Singapore, 23 December 2025 — AI will keep boosting productivity in 2026, but the darker storyline is getting harder to dismiss: the tools are improving, the costs are falling, and bad actors are learning faster than many organizations can update controls. Singapore’s own regulators and agencies have already warned about digitally manipulated scams and deepfakes targeting businesses, an early sign that what used to feel “theoretical” is already operational. Below are six scary predictions for AI in 2026, not as clickbait, but as realistic scenarios stitched together from what authorities, analysts, and recent reporting are already flagging.
1) Deepfake-enabled payment fraud becomes “business as usual”
In 2026, deepfakes won’t be a once-in-a-while headline, they’ll become a routine tactic in corporate fraud. Singapore agencies have already described scam variants where criminals use digital manipulation to impersonate high-ranking executives, pressuring staff into transferring funds.
MAS has also highlighted cyber risks associated with deepfakes, including impersonation and fraudulent transactions, underscoring that this is a financial-sector concern, not just a social-media problem.
2) “Government official” impersonation scams get more convincing and more automated
Singapore Police Force advisories show impersonation scams continue evolving, including cases where scammers impersonate telcos and even MAS-linked contexts. ScamShield also warns that government-official impersonation scams can happen through calls and video calls, which is exactly where AI voice and face manipulation thrives.
3) Agentic AI turns into a new “attack surface” inside companies
The rise of agentic AI, systems that plan, decide, and act will change workflows in 2026, especially in finance and customer service. Reuters recently reported banks pushing into agentic AI trials expected in early 2026, while regulators flagged concerns tied to the speed and autonomy of these systems.
At the same time, Gartner’s 2026 tech-trend brief highlights the need for AI security platforms to protect AI investments against risks such as prompt injection, data leakage, and “rogue agent actions.”
4) A trust crisis spreads: people stop believing what they see (and brands pay the price)
Singapore’s anti-fraud community is already treating AI-enhanced deception as a mainstream threat, with reporting noting how AI and deepfakes are accelerating scam sophistication and scale.
5) Power and compute become the hidden constraint that slows AI ambitions
AI needs compute; compute needs electricity; electricity in Singapore is a strategic constraint. IMDA notes data centers use about 7% of Singapore’s total power consumption (with projections rising), and Singapore has been tightening sustainability expectations even as demand grows.
On 1 Dec 2025, EDB and IMDA launched the second Data Centre Call for Application (DC-CFA2), making at least 200MW available (and potentially more via green energy pathways). Reuters also reported this new 200MW call and noted it builds on earlier allocations awarded in 2023.
6) Regulation and procurement shift from “guidance” to “hard requirements”
For Singapore companies selling into Europe or using European platforms and partners, 2026 is a compliance turning point. The European Commission’s official timeline says the EU AI Act becomes fully applicable on 2 Aug 2026, with important rules already phased in earlier.
The Commission’s AI Act service desk also states that in August 2026, most rules come into force and enforcement starts, including transparency-related requirements. Reuters has also covered EU guidance linked to prohibited practices and the ramp-up to full implementation.
If 2025 was the year AI became normal, 2026 may be the year AI risk becomes operationally expensive. The scary part isn’t one breakthrough moment; it’s accumulation: more believable fraud, more automation inside companies, tighter energy limits, and faster-moving compliance expectations.
AI will keep getting more useful in 2026, but it will also get easier to weaponize, harder to govern, and more resource-intensive to run at scale. For Singapore, the story won’t be “AI vs no AI,” but how quickly organizations can build trust into everyday operations, verifying identities, securing autonomous tools, and proving governance, while staying realistic about infrastructure and regulation that will shape what’s possible.