Far East Organization is among those seeing tangible benefits. It automated end-to-end lease management using SAP’s solutions to improve data accuracy, reduce manual inputs, and provide real-time insights into portfolio performance. These enhanced analytics now track trends in rental, occupancy rates, and lease durations, giving property managers actionable insights to respond faster to market changes while making better decisions that strengthen portfolio and operational management.
"What previously took days can now be completed in minutes, giving our teams the time and insight to focus on customers and business growth. Building on this success, we continue to innovate with SAP Business AI," says Ng Yee Pern, Far East Organization’s CTO.
Still, data quality problems and governance weaknesses could undermine organisations’ AI ambitions. A separate Salesforce State of Data and Analytics report shows that 91% of data and analytics leaders in Singapore say their data strategies need a complete overhaul before their AI plans can succeed.
Respondents estimate that 27% of their organisational data is untrustworthy, while 21% is siloed or inaccessible, with most of the valuable business insights residing within that inaccessible portion.
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Application sprawl is worsening the issue. The average enterprise uses 897 applications, but only 29% are connected, resulting in data scattered across silos.
“Fragmented data and inconsistent governance continue to hold organisations back from realising [agentic AI’s] full potential, [which can] usher unprecedented productivity, customer connection and growth,” says Gavin Barfield, vice president and chief technology officer for solutions in Asean at Salesforce.
Security concerns add another layer of complexity. Singaporean organisations experienced an average of 10 data loss incidents per year, with 45% attributing their most significant events to careless employees or contractors, according to Proofpoint's second annual Data Security Landscape report.
See also: AI adoption is surging in Asia but are we using it right?
AI tools themselves are emerging as a new source of risk. Forty per cent of organisations cite data loss via public or enterprise generative AI tools as a top concern, while 35% flag unsupervised data access by AI agents as a critical threat. Almost half lack sufficient visibility and controls over generative AI tools, reveals the Proofpoint survey.
"Nearly half of Singaporean organisations lack adequate oversight of generative AI tools, while experiencing an average of 10 data loss incidents annually. As Singapore continues to lead in AI implementation, organisations must move beyond fragmented point solutions,” says George Lee, senior vice president for Asia Pacific and Japan at Proofpoint.
Workforce readiness presents another bottleneck. The SAP study found that 76% of organisations have not yet provided comprehensive AI training for employees, even as 68% acknowledge that shadow AI (or the use of unapproved or unregulated AI tools) is already in use internally.
"Agentic AI represents the next frontier of business transformation. It has the potential to multiply productivity and innovation, but its success depends on the same fundamentals: data quality, integration, and people readiness,” says Eileen Chua, managing director of SAP Singapore
