Generative artificial intelligence is reshaping customer experience across industries, from streaming platforms to retail. While organizations are rapidly adopting AI to improve engagement and operational efficiency, leaders emphasize that governance, data readiness, and responsible deployment remain essential.
Streaming Platforms: Beyond Genre-Based Recommendations
Streaming platforms traditionally rely on genre-based recommendation engines. However, human preferences are more nuanced.
Sunil Rao, EVP and Head of Analytics for the Americas at Merkle, explained that one streaming platform used generative AI to analyze video content at a granular level, identifying “the emotions and actions, the themes and tones across a film or episode.” This deeper contextual understanding allowed the platform to match both content and advertisements to viewer preferences with greater precision.
Rao reported measurable impact: “We’re seeing a 21 percent improvement in ad performance and a 45 percent improvement in engagement rates.” These results suggest that AI can drive both commercial performance and viewer satisfaction.
AI in Retail: An Operational Multiplier
Retail organizations are also expanding AI adoption.
“I’m very bullish on AI,” said Vineet Mehta, General Manager of Enterprise Technology at Kmart and Target Australia. He described AI as an augmentation layer that enhances existing digital capabilities, calling it “an extra turbo mode on your engine.”
Kmart Australia has implemented AI-powered chatbots that handle approximately 30 percent of customer service calls without human intervention. In product design, AI combined with 3D tools enables rapid iteration. “We can change the colour on the fly now,” Mehta noted, emphasizing increased agility in private label development.
AI applications extend to physical stores, where robots collect real-time inventory data. The company is also exploring image recognition systems for loss prevention, identifying potential theft scenarios as they occur.
However, Mehta cautioned against careless implementation in customer-facing environments: “There’s very little margin between winning a customer and losing a customer.”
Governance and Risk: Proceeding with Discipline
While enthusiasm for AI remains high, industry leaders stress the importance of governance.
Navin Dhananjaya, Chief Solutions Officer at Merkle, underscored the need for measurable oversight. “We definitely need some quantifiable measures,” he said, referencing bias detection and model observability as critical components of responsible AI deployment.
He also highlighted emerging risks related to large language models, including prompt manipulation that could expose sensitive data or trigger unintended actions.
Data readiness presents another challenge. As Rao observed, “Having the right curated data in one place, integrated in a way where we can use that to feed these algorithms in a production capacity, has been a challenge.” Even mature organizations may require months to prepare their infrastructure for AI at scale.
India’s Expanding Role
The impact of AI extends beyond individual enterprises. India’s global capability centers are increasingly leading end-to-end AI initiatives. As Rao noted, “Most GCCs are doing it end-to-end. They are doing thought leadership, they’re driving innovation, they are the talent powerhouse, and they are building solutions.”
