About a year ago, I started noticing a pattern in how clients were briefing us. They don’t just come to us for deliverables anymore. They were coming with questions. Which AI tools should we be using? Should we be using them at all? What does a responsible AI-assisted creative process even look like?
I spent seven years in government service before founding CreativesAtWork 14 years ago. Across those two very different worlds, I have sat across from a lot of different kinds of clients. But this was new. They were not just buying a service. They were looking for someone to think alongside them — someone who understood both the craft and the tooling, and could help them make sense of a landscape moving faster than anyone expected.
That shift told me something important: the gap isn’t just between AI and creatives. It’s between what the market now expects and what our talent pipeline is actually producing.
What clients are actually asking for now
The ask has quietly changed. Clients today don’t just want execution. They want judgment. They want someone who can look at an AI-generated concept and tell them honestly whether it’s on-brand, culturally appropriate, or legally murky. They want a creative partner who knows when to use the tools and, just as importantly, when not to.
That is a fundamentally different profile from what most creative training — formal or informal — has historically built toward.
And yet the conversation in most education and training circles is still centred on outputs: learn the tools, build the portfolio, get the brief done. The advisory layer — the ability to help a client think through AI adoption in their own creative process — is barely on the curriculum and it should be.
Also Read: What to actually prioritise when your board wants AI and everything feels urgent
Where the pipeline is falling short
Across Southeast Asia’s creative economy, which includes a large and growing freelance workforce, this mismatch is structural. Universities producing design, communications, and media graduates are still largely running programmes built for a pre-generative-AI world.
Bootcamps have moved faster, but they are largely targeting engineers, marketers and tools-specific and focused. Few focused on the mindset shift and the design thinking process together with the client.
The freelance community is largely left to self-educate. Platforms like Coursera and LinkedIn Learning have added GenAI modules, but most of what exists treats AI as a feature to understand rather than a professional context to navigate.
What actually would help
Peer-led communities are filling the gap faster than institutions. Regional design communities, Discord servers, and creative Slack groups are where working freelancers are sharing real workflows, catching mistakes, and pressure-testing AI output against live briefs. The learning is messy and informal, but it is grounded in actual work, which is more than most formal programmes can say.
Agencies that have restructured around AI are also quietly becoming training grounds. When the workflow changes, junior people inside it develop judgment faster — because they are doing real work, not doing exercises. That will be increasingly important, and how a good creative training will work. The tools are new. The apprenticeship logic isn’t.
The structural barriers are slowing progress
Three things are holding this back at scale.
Curriculum cycles move too slowly. Degree programme updates will take a while. GenAI capabilities are shifting every six to twelve months. It needs to catch up faster.
Assessment needs to be caught up as well. It is still hard to tell whether someone can genuinely work well with AI or is just using it to cut corners. Without clearer signals of quality, the market will not be able to reward real capability development the way it should.
Also Read: Think with AI: The new skill for social entrepreneurs
And the freelance workforce has no institutional home. Salaried workers access employer-sponsored training. Freelancers largely is on their own. In Singapore, SkillsFuture credits help, but take-up among creative freelancers stays low — partly because the available courses aren’t yet matched to how creative AI work actually operates day to day.
What needs to change
I would think an actionable next step for creatives is to have an industry body to lead the development of a portable, competency-based credential for AI-assisted creative work — built with practising freelancers, not just academics. One that assesses judgment and workflow design, not just tool familiarity.
For business leaders, rewrite your briefs. If you need someone who can direct AI-assisted production and advise on which tools fit the project, say that clearly. Vague calls for “AI-literate creatives” produce vague results.
And for educators: spend time with freelancers who are actually doing this work. The curriculum you need already exists in practice. It just hasn’t been written down yet.
The creative economy has always run on a mix of formal training, peer learning, and hard-won experience. What’s changed is how fast the ground is moving underneath all three.
Twenty-one years across two very different sectors has taught me one thing consistently: the people who stay relevant are not the ones who master the tools best. They are the ones who never stop asking what the work is actually for. That skill no model generates. But we need to start teaching it now.
—
Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.
The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.
Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.
The post The creative gap: Why GenAI is outpacing the talent it was meant to empower appeared first on e27.