AI in Paint Industry: From Shade Matching to Smart Recommendations

The Indian paint industry is undergoing one of its most transformative phases. Valued at $10.46 billion in FY25 and expected to reach $16.38 billion by 2030, it is propelled by urban housing demand, shorter repaint cycles, and a rising preference for eco-friendly paints. Yet, even as the market grows, the customer journey remains fragmented. Online research rarely translates smoothly into offline purchase, and dealers still operate with siloed systems that require customers to repeat themselves at every stage.

This is where Artificial Intelligence (AI) is beginning to redefine possibilities. From AI-driven shade matching that removes uncertainty in color selection to recommendation engines that personalise paint suggestions, AI is poised to close the gap between digital discovery and dealer engagement. For paint companies, it offers more than just tools - it creates the foundation of a seamless ecosystem that drives higher conversions, deeper loyalty, and greater efficiency.

Why AI Matters in Paint Industry

Paint is both a high-involvement and an anxiety-driven purchase. Homeowners often struggle to visualise how a chosen shade will look on their walls. Contractors rely on personal judgement, and dealers frequently push popular products rather than truly personalised options. These limitations result in hesitation, delays, or dissatisfaction post-purchase.

AI directly addresses these pain points. By analysing consumer behavior, browsing history, and contextual data, AI can recommend the right product faster and with higher accuracy. In a sector where urban repaint cycles have shortened to three to four years, the ability to deliver fast, personalised recommendations increases the likelihood of repeat sales and long-term loyalty. For brands, AI does not just improve customer experience - it becomes a growth driver embedded in the sales engine.

AI Use Cases in the Paint Industry

Shade Matching and Visualisation

One of the earliest and most visible applications of AI is in shade matching. Customers can upload photos of their rooms, and AI-powered algorithms instantly suggest the closest matching paint shades. This removes ambiguity from the selection process and instills confidence in the decision. Some systems go further by rendering virtual rooms in different shades, allowing homeowners to visualise before they buy.

For dealers, this technology is invaluable. Instead of relying on swatches or trial-and-error, they can demonstrate shades digitally and close sales faster. This improves customer satisfaction while reducing returns or repaint requests.

Smart Recommendations

AI-driven recommendation engines analyse both customer preferences and contextual factors - such as room type, lighting, location, and budget - to suggest the most suitable products. For example, a homeowner in Mumbai searching for an interior emulsion may receive a suggestion for a moisture-resistant, low-VOC paint tailored to coastal climates. In contrast, a Delhi customer may be offered dust-proof exterior finishes. By moving beyond generic upselling, AI ensures recommendations feel personalised, relevant, and trustworthy.

Dealer Routing and Lead Management

AI is not just for consumers; it also transforms how brands manage their dealer networks. The IRR highlights the role of AI orchestration in routing digital enquiries to the right dealer. Instead of manual follow-ups with incomplete context, AI ensures that a homeowner browsing waterproofing options online is instantly connected to the nearest dealer who has full visibility of that interaction. This reduces friction, accelerates conversions, and strengthens dealer confidence in digital channels.

Predictive Repaint Cycles

Another promising application is predictive analytics. By tracking purchase history, weather conditions, and emerging design trends, AI can anticipate when a customer is likely to repaint. For example, if a customer purchased an interior finish three years ago, AI can trigger timely reminders or promotions, routed through dealers, to capture repeat sales. This transforms paint from a one-off purchase into a recurring engagement cycle.

The Business Impact of AI in Paints

AI adoption translates directly into business outcomes. Research shows that personalised campaigns powered by AI deliver 5–8 times higher ROI than generic outreach. Paint companies that integrate AI into their dealer-consumer loop also reduce lost leads, shorten sales cycles, and improve brand loyalty.

For dealers, AI is equally transformative. Equipped with AI tools, they can respond faster, offer better advice, and convert more walk-ins into buyers. Instead of feeling sidelined by digital campaigns, dealers become central actors in delivering personalised, data-driven experiences. This alignment builds stronger trust between brands and their distribution partners.

Importantly, AI also strengthens eco-friendly positioning. With nearly 46% of revenues now coming from low-VOC, water-based paints, AI can nudge customers toward sustainable options by matching preferences with green products. This not only boosts margins but also reinforces premium positioning for brands that lead with sustainability.

Lessons from Industry Leaders and Challengers

Asian Paints has long been at the forefront of digital adoption. By building a connected ecosystem that integrates dealers, painters, and customers, it has laid the groundwork for AI-driven engagement. Its visualiser apps and dealer portals are early steps toward embedding AI into everyday interactions, ensuring a consistent experience across channels.

Challengers like Birla Opus are embedding AI from the ground up. Launched in 2024 with a ₹10,000 crore investment, the company is leveraging AI to orchestrate CRM systems and consumer engagement. Online leads are not only routed instantly to dealers but also accompanied by AI-generated insights about customer preferences. This empowers dealers to have more tailored conversations and build stronger relationships.

Similarly, JSW Paints has focused on rapid dealer expansion supported by modern IT systems. While its primary differentiator has been aggressive pricing and onboarding, the integration of AI-driven dealer management is expected to strengthen its long-term competitiveness. These examples show that whether a market leader or a new entrant, AI is quickly becoming the baseline for engaging dealers and customers alike.

From Fragmented Journeys to Connected Ecosystems

The IRR emphasises that shiny digital tools alone cannot fix a broken customer journey. Without integration, even the most sophisticated apps remain silos. AI becomes valuable only when embedded into a Business Operating System (BOS) that connects every stakeholder.

In a BOS-enabled ecosystem, AI ensures continuity. A customer who browses paints online enters their details once; that record flows through the CRM and is accessible to the dealer. AI analyses the data and routes the lead to the right dealer, who receives full context. Follow-ups - whether on WhatsApp, in-store, or via call centers - are logged centrally. The customer never repeats themselves, and the dealer feels empowered with actionable insights.

The result is not just smoother journeys but stronger financial outcomes. Companies that adopt AI-led omnichannel engagement strategies are already growing three times faster than laggards at 9-10% annually versus 3%. For paint companies, this demonstrates that AI is not just a technology play; it is a growth engine.

The Future of AI in Paint Industry

Looking ahead, AI’s role in paints will expand beyond shade matching and recommendations. As smart homes and IoT adoption grow, AI could integrate with devices to suggest repainting schedules based on humidity, pollution levels, or UV exposure. Augmented Reality (AR) tools powered by AI will deliver hyper-realistic visualisations, making it easier for customers to experiment with designs. AI chatbots will become first responders, handling enquiries 24/7 before routing them to dealers with context.

For paint brands, the challenge will be to ensure that AI strengthens, rather than replaces, dealer relations. The most successful models will be those that use AI to empower dealers - providing them with insights, leads, and tools that enhance their advisory role. This balance will be key to building loyalty and sustaining growth in a market where distribution remains dealer-led.

AI may be transforming shade choices into smart journeys, but what happens when paint websites fail to convert these ready customers? That’s exactly what we’ll uncover in the next article

FAQs

1. How is AI used in the paint industry?
AI is used for shade matching, smart product recommendations, predictive repaint cycles, and routing customer leads to the right dealers with full context.

2. Can AI really help me choose the right paint colour?
Yes. AI-powered visualisers allow you to upload room photos and see how different shades will look, reducing uncertainty and making selection easier.

3. How does AI benefit paint dealers?
AI equips dealers with insights into customer preferences, helps close sales faster, and routes digital enquiries directly to them, strengthening their role in the value chain.

4. Will AI make paint buying faster and easier for homeowners?
Absolutely. By analysing needs, location, lighting, and budgets, AI speeds up recommendations and ensures customers find the most suitable products quickly.

5. Which paint companies are currently using AI in India?
Leaders like Asian Paints, challengers like Birla Opus, and players like JSW Paints are already embedding AI in shade visualisation, dealer management, and CRM systems.