ServiceNow published its Enterprise AI Maturity Index for Singapore in August 2026, and the headline is the kind that gets repeated without the second half attached: agentic AI adoption among Singapore enterprises more than doubled in a year, from 22% in 2025 to 51% in 2026. Singapore’s overall AI maturity score jumped 19 points to 53 out of 100, ahead of the global average of 51 and above the country’s own 2024 peak.
That’s the number that will show up in every slide deck quoting this report. It’s also the less interesting half of it.
Buried in the same release is the number that should worry a founder more than it seems to worry the market: of the 51% who’ve adopted agentic AI tools, only 10% have actually redesigned how work gets done, so that AI completes multi-step tasks end to end. The largest group, 33%, are using AI to help individual employees get through their existing tasks faster. Another 18% have made no real progress on advanced adoption at all, worse than the 11% global average.
Those are three very different companies wearing the same “we’ve adopted AI” label.
Assisting a task is not the same as redesigning a workflow
ServiceNow draws this distinction explicitly in the release: adoption and transformation are not the same thing. Giving someone a chatbot to speed up a task they already do is adoption. Rebuilding the process itself around what AI can now handle end to end is transformation. Most companies have done the first. Almost none have done the second.
The report also cites a finding from Singapore’s 2025 edition of the same index, not new data collected in 2026: enterprises that redesigned their processes around AI, rather than layering it on top, were nearly four times more likely to report significant productivity gains. It’s a year-old data point, resurfaced here to make the same case, but it’s still the clearest evidence available that the 10% aren’t just further along. They’re getting a structurally different return.
The one example ServiceNow gives is Standard Chartered’s redesign of colleague onboarding: mapping every step, deciding what genuinely needed a human and what didn’t, then rebuilding the roles and workflow around that split. Expected result is a 35% cut in hiring-manager effort and a 20% productivity gain across HR. Worth flagging that this is an HR process, not a marketing one. Nobody has published a marketing equivalent of that case study, and we’re not going to pretend the study said something it didn’t.
Why an agency retainer can’t get you into the 10%
This is our read, not ServiceNow’s, but it follows directly from what they measured.
Most marketing agencies are doing exactly what 33% of Singapore enterprises are doing: bolting an AI tool onto an unchanged workflow. Faster copy drafts. Faster first-pass creative. The account structure underneath, the briefing process, the approval chain, the reporting cadence, none of it has been rebuilt. It’s the same distance between client and work, just typed a bit quicker.
That’s not a criticism of effort. It’s a structural limit. Redesigning a workflow means deciding what genuinely needs a person and what a system can now handle end to end, then rebuilding the roles around that split, the way Standard Chartered did with onboarding. An agency has no commercial reason to do that. The redesign work isn’t billable inside a retainer, and if the redesign works, it shrinks the retainer. The incentive runs the wrong way.
Getting into that 10% requires being inside the business, with the standing to actually rebuild how the work moves, not adjacent to it with a mandate to produce more output faster.
The question this raises for anyone already using AI tools
If you’re a founder who’s already tried ChatGPT on a marketing task, or your team has some AI tool bolted onto the existing process, this data says something specific to you: having the tool isn’t where the return is. Most companies already have it. The study’s own framing is that the payoff sits on the far side of a workflow redesign, not in the tool itself.
We’re not going to put a number on what that redesign is worth for a marketing function specifically, because nobody has measured it, including us. What we can say is which side of that 10% line matters more than which tools are in use. That’s a fair question to ask of any AI vendor pitch, and of your own marketing setup: is this making the existing process faster, or has anyone actually redesigned the process itself?
Sources:
ServiceNow Enterprise AI Maturity Index — Singapore, press release, 17 August 2026: https://newsroom.servicenow.com/press-releases/details/2026/Singapore-Enterprise-AI-maturity-Index/default.aspx
Singapore Enterprise AI Maturity Index 2025 (data sheet, source of the “4x more likely” figure): https://www.servicenow.com/standard/data-sheet/singapore-enterprise-ai-maturity-index-2025.html
