The
following is my answer to a Quora question: “Is
the increase in Singapore’s core inflation from the middle of next year a
concern?”
You
are seeing the numbers, but looking at the wrong thing. The headline is that Singapore’s core
inflation reached 1.6 per cent in June 2026, up from 1.4 per cent in May. The concerned reaction is
understandable. It is also premature. The Monetary Authority of Singapore’s
forecast band for core inflation in 2026 is 1.5 to 2.5 per cent. At 1.6 per cent, Singapore is at the lower
bound of its own projection. Overall CPI
came in at 1.9 per cent for June. These
are not the numbers of a runaway price environment. They are the numbers of an economy running
warm on the back of growth — which, in an economy of Singapore’s structure, is what
you would expect.
GDP
growth for Q2 2026 was 6.2 per cent year-on-year. Q3 2026 delivered 5.4 per cent. The International Monetary Fund projects 5
per cent for the full year. Manufacturing
grew 7.5 per cent, driven by semiconductors.
Construction grew 8.8 per cent, driven by data centres. Singapore accounts for 10 per cent of global
semiconductor output and 20 per cent of semiconductor equipment supply. The economy is not struggling. The economy is being rebuilt around
artificial intelligence infrastructure, and that process costs money. Some of that cost appears in the price
level. This is what demand-pull
inflation looks like when the demand is productive.
The
Straits of Hormuz: A Tax on Asian Energy
The
external shock is real, and it is not Singapore’s fault. The Strait of Hormuz carries 18.4 million
barrels of oil per day — one-fifth of global supply. 84 per cent of Hormuz crude flows to
Asia. The conflict in the Middle East
has cut net supply by 11 million barrels per day. Brent crude has crossed US$100 per
barrel. The strait also carries 110
billion cubic metres of liquefied natural gas per year. QatarEnergy’s LNG capacity is down 17 per
cent. Asian spot LNG prices have risen
from US$10 to US$12 per million British thermal units to above US$25. European buyers are paying €500 million per
day in additional energy costs — a figure that understates the Asian exposure,
given where the physical flows go. Newcastle
coal, the regional benchmark, has moved from US$114 to US$132 per tonne.
Singapore
essentially imports all its energy.
Higher energy costs feed into utility bills, transport, and
manufacturing inputs. They are not a
structural shift in Singapore’s price level.
They are a contingent external shock, driven by geopolitics rather than
domestic policy. The MAS has noted that
AI-driven demand pressure is expected to ease in the second half of 2027. Energy prices will ease when the conflict
permits. Core inflation is forecast to
return within the lower half of the MAS band as those pressures unwind. Singapore’s inflation is manageable, and its
causes are well-understood. The more
interesting question is what comes next — and the answer has nothing to do with
the CPI.
The
AI Boom: Singapore at the Centre
Singapore
has positioned itself well for the decade’s defining capital expenditure
cycle. Singapore is a data centre hub
for Southeast Asia, a semiconductor manufacturing base of global importance,
and a financial gateway for the region’s technology investment flows. The hyperscaler build-out — Microsoft,
Google, Amazon, Meta — has treated Singapore as essential infrastructure. Data centre construction has driven the 8.8
per cent surge in the construction sector.
The semiconductor equipment cluster supports the regional AI chip supply
chain.
These
are not small numbers. Global
hyperscaler capital expenditure exceeded US$700 billion in 2026, according to
Moody’s estimates. A significant
fraction of that spending flows through or lands in Singapore — in land, power,
talent, logistics, and financial services.
The GDP numbers reflect this. The
construction numbers reflect this. The
current account reflects this. For
Singapore’s immediate growth story, the AI boom has been a gift. The concern is what happens when the boom
encounters arithmetic.
The
AI Debt Cliff
In
December 2025, Bank of America warned investors to brace for what it called an “air
pocket” in artificial intelligence spending.
The warning was not about whether AI is useful. It was about whether the capital expenditure
cycle is sustainable at its current scale and pace. The numbers are uncomfortable. Amazon, Google, Meta, Microsoft, and Oracle
collectively issued US$121 billion in debt in 2025 — four times their average
annual debt issuance over the preceding five years. We project an additional US$100 billion in
2026. The shift in funding from
operating cash flow to debt issuance is the signal. When the cash flow runs out and the debt
begins, the question of return on investment becomes urgent. US$8 trillion in AI capital expenditure would
require US$800 billion in profit just to cover interest — before returning a
cent of principal. The AI infrastructure
supply reportedly grew more than 1,000 per cent between 2024 and 2025. Rapidly advancing model capabilities mean
that the data centre built today could be partially obsolete within five years. Moody’s has warned of overbuild risk. Bank of America has warned of the air
pocket. The concern is structural:
hyperscalers are committing capital at a scale that assumes monetisation will
arrive before the debt service becomes a crisis. That assumption has not been tested.
Singapore’s
Real Challenge: Riding the Correction
If
the AI debt cliff arrives — when hyperscaler capital expenditure normalises,
when the overbuild is acknowledged, when the debt issuance pace reverses —
Singapore will feel it. The construction
sector will slow. Data centre demand
will soften. Financial services revenue
linked to technology investment will contract.
The semiconductor cycle, already subject to its own inventory swings,
will interact with AI capex cuts in ways that are difficult to predict.
This
is not a reason for pessimism. It is a
reason for preparation. Singapore has
navigated structural economic transitions before from entrepĂ´t to
manufacturing, from manufacturing to financial services, from financial
services to the knowledge economy. The
institutional capacity for long-range planning exists. The question is whether it is being applied
to the AI transition with the same rigour it was applied to earlier ones.
The
specific risks are three. First,
concentration: an economy that has oriented significant capacity toward AI
infrastructure is exposed if AI capital expenditure corrects. Diversification within the AI economy — not
just data centres and chips, but AI-driven professional services, biomedical
AI, financial AI — reduces that exposure.
Second, talent: the AI transition requires a workforce that can operate
and extend AI systems, not merely consume them.
Singapore’s education and training pipeline must produce that workforce
faster than the transition demands it.
Third, sovereign positioning: the hyperscalers that built Singapore’s
data centres will make capital allocation decisions in San Jose, not in
Singapore. The MAS and the Economic
Development Board need contingency plans for the scenario in which that capital
moves.
The
Assessment
Core
inflation at 1.6 per cent is not a concern.
It is a rounding error on an economy growing at 5.4 per cent. The Hormuz disruption is a real cost and a
real irritant, but it will end. Energy
prices are driven by bullets and diplomacy, not by structural economic failure. The question is whether Singapore can
position itself to benefit from — rather than be disrupted by — the AI
investment correction.
Singapore
has the institutions, the reserves, and the track record to make the
transition. Whether it makes it well
depends on decisions being taken now: in the EDB, in the MAS, in the
universities, and in the boardrooms of the companies that have made Singapore
their regional headquarters. Inflation
is not the problem. Inflation is the
smoke. Watch the fire.
Terence
Nunis | Executive Chairman, Equinox Zenith | Author, The 1% Playbook: The
Billionaire Cheat Code




