ASEAN’s push to develop its creative economy is gaining policy momentum, but weak definitions and inconsistent data could make it difficult for governments to determine whether the sector is delivering the economic and social benefits expected of it.
At the 2025 ASEAN Summit, regional leaders adopted the Creative Economy Sustainability Framework, establishing a shared commitment to coordinated investment and development across areas including gaming, film and digital content. The move gives the creative economy a stronger regional policy mandate, but also exposes a fundamental measurement problem: ASEAN does not yet have a consistent way to define or measure the sector.
That gap matters because the creative economy encompasses activities ranging from music and publishing to design, gaming, film and crafts, with different countries and international organisations using different boundaries.
The Inter-American Development Bank estimated in 2013 that the global “orange economy” was worth US$4.3 trillion, equivalent to 6.1% of global GDP, and employed about 144 million people. In the same year, the United Nations Conference on Trade and Development (UNCTAD) estimated global trade in creative goods and services at US$624 billion.
More than a decade later, those figures continue to shape the narrative around creative industries, despite major changes in technology and consumption. The lack of updated, comparable measurements makes it difficult to determine how much the sector has actually grown and whether public policies designed to support it are working.
One problem is the absence of a common definition. Indonesia, for example, includes culinary arts in its creative-economy definition, while Thailand includes traditional medicine. The IADB identifies 45 industries, UNCTAD uses a broader framework covering 54 industries plus 21 industries involved in manufacturing creative goods, while UNESCO’s definition covers 37 industries.
ASEAN’s own 2025 framework acknowledges the lack of baseline definitions and metrics across the region.
That inconsistency affects everything from cross-country comparisons to assessments of policy outcomes. UNCTAD’s 2024 Creative Economy Outlook found the sector’s GDP contribution ranged from 0.5% to 7.3% across 36 reporting countries. Such a wide range may reflect genuine economic differences, but it can also reflect differences in what governments classify as creative activity.
Measurement is particularly difficult in areas such as crafts and traditional cultural expressions, where informal markets and tourism play important roles. Digital platforms, by contrast, provide much richer data for sectors such as music.
The distribution of economic gains is another unresolved issue. Spotify’s Loud & Clear data showed that fewer than 0.6% of more than 12 million artists uploading music in 2024 earned more than US$10,000 annually from the platform. On YouTube, the top 10% of creators received 62% of advertising payments in 2025, compared with 53% in 2023.
These figures illustrate why aggregate GDP and export numbers may not tell policymakers who actually benefits from creative-sector growth.
Technology is adding another measurement challenge. Generative AI is changing how creative work is produced, distributed and monetised, while existing statistical frameworks have not necessarily been designed to capture AI-generated output. The source article cites research showing freelance writing job postings fell 30% within eight months of ChatGPT’s release, highlighting how quickly technology can reshape creative labour markets.
Market Landscape
The creative economy increasingly overlaps with digital media, creator platforms, gaming, advertising, entertainment and AI-generated content. This makes accurate measurement more difficult because traditional industry classifications can struggle to separate creative activity from adjacent technology, tourism and digital services.
For ASEAN, the challenge is particularly significant because governments are considering coordinated investment while operating with different national definitions and statistical systems.
The source highlights several potential models. UNESCO’s 2025 Framework for Cultural Statistics represents an updated international measurement approach, while the UK’s use of defined industry codes offers a more disciplined way to separate creative activity from related sectors. Malaysia’s 2025 satellite cultural and creative account demonstrates that more detailed measurement can also be developed at the national level.
Strategic Outlook
ASEAN’s creative-economy ambitions will depend partly on whether policymakers can establish a common evidence base. Standardised definitions would make regional comparisons more meaningful, while updated methodologies could better capture digital platforms, creator economies and AI-assisted or AI-generated production.
Measurement should also move beyond GDP and exports. Median earnings, income distribution and employment outcomes could provide a clearer picture of whether creative-sector growth is producing broad-based economic opportunity.
Better data would also make government interventions easier to evaluate. Film incentives, grants and other creative-industry subsidies can involve significant public expenditure, making independent assessment of their economic returns important.
The broader opportunity remains substantial, but the policy question is shifting. ASEAN is no longer deciding whether the creative economy deserves attention; it increasingly needs to determine how to measure its actual impact.
Top Insights
- ASEAN’s creative-economy ambitions face a measurement problem because inconsistent definitions make regional comparisons, investment decisions and policy evaluation difficult.
- Digital platforms provide detailed creator and advertising data, while crafts and informal creative activity remain significantly harder for governments to measure.
- Income concentration across creator platforms suggests GDP growth alone cannot determine whether creative-economy expansion is producing broad-based economic opportunity.
- Generative AI is changing creative production rapidly, creating pressure for statistical frameworks to account for emerging forms of digital creative output.
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