TRENDING
MOVING BEYOND HYPE AND OVERCOMING CHALLENGES OF AI
One of the primary hurdles to successful AI implementation is data readiness since AI systems require vast amounts of data to function effectively . Yet many organisations are not equipped to analyse data efficiently . IFS research finds only a minority of businesses have necessary cloud infrastructure and data readiness in place says Christian Pedersen at IFS .
Artificial Intelligence , AI has been heralded as the next great technological revolution , with many commentators claiming it will have a bigger impact on the world than even the Internet . The promise of AI spans industries , from enhancing productivity and innovation to transforming business models and customer experiences . projects and realise the full potential of AI . This discrepancy has led to a growing sentiment that the AI hype is dying .
Indeed , MIT ’ s leading economist Daron Acemoglu ’ s paper published in the National Bureau of Economic Research forecasts a lot more modest GDP gains of around 1 %. But why is this happening ? A closer look reveals that the challenges lie not in the technology itself but in the readiness and strategic alignment of organisations .
In 2023 Goldman Sachs economists estimated that AI would increase annual global GDP by 7 % over 10 years , equivalent to $ 7tn . More recently , Goldman Sachs has taken a more critical view of AI return on investment , sparking a broader discussion on how to get to AI results .
However , the reality has been more complex , with many organisations struggling to move beyond pilot
According to a recent study by IFS of 1,700 senior leaders , a significant majority of executives , 84 % are optimistic about AI ' s potential to bring substantial benefits to their organisations . However , there is a palpable concern among 82 % of senior decision-makers that the AI bubble may burst if projects fail to move beyond the pilot stage due to a lack of strategy , proper implementation , and communication .
Analyst Gartner recently claimed that by the end of 2025 , at least 30 % of Generative AI projects will be abandoned after proof of concept . These studies highlight that while there is enthusiasm , there is also a recognition of the
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