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2. From information advantage to intelligence advantage
Traditional marketing strategy has long relied on information asymmetry. Firms
gained a competitive advantage through superior market research, strategic marketing
strategies comprising segmentation, targeting, and positioning, and consumer
insights. The emergence of big data accelerated this information advantage. However, AI
introduces a new paradigm: an intelligence advantage. Rather than merely collecting and
analysing data, AI systems can autonomously learn patterns, predict future behaviors, and
continuously adapt strategies in real time.
Huang and Rust (2021) conceptualise AI in marketing as comprising three levels:
mechanical AI (automation), thinking AI (data-driven analytics), and feeling AI (emotion
recognition and personalisation). The integration of these levels transforms marketing
from reactive communication to predictive orchestration. This shift has profound
implications for competitive positioning, organisational capabilities, and governance
structures.
3. Strategic opportunities in AI-driven marketing
3.1. Hyper-personalisation at scale
One of AI’s most significant contributions is the operationalisation of one-to-one
marketing. Through predictive modelling, machine learning algorithms, and behavioural
analytics, firms can deliver personalized recommendations, dynamic pricing strategies,
dynamic advertising content and individualized customer journeys.
Personalisation enhances customer satisfaction, increases engagement, and
improves conversion rates (Bleier & Eisenbeiss, 2015). In ASEAN markets, which are
characterised by mobile-first consumers and expanding e-commerce ecosystems. AI-
driven personalisation offers strong potential for SME growth and for expanding cross-
border trade. However, personalisation must be balanced with ethical safeguards.
Excessive predictive targeting risks infringing upon consumer autonomy and privacy.
3.2. AI-enhanced strategic decision-making
AI systems increasingly support managerial decisions in demand forecasting, media
optimisation, customer lifetime value prediction, and real-time experimentation. The
acceleration of decision cycles enhances operational efficiency and strategic
responsiveness. Lemon and Verhoef (2016) emphasize that data-driven customer
experience management is central to modern marketing performance. AI amplifies this
capability by enabling dynamic adjustments based on live behavioural signals.
For ASEAN countries, AI-enhanced decision systems can strengthen the SME’s
competitiveness, reduce marketing inefficiencies, and improve export readiness in global
markets. Nevertheless, reliance on algorithmic systems introduces accountability
challenges. Managers must understand model limitations, interpret output critically, and
ensure regulatory compliance.
3.3. Generative AI and creative transformation
The emergence of Generative AI has disrupted assumptions about creativity in
marketing. AI systems can now generate advertising copy, visual branding assets,
multilingual content, and even synthetic or artificial influencers. Rather than replacing
human creativity, AI augments it. Humans contribute to cultural intelligence, ethical
reasoning, and strategic vision, while AI provides speed, scalability, and pattern
recombination. In ASEAN countries, where linguistic and cultural diversity is high,
Generative AI can support localization strategies and enhance productivity in the creative

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