KUALA LUMPUR, June 22 (Bernama) -- Bursa Malaysia ended on a softer note today as investors engaged in profit-taking following the recent rebound in the local market, an analyst said. At 5 pm, the FTSE Bursa Malaysia KLCI (FBM KLCI) declined by 0.65 per cent, or 11.19 points, to 1,700.84 from last Friday's close of 1,712.03. The benchmark index opened 1.56 points lower at 1,710.47 and moved between 1,699.94 and 1,712.32 throughout the trading session. Market breadth was negative, with decliners outnumbering gainers 560 to 481. A total of 608 counters were unchanged, 1,649 untraded, and 14 suspended. Turnover slipped to 3.29 billion units worth RM2.40 billion from 3.45 billion units worth RM3.79 billion on Friday.
The global market for artificial intelligence (AI)-related products is set to soar to nearly US$1 trillion by 2027, according to a new report by Bain & Co. The rapid adoption of AI across industries and governments is expected to disrupt companies and economies, fueling market growth of 40% to 55% annually from US$185 billion in 2023 to an estimated US$780 billion to US$990 billion by 2027.
This growth will be driven by the expansion of AI systems and data centers, as companies and governments increasingly leverage AI to enhance efficiency. Bain warns that rising demand could strain supply chains for key components, particularly semiconductors, which are crucial for running AI services. Geopolitical tensions may further exacerbate potential shortages in chips, personal computers, and smartphones.
Upstream chip components, such as integrated circuit design, could see demand rise by 30% or more by 2026, placing added pressure on manufacturers. The cost of larger data centers is also expected to surge, with current costs of US$1 billion to US$4 billion potentially rising to US$10 billion to US$25 billion in five years, as their capacity expands significantly.
“These changes are expected to have huge implications on data center ecosystems, including infrastructure engineering, power production, and cooling,” Bain stated.
As companies move beyond the experimental phase, they are beginning to scale generative AI across their operations. Smaller, more efficient language models may gain favor among enterprises due to concerns about costs and data privacy.
Governments worldwide, including Canada, France, India, Japan, and the UAE, are investing billions in building sovereign AI ecosystems, focusing on domestic computing infrastructure and AI models trained on native data. However, establishing these ecosystems will be a time-consuming and expensive process, Bain’s Global Technology practice head, Anne Hoecker, noted.
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