AI roadmap benefits all areas of the business congruently .
Of greater concern , fewer than 6 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 , 59 % and storing , 57 %, to processing , 55 % and recovering , 51 %. This discrepancy not only risks slowing down the AI model creation process , but also increases the probability the model will deliver inaccurate insights and a negative ROI . p
Sylvia Hooks , VP , HPE Aruba Networking
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 , 7 % of organisations can run real-time data pushes , pulls to enable innovation and external data monetisation , while just 26 % have set up data governance models and can run advanced analytics .
Dr Eng Lim Goh , SVP for Data and AI , HPE
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