TRENDING approach as ‘ fragmented ’. As evidence of this , over a third ( 38 %) of organisations have chosen to create separate AI strategies for individual functions , while 38 % are creating different sets of goals altogether .
About the report
More dangerous still , it appears that ethics and compliance are being completely overlooked , despite growing scrutiny around ethics and compliance from both consumers and regulatory bodies . The research shows that legal / compliance ( 15 %) and ethics ( 14 %) were deemed by IT leaders to be the least critical for AI success . In addition , the results showed that almost one in four organisations ( 20 %) aren ’ t involving legal teams in their business ’ s AI strategy conversations at all .
The fear of missing out on AI and the business risk of over confidence
As businesses move quickly to understand the hype around AI , without proper AI ethics and compliance , businesses run the risk of exposing their proprietary data – a cornerstone for retaining their competitive
If businesses continue their current approach to AI , it will adversely impact their long-term success .
HPE commissioned Sapio Research to conduct a survey to examine where businesses are in their AI journeys , and whether they are taking a holistic enough approach to position themselves for success . The survey included 399 IT decision makers ( IT leaders ) from the UK and Ireland . These IT leaders work at companies of 500-plus employees , and span industries from financial services to manufacturing , retail and healthcare .
shows data maturity levels remain low . When combined with the metric that less than half of IT leaders admitted to having a lack of full understanding on the IT infrastructure demands across the AI lifecycle , there is an increase in the overall risk of developing ineffective models , including the impact from AI hallucinations . Also , as the power demand to run AI models is extremely high , this can contribute to an unnecessary increase in data centre carbon emissions . These challenges lower the ROI from a company ’ s capital investment in AI and can further negatively impact the overall company brand . edge and maintaining their brand reputation . Among the issues , businesses lacking an AI ethics policy risk developing models that lack proper compliance and diversity standards , resulting in negative impacts to the company ’ s brand , loss in sales or costly fines and legal battles .
There are additional risks as well , as the quality of the outcomes from AI models is limited to the quality of the data they ingest . This is reflected in the report , which
“ If businesses continue their current approach to AI , it will adversely impact their long-term success ,” continued Armstrong-Barnes . “ They must adopt a comprehensive end-to-end approach across the full AI lifecycle to streamline interoperability and better identify risks and opportunities . Considering AI – especially GenAI – is data , power , time and resource intensive to deploy and maintain , businesses need to take the necessary steps and lay the groundwork for their deployments so they don ’ t run before they can walk .” p
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