5 AI trends transforming Consumer Goods in APAC
Artificial Intelligence (AI) is transforming the consumer goods industry across the APAC region, where diversity in consumer behavior, rapid digital adoption, and supply chain complexity present both challenges and opportunities. From personalization to predictive analytics, AI is helping brands unlock growth, improve efficiency, and deliver more relevant customer experiences.
Here are five key AI trends and practical tips for consumer goods companies in APAC to stay ahead of the curve.
1. Hyper-Personalization Across Channels
In APAC’s mobile-first markets, consumers expect tailored experiences across digital and physical touchpoints. AI enables brands to deliver personalized product recommendations, dynamic pricing, and targeted promotions based on real-time behavior and preferences.
Start with foundational segmentation (e.g., RFM) and evolve toward next-best experience engines that adapt to individual customer journeys.
In APAC’s mobile-first markets, consumers increasingly expect seamless, tailored experiences across both digital and physical touchpoints. To meet these expectations, brands are moving beyond traditional personalization toward adaptive experience orchestration—a more dynamic, AI-driven approach that responds to real-time consumer behavior, preferences, and context. What sets this apart from earlier personalization efforts is the shift from static segmentation models to real-time, journey-aware engines. These systems don’t just segment customers—they learn and adapt continuously, offering the next-best action or experience based on live data inputs.
According to market studies, the role of technology in beauty is expanding, as consumers show growing interest in AI-based skin analysis and tailored cosmetic solutions (1). Amor pacific, South Korea’s largest beauty conglomerate, launched the AI Beauty Counselor (AIBC) using utilizing Open AI’s GPT-4 and Azure AI technologies. Unlike static recommendation engines, AIBC adapts to each user’s journey by analyzing purchase history, skin diagnostics, and chat interactions to provide personalized skincare. It mimics the in-store experience by offering tailored recommendations and follow-up support, driving higher engagement and conversion (2).
Tip: Shift from static personalization to adaptive experience orchestration.
Rather than relying solely on predefined customer segments, invest in AI systems that continuously learn and respond to individual journeys. This allows brands to deliver context-aware experiences that drive engagement, loyalty, and conversion.
2. Predictive Analytics for Demand and Inventory
AI-powered forecasting models are helping brands anticipate demand shifts with greater precision, especially in markets with high seasonality and regional variation. This leads to better inventory management and reduced waste.
Combine internal sales data with external signals—such as weather, holidays, and social media trends—to build robust predictive models.
Unilever has rolled out a cloud-based eB2B platform across six APAC markets to modernize its distributive trade operations. This system uses AI-powered forecasting models that draw on real-time data from retailers, distributors, and sales representatives to improve inventory planning and predict demand more accurately. By combining internal sales data with external factors such as weather patterns, holidays, and social media activity, the platform enables Unilever to anticipate shifts in consumer demand with high precision. In pilot programs, this approach led to a 98% on-shelf availability rate with partners like Walmart. It also helped reduce waste by minimizing unnecessary delivery trips and optimizing stock levels, resulting in lower excess inventory and transportation costs (3).
Ekimetrics recently helped two luxury watch brands leverage AI-powered predictive analytics to optimize product assortments across 3,000 retail locations. By analyzing historical sales data, local demand patterns, and store-specific dynamics, they were able to forecast inventory needs more accurately. This data-driven approach helped reduce overstock and understock situations, improve sell-through rates, and enhance customer satisfaction by ensuring the right products were available at the right locations (4).
Tip: Build smarter forecasting models by integrating diverse data sources.
To replicate Unilever’s success, brands should consider combining internal sales data with external signals—such as weather forecasts, holiday calendars, and social media trends—to build robust predictive models.
3. AI-Enhanced Product Innovation
Consumer goods companies are leveraging AI to analyze customer feedback, market trends, and competitor activity to inform product development. This is particularly valuable in fast-moving categories like snacks, beverages, and personal care.
Use methods such as Natural Language Processing (NLP) to extract insights from reviews, surveys, and social media.
Consumer goods companies are increasingly turning to AI to inform product development by analyzing customer feedback, market trends, and competitor activity. This is especially critical in fast-moving categories like snacks, beverages, and personal care, where consumer preferences shift rapidly and regional tastes vary widely.
Ai Palette, a Singapore-based AI startup, partners with consumer goods companies such as Nestle and Danone to optimize product development using real-time consumer insights. Their platform uses Natural Language Processing (NLP) and machine learning to analyze data from social media, reviews, blogs, and market reports across multiple languages and regions in APAC. Their platform identifies preferences, unmet needs, and emotional responses from millions of online conversations, while also forecasting emerging trends in flavors and packaging. These insights enable brands to refine existing products or develop new ones that align with regional tastes, resulting in faster time-to-market and improved product-market fit (5).
Tip: Use AI to accelerate and de-risk product innovation.
Rather than relying solely on traditional market research, brands should integrate AI tools that analyze real-time consumer conversations and forecast emerging trends. This enables faster iteration, better alignment with regional preferences, and more confident decision-making in product development.
4. Smart Retail Execution with AI driven solutions
In APAC’s fragmented retail environments, ensuring consistent in-store execution is a challenge. AI-powered tools such as image recognition help monitor shelf placement, pricing accuracy, promotional compliance and overall customer experience. Moreover, field teams are increasingly equipped with mobile-based computer vision apps that automate store audits and improve planogram compliance, ensuring products are displayed correctly and promotions are executed as planned.
Coles in Australia has introduced AI-powered smart shopping trolleys that streamline the in-store experience by eliminating the need for traditional checkouts. These trolleys automatically scan items as customers place them inside, track spending in real time, and offer personalized promotions through a built-in screen. By allowing shoppers to pack their bags as they go and pay directly through the trolley, Coles has created a faster, more convenient, and frictionless shopping journey. This innovation reflects a broader push in APAC retail toward integrating AI to enhance customer experience and operational efficiency (6).
Tip: Use AI to enhance in-store execution and streamline customer journeys.
To scale impact, brands should integrate these tools into daily operations and invest in training frontline teams to use them effectively. This not only improves execution but also builds a feedback loop between store-level insights and strategic decision-making.
5. Democratizing AI Across the Organization
To scale AI impact, consumer goods companies must embed analytics into daily decision-making across departments—from marketing and sales to supply chain and finance. As AI becomes more embedded in consumer goods operations, the next frontier is scaling its impact across the entire organization. This means moving beyond isolated use cases and ensuring that analytics and AI insights are part of daily decision-making—from marketing and sales to supply chain, finance, and product development.
To achieve this, companies must invest not only in technology but also in capabilities and culture. This includes:
- AI literacy programs to upskill teams and foster confidence in data-driven decision-making.
- Self-service dashboards that democratize access to insights, allowing non-technical users to explore data and act on it independently.
- Cross-functional collaboration to ensure AI tools are aligned with business goals and embedded into workflows.
Ekimetrics has supported APAC clients by building tailored dashboards and training programs that improve reporting efficiency and foster a data-driven culture.
Tip: Build AI fluency across teams to unlock enterprise-wide value.
Scaling AI impact isn’t just about deploying more models—it’s about empowering people. Invest in training, intuitive tools, and change management to ensure that AI becomes a natural part of how decisions are made every day.
Embracing the future of AI in consumer goods
Consumer goods companies that are ahead in digital transformation are already using data and AI to fuel efficient, profitable growth. How can brands catch up?
Start by focusing on the specific opportunities and challenges your business faces. Choose a manageable but impactful starting point, and clearly define what success looks like and how you’ll measure it. Build a solid data foundation by collecting and organizing what you have, identifying gaps, and ensuring it’s actionable. Then, develop a plan that combines the right technology with a thoughtful change management strategy. As AI continues to evolve, new capabilities will emerge—and staying adaptive is key to remaining competitive.
Sources :
1. South Korea’s Beauty & Cosmetics Market Overview2025 - KOISRA
2. How South Korea is building an AI-powered future foreveryone | The Microsoft Cloud Blog
3. AI and e-commerce tools transform emerging marketretail | Unilever
5. Singapore-based Ai Palette lands $4m to fuel global growth
6. Coles shows off AI-powered smart trolley for a smarter shopping experience | 7NEWS
