FEATURE : CIO PRIORITIES
Analysts explore how CIOs can seize uncertainty and make the most of it in 2023 and beyond .
Through 2027 , fully virtual workspaces will account for 30 % of the investment growth by enterprises in Metaverse technologies and will ‘ reimagine ’ the office experience
As employees continue to desire more flexible work scenarios , virtual workspaces in Metaverses will emerge to support new immersive experiences . Fully virtual workspaces are computer-generated environments where groups of employees can come together using personal avatars or holograms .
Gartner has revealed its top strategic predictions for 2023 and beyond . Gartner ’ s top predictions explore how business and technology leaders can reimagine assumptions and seize the moment to turn uncertainty into certainty .
“ Uncertainty carries as much opportunity as it does risk ,” said Daryl Plummer , distinguished VP Analyst and Gartner Fellow . “ The key to unlocking those opportunities is to reimagine assumptions – especially those rooted in a pre-digital past – around how work is done , how relationships between customers and providers will evolve and how current trends will unfold .
“ The comforts of consistency are a detriment to the growth of any company seeking to lead in a modern digital world filled with unknowns . This year ’ s predictions provide a foundation for executive leaders to seize uncertainty , challenge thinking and change expectations while maintaining forward movement .”
Gartner analysts have presented the top 10 strategic predictions for guidance .
“ Existing meeting solution vendors will need to offer Metaverse and virtual workspace technologies or risk being replaced ,” added Plummer . “ Virtual workspaces deliver the same cost and time savings as videoconferencing , with the added benefits of better engagement , collaboration and connection .”
By 2025 , without sustainable Artificial Intelligence ( AI ) practices , AI will consume more energy than the human workforce , significantly offsetting carbon-zero gains
As AI becomes increasingly pervasive and requires more complex Machine Learning ( ML ) models , it consumes more data , compute resources and power . If current AI practices remain unchanged , the energy needed for ML training and associated data storage and processing may account for up to 3.5 % of global electricity consumption by 2030 .
Yet as AI practitioners become more aware of their growing energy footprint , sustainable AI practices are emerging , such as the use of specialised hardware to
Gartner unveils top predictions for IT organisations and users in 2023
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