AI is scaling marketing. But is it scaling judgement?
A new report from IAA Singapore asks whether marketing’s rush to adopt artificial intelligence is improving the quality of decision-making, or simply helping organisations produce more, faster.
Marketing leaders no longer need convincing that artificial intelligence matters. According to Scaling Faster. Scaling Better?, the latest edition of IAA Singapore’s Insights series, 100% of CMOs believe AI is essential to the future of marketing. Yet 90% admit they are struggling to keep pace with change, while 63% do not believe their teams have the skills they need.
That gap between belief and confidence may be one of the defining leadership challenges of the next 12 months.
The report, drawn from Chatham House Rule conversations with more than 40 senior marketing leaders, suggests that access to AI is no longer the primary constraint. Tools are widely available, budgets are being found and experimentation is already under way. The harder question is whether organisations know how to use AI well.
Speed is only the first benefit
Much of the value marketers are seeing today comes from efficiency. AI can produce first drafts, adapt assets, synthesise research, generate variations and accelerate prototyping. Tasks that once consumed hours can now be completed in minutes.
These are meaningful gains, particularly for teams under pressure to deliver more without equivalent increases in resources. However, speed alone does not transform a marketing function.
The report warns that faster production can just as easily accelerate weak thinking, generic creative and poorly framed work. More output does not necessarily mean better performance, especially when teams have not agreed what quality looks like before the tools begin generating it.
This is one of the report’s central tensions: AI can remove friction from execution, but it can also make it easier to scale mediocrity.
The organisations making the strongest progress are therefore moving beyond isolated productivity tools. They are beginning to embed AI into workflows, decision rights, capability models and ways of working. That is where the harder work begins.
Human plus AI beats either extreme
The report finds that the strongest outcomes consistently come from combining human judgement with machine execution.
AI-only work can be brittle, predictable and detached from context. Human-only processes can be slower than the market now demands. The more effective model places people at the beginning and end of the process: humans frame the problem, AI accelerates the work, and humans interpret, edit and decide. This changes where marketing capability creates value.
As AI absorbs more drafting, formatting, synthesis and variation, distinctly human strengths become more important. The report identifies judgement, taste, problem framing, prioritisation, creative point of view, intent and agency as capabilities that organisations need to protect and sharpen. These qualities determine whether an output is merely plausible or genuinely right for the brand, customer and moment.
AI may be able to produce hundreds of options. Leadership still has to decide which option deserves investment, what risks are acceptable and what the work is ultimately intended to achieve.
The technology may be the easy part
One of the report’s most useful provocations is its division of AI implementation into the “25%” and the “75%”.
The technology, architecture and connective infrastructure represent roughly a quarter of the work. The remaining three quarters sit in people, culture, capability, workflows and decision rights. This explains why many AI programmes struggle after the initial excitement.
A company may licence several tools without retiring the processes those tools were meant to replace. A central transformation team may establish a strategy, while employees experimenting at the edges encounter bottlenecks and approval delays. Marketing may have ideas but lack ownership of the budget, governance or technical support needed to implement them.
The report argues that AI adoption should be treated as operating change rather than a technology rollout.
That means identifying real sources of friction before selecting tools, embedding AI within existing workflows and setting clear guardrails while allowing learning to spread across the organisation. It also means deciding what must remain human before convenience gradually makes that decision on the organisation’s behalf.
What happens to the next generation?
Perhaps the most important question in the report concerns junior roles. Many of the repetitive tasks now being automated were also the tasks through which people learned their craft. Drafting, researching, comparing, formatting and revising helped junior employees develop pattern recognition and judgement over time. Removing those roles may lower costs in the short term, but it could also remove the bottom rung of the capability ladder.
IAA Singapore’s report recommends redesigning junior positions rather than deleting them. The opportunity is to create AI-augmented apprenticeships in which younger team members learn faster through guided use of technology, while receiving the context, feedback and exposure required to build judgement.
This requires deliberate management. Juniors cannot develop taste or commercial judgement simply by supervising machine-generated outputs. They need opportunities to understand why decisions were made, challenge assumptions and see how work performs in the market.
The organisations that solve this well may gain more than efficiency. They may build a generation of marketers who are both technologically fluent and commercially stronger.
Scaling better
Scaling Faster. Scaling Better? is ultimately less concerned with which AI tools marketers choose than with the operating principles surrounding them.
It asks leaders to start with genuine business friction, define what good looks like, protect human agency and make experimentation part of everyday work. It also explores the areas where marketing is already making progress, including research, creative production, customer experience, prototyping, governance and visibility within AI-powered search.
The report does not offer a simple roadmap, because the right implementation will differ by organisation. Instead, it provides a set of tensions, anchors, warning signs and practical habits that leadership teams can use to assess whether AI is genuinely improving the work.
The speed gains are already available. The more consequential opportunity is to use that speed to improve judgement, creativity and commercial decision-making.
Download the full Scaling Faster. Scaling Better? report from IAA Singapore to explore the five shifts shaping AI adoption, the human capabilities organisations need to protect and the practical habits helping marketing teams scale with greater confidence.