building the artificial intelligence-enabled enterprise of the future

artificial intelligence is reshaping industries by automating repetitive tasks, analysing vast datasets, and augmenting human capabilities. companies face urgent pressure to deploy strategies while infrastructure and readiness gaps persist.

artificial intelligence is fundamentally reshaping how organisations operate, with the potential to automate repetitive tasks, analyse vast datasets, and augment human capabilities. the article highlights concrete sector impacts: in health care and pharmaceuticals machine learning and artificial intelligence tools are advancing diagnosis, cutting drug discovery timelines by as much as 50 percent, and enabling more personalised treatments. in supply chain and logistics artificial intelligence models can help prevent or mitigate disruptions, and across research and development cycles artificial intelligence may reduce time to market by about 50 percent and lower costs in industries such as automotive and aerospace by up to 30 percent.

the speed of change is driving intense urgency among companies. nearly all respondents say they feel increased urgency to act, with 98 percent reporting more pressure in the last year and 85 percent believing they have less than 18 months to deploy an artificial intelligence strategy or face negative business effects. industry leaders emphasise the scale of the transformation: Patrick Milligan, chief information security officer at Ford, describes the moment as an inflection point whose full societal significance is not yet apparent.

despite that urgency, readiness remains low. only 13 percent of companies globally report being ready to leverage artificial intelligence to its full potential, and two thirds (68 percent) say their infrastructure is moderately ready at best to adopt and scale artificial intelligence technologies. the article identifies essential capabilities that organisations must build: sufficient compute power for complex models, optimised network performance across sites and data centres, and stronger cybersecurity to detect and prevent sophisticated attacks. observability to monitor and optimise infrastructure and models, and high-quality, well-managed enterprise-wide data are also highlighted as prerequisites. supporting all technical work are organisational needs for an artificial intelligence-focused culture and talent development.

industry voices warn against delay. Jeetu Patel, president and chief product officer at Cisco, cautions that organisations that wait risk becoming irrelevant to competitors that use artificial intelligence more effectively. the article concludes with a disclosure that the piece was produced by Insights, the custom content arm of MIT Technology Review, and that any artificial intelligence tools used were limited to secondary production processes subject to human review.

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