The coverage of IMDA’s new report all led with the same two numbers: 19.3 per cent of GDP, and tech workers earning 60 per cent more than the median. Both are true and neither one changed a decision for me. The number that did is two lines further down the employment section, it is unglamorous, and it explains something that had been quietly costing us candidates for the better part of a year.
What the Report Actually Says
The Singapore Digital Economy (SGDE) Report 2026, published by the Infocomm Media Development Authority, was reported on in the first week of October 2026. OpenGov Asia covered it on 5 October and Techgoondu on 7 October, with consistent figures. The headline set:
| Measure | 2025 | Change |
|---|---|---|
| Digital economy, nominal value added | S$144.1 billion | 19.3% of GDP, from 18.8% |
| Information & communications sector | S$47.1 billion | +6.1% year on year |
| Non-I&C sectors | about S$97 billion | +3.6% year on year |
| Tech employment | 222,200 | +3.8% year on year |
| Median monthly tech wage | S$8,000 | about 60% above the S$5,000 resident median |
| Postings needing an AI skill | 16.7% | from 14.0% |
| SME AI adoption | 23.4% | from 14.5% |
| Large enterprise AI adoption | 70.4% | from 62.5% |
Non-I&C sectors contributed over two-thirds of the digital economy’s growth, and 96.4 per cent of enterprises reported at least one digital capability. Among enterprises that had adopted AI, 87.6 per cent cited productivity and process improvement as the benefit.
Signal 1: The Growth Is Outside the Tech Sector
Here is the line that matters. Tech employment grew 3.8 per cent overall. But employment in non-I&C sectors grew 5.3 per cent, while employment inside the information and communications sector itself grew 1.8 per cent.
Read that twice, because it inverts the mental model most of us hire with. The marginal engineering job in Singapore in 2025 was not created by a software company. It was created by a bank, an insurer, a logistics operator, a healthcare group or a manufacturer that decided it needed to build rather than buy. The tech sector is growing in value faster, at 6.1 per cent against 3.6 per cent, and adding people more slowly, which is a productivity story and also a competitive one.
For most of last year our sourcing, our compensation benchmark and our pitch were all calibrated against other software companies. We lost candidates we should have won and the post-mortems kept concluding “they paid more,” which was sometimes true and was not the mechanism. We were losing to employers we were not benchmarking against, offering things we were not talking about: scale of data, stability, a problem domain with real-world consequences, and in several cases a shorter path to owning a system outright.
Our Expert Take
If you are a software company hiring in Singapore, your competitor set is no longer mostly software companies, and the 5.3 versus 1.8 per cent split is the cleanest evidence of it we have seen published. Practical consequence: when you ask a candidate who else they are talking to and the answer is a bank, do not treat it as a weak competing offer. Treat it as the median case. Our close rate improved when we started preparing for that conversation specifically instead of assuming we were in a startup-versus-startup comparison.
Signal 2: The AI Skill Requirement Moved Slower Than the Noise
Job postings requiring at least one AI skill rose from 14.0 per cent to 16.7 per cent. That is a real increase and it is modest. If you have spent 2026 reading that AI has rewritten every engineering job description, this is the correction: roughly five in six Singapore tech postings still do not ask for an AI skill.
I find this genuinely useful as a calibration tool, in both directions. It argues against panic-rewriting every requisition to demand model experience you do not need, which inflates your band and shrinks your pool for no delivery benefit. It also argues against complacency, because a 2.7 point move in one year on a base that large is a lot of postings, and the direction is not ambiguous.
What we did with it: we audited our own open roles and found two where we had added AI requirements that nothing in the actual work justified. We took them out. Both filled faster. The skill we should have been screening for in one of those roles was not AI at all, it was data modelling, which had been crowded off the job description by a more fashionable requirement.
Signal 3: The SME Adoption Gap Is Wide and Closing Fast
SME AI adoption went from 14.5 per cent to 23.4 per cent in one year. Large enterprise adoption went from 62.5 per cent to 70.4 per cent. Separately, the share of organisations planning to adopt AI reached 12.1 per cent, up from 5.6 per cent in 2023.
Two readings, both correct. The gap between a smaller employer and a large one is still enormous, which means an SME that deploys something genuinely useful is still differentiated rather than merely compliant. And the rate of change is steep enough that the window has a shape: at nine points a year, “we will look at it next year” is a competitive decision rather than a neutral one.
The hiring implication is the one I would most like to argue with people about, because the intuitive move is wrong. The intuitive move is to open an AI engineer requisition. The better move, for most employers in that 23.4 per cent cohort, is to find the engineer already on your team who is using AI tooling well, give them explicit ownership of evaluation and enablement for one quarter, and hire only once you know which capability is actually missing. The report’s own finding supports this: 87.6 per cent of AI-adopting enterprises cited productivity and process improvement as the benefit. That is an internal-efficiency outcome, and it is reached with enablement far more often than with a new specialist headcount.
If the gap you find after that quarter is real and structural, preparing an existing engineering team for AI reskilling requirements is the cheaper half of the answer, and the national programmes do a lot of the funding work: we covered the scale of that in our piece on the National AI Impact Programme and its 100,000-worker target.
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Get 3 Free Developer ProposalsSignal 4: The S$8,000 Median Is Being Misread Everywhere
The median monthly tech wage of S$8,000, about 60 per cent above the S$5,000 resident median, was the most quoted figure in the coverage and it is the easiest one to misuse.
It is a median across all tech occupations and all seniorities. It includes support, infrastructure, QA and analyst roles alongside senior software engineering. Treating it as the going rate for a mid-level or senior developer will put you below market for exactly the roles you are most likely hiring. Treating it as a benchmark for a junior role will put you well above.
What it is good for: a sanity check on your overall band structure, and evidence in a budget conversation that tech compensation in Singapore sits roughly 60 per cent above the general median, which is a useful thing to be able to show a finance team that has never had to fund an engineering org before. Build the actual bands from role-level and level-specific data. We set out the method in structuring developer compensation packages in Singapore.
Our Expert Take
An occupation-group median is a macro statistic, not a salary benchmark, and the difference costs real money in both directions. We have watched employers lose a senior candidate by anchoring an offer to S$8,000, and watched another overpay a junior by anchoring to the same number. If a figure covers every seniority in a profession, it cannot tell you what to pay any individual in it. Use it to argue for the budget envelope; use level-specific data to set the band inside it.
The Four Things We Changed
- Changed who we benchmark against. Our compensation and benefits comparison set now includes the non-tech employers who actually take our candidates, not just software companies. This moved two bands and explained a year of losses.
- Rewrote what the first call emphasises. When a candidate is also talking to a bank, the deciding factors are usually ownership scope, decision speed and what they will have built in eighteen months. We now lead with those instead of discovering them at offer stage.
- Audited AI requirements out of two requisitions. Both filled faster. One of them needed a data modelling screen, which the AI requirement had crowded out.
- Stopped promising an AI mandate we could not fund. The honest version, for a company in the 23.4 per cent cohort, is enablement ownership for a quarter. Selling a candidate a greenfield AI charter you have not resourced is how you create a twelve-month attrition problem.
None of the four is a salary increase, which is the point. A macro report cannot tell you what to pay. It can tell you that you are looking at the wrong half of the market, and this one did.
Two Caveats Worth Stating
These are 2025 figures published in late 2026. Official statistics lag, and a year is a long time in this market. The structural signal, growth concentrated outside the tech sector, is the kind of finding that persists across a year. The precise percentages are history.
“Tech employment” is a wider category than software engineering. The 222,200 figure covers tech occupations across the economy, so do not read it as a count of developers. The employment split between sectors is the usable part; the absolute number is context, and reading it as a developer population would overstate your available pool substantially. If you are building the pipeline side of this, building a skills-based hiring pipeline in Singapore is the operational companion to this analysis.
FAQ: The Singapore Digital Economy Report 2026
What are the headline figures in the Singapore Digital Economy Report 2026?
IMDA reported that Singapore’s digital economy reached S$144.1 billion in nominal value added in 2025, or 19.3 per cent of GDP, up from 18.8 per cent in 2024. The information and communications sector accounted for S$47.1 billion of that, growing 6.1 per cent year on year, while non-I&C sectors accounted for roughly S$97 billion, growing 3.6 per cent. Tech employment reached 222,200 in 2025, up 3.8 per cent year on year, and the median monthly wage for a tech worker was S$8,000, about 60 per cent above the overall resident median of S$5,000. On adoption, 96.4 per cent of enterprises reported at least one digital capability, SME AI adoption rose from 14.5 per cent to 23.4 per cent, and large enterprise AI adoption rose from 62.5 per cent to 70.4 per cent. Job postings requiring at least one AI skill rose from 14.0 per cent to 16.7 per cent.
Why does the non-I&C employment split matter more than the headline number?
Because it tells you who you are actually bidding against for engineers. Tech employment grew 3.8 per cent overall, but that growth was not evenly distributed: employment in non-I&C sectors grew 5.3 per cent while employment inside the information and communications sector itself grew only 1.8 per cent. In other words, the marginal engineering job in Singapore in 2025 was created by a bank, an insurer, a logistics operator, a healthcare group or a manufacturer, not by a software company. If your sourcing strategy, your compensation benchmark and your employer brand are all calibrated against other tech companies, you are calibrated against the slower-growing half of the market and you will be repeatedly surprised by who takes your candidates. We were, for most of a year, and the fix was not paying more. It was changing who we benchmarked against and what we emphasised in the first conversation.
Does the S$8,000 median tech wage mean we have to pay more?
Not directly, and treating it as a target is the most common misuse of this figure. S$8,000 is the median monthly wage across all tech occupations and all seniorities in Singapore, which includes support, infrastructure, QA and analyst roles alongside senior software engineering. Reading it as the market rate for a mid-level or senior developer will put you below market for the roles you are probably hiring, while reading it as a benchmark for a junior role will put you well above. Use it the way it is meant to be used: as a sanity check on your overall band structure and as evidence in a budget conversation that tech compensation sits roughly 60 per cent above the general resident median. Then build your actual bands from role-level and level-specific data, because the premium that matters to a candidate is the one attached to their specific level, not to the occupation group.
What should a smaller Singapore employer do with the SME AI adoption jump?
SME AI adoption rising from 14.5 per cent to 23.4 per cent in a single year, against 70.4 per cent among large enterprises, says two useful things. First, the gap is still wide, so an SME that deploys something genuinely useful is still differentiated rather than late. Second, the adoption curve is steep enough that the window is closing: at that rate of change, being undecided for another two years is a competitive position rather than a neutral one. For hiring specifically, the practical move is not to open an AI engineer requisition. It is to identify which existing engineer on your team is already using AI tooling effectively, give that person explicit ownership of evaluation and enablement for a quarter, and only hire once you know which capability you are missing. The report also notes that 87.6 per cent of AI-adopting enterprises cited productivity and process improvement as the benefit, which is a strong hint that the first win is internal rather than in the product.
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Tell us the roles you are hiring and the sectors your candidates keep choosing instead. We will recalibrate the band and the pitch with you, then shortlist against it. Full-stack developers | Building data analytics in Singapore
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Sources: Infocomm Media Development Authority, Singapore Digital Economy (SGDE) Report 2026, as reported by OpenGov Asia on 5 October 2026 and Techgoondu on 7 October 2026, for the S$144.1 billion value added, the 19.3 per cent GDP share up from 18.8 per cent, the S$47.1 billion information and communications sector figure and its 6.1 per cent growth, the non-I&C figure and its 3.6 per cent growth, tech employment of 222,200 and 3.8 per cent growth, the 5.3 per cent and 1.8 per cent employment splits, the S$8,000 median monthly tech wage against a S$5,000 resident median, AI skill postings moving from 14.0 to 16.7 per cent, SME adoption from 14.5 to 23.4 per cent, large enterprise adoption from 62.5 to 70.4 per cent, 96.4 per cent of enterprises with at least one digital capability and the 87.6 per cent productivity finding. All figures describe 2025 and were published in 2026. The interpretation, the four signals and the changes described are our own view based on the roles we recruit for in this market.