Turning AI Adoption into Measurable Growth — Lessons from Regional Consumer Behaviour and Enterprise Maturity
Asnawi Jufrie, Vice President and General Manager of SleekFlow (Southeast Asia)
Across Southeast Asia (SEA), AI has rapidly shifted from buzzword to baseline. Consumers already rely on it at every step of the buying journey — comparing products, making decisions, and seeking support — while many businesses are still racing to keep up.
Adopting AI is no longer the hard part; turning it into measurable growth is. Efficiency alone will not close the gap.
Businesses now need an integrated approach that uses AI to build trust, personalise interactions, and drive revenue.
The key question is how companies can move from “catching up” to truly “staying competitive.”
The consumer reality: AI shapes every step of the buying process
SEA consumers have quietly become AI-native. In a mobile-first, chat-first region, people embrace any tool that removes friction.
Conversational commerce — buying directly through WhatsApp or social media DMs — has normalised informal, immediate, and highly personalised interactions.
In our recent AI Transformation in SEA whitepaper, based on responses from 1,100 consumers and more than 500 businesses across Singapore, Malaysia, and Indonesia, over 75% of SEA consumers said they were more likely to purchase when AI assistance was involved.
Consumers now treat AI like a hyper-convenient personal assistant. Younger, digital-native buyers expect instant replies, accurate information, and personalised guidance.
They do not care whether the interaction comes from a human or AI; they care about speed, clarity, and relevance.
In fact, our research shows that 84% of customers expect a response within five minutes or less.
In Southeast Asia, the buying journey isn’t just digital — it’s AI-driven. Speed wins customers now, and AI is the only way to deliver at scale.
AI maturity across SEA businesses
While consumers have adapted quickly, businesses across SEA display wide variation in AI readiness.
Some still view AI as an efficiency tool, while others already treat it as a growth engine.
Small and mid-market companies tend to move fast and experiment often, using AI for messaging, workflow automation, and basic lead qualification. But fragmented systems, unclear ownership, and limited resources prevent them from scaling these experiments into integrated workflows.
Large enterprises typically have the strongest infrastructure but the slowest deployment cycles.
Legacy systems, governance layers, and departmental silos often delay implementation despite strong intent.
Ultimately, maturity is not defined by company size but by integration. Many firms mistake having AI tools for having an AI strategy. Tools alone don’t move metrics.
Real transformation happens when AI is embedded into core business engines — sales, retention, and operations — turning isolated experiments into a cohesive system.
Barriers to effective AI adoption
Despite growing enthusiasm, meaningful AI deployment remains challenging. Security concerns, high costs, and limited AI literacy add friction to adoption.
The biggest obstacle is data fragmentation. Sales records sit in one system, inventory in another, and customer feedback in a third. Without a unified data foundation, AI cannot deliver personalisation or actionable insights. AI is only as powerful as the data behind it.
These challenges align with Boston Consulting Group’s ASPIRE framework, which ranks Indonesia and Malaysia in the top 50% globally for AI readiness.
Ambition is high, but investment and skills are still developing — creating a window for early movers to lead.
The hybrid workforce: Human + AI
Consumers are comfortable with AI for information and quick transactions. But when it comes to financial commitments, medical guidance, or complex complaints, human reassurance still matters.
Scepticism toward full automation remains strong across SEA markets.
The most successful companies don’t choose between AI and humans; they blend both. AI handles the volume — availability checks, updates, and FAQs. Humans provide value — empathy, negotiation, and complex judgment.
This hybrid model consistently lifts conversion and satisfaction because it mirrors real consumer behaviour: they want speed from AI and confidence from a human.
The next frontier is not replacing humans with AI — it is augmenting humans through AI.
The path forward: growth comes from orchestration
Measurable growth does not come from adopting AI tools in isolation.
It comes from orchestrating AI across the entire customer journey — from acquisition to conversion, retention to operations.
This shift has accelerated the rise of unified communication platforms like SleekFlow.
To close the gap between consumer enthusiasm and enterprise maturity, decision-makers should prioritise three actions:
1. Unify the Data Layer
Stop treating data as a departmental asset. For AI to work, sales data, inventory, and customer history must be synchronised. You cannot personalise a sale if your AI doesn’t know what’s in stock.
2. Define Metric-Driven Goals
Shift from vanity metrics like “chats handled” to business outcomes: higher conversion, lower churn, and increased average order value.
3. Empower the Middle Layer
The technology is ready — the people must be too. Upskill managers and frontline teams to work with AI agents, shifting their roles from execution to editing and strategy.
The window for early-mover advantage is closing. Nearly 68% of SEA businesses have already adopted AI agents or chatbots, and budgets for customer experience continue to rise.
In a region where digital competition is fierce and expectations evolve rapidly, AI is no longer the differentiator — the orchestration of AI is.
In Southeast Asia, that orchestration will separate the leaders from those who fall behind.
(JUN/RHZ/QOB)