Generative artificial intelligence (Gen AI) is spurring organizations across different sectors to fundamentally reimagine their approach to digital transformation. Nowhere is its disruptive potential more evident than in retail, where Gen AI’s ever-increasing capabilities are powering a new age of customer-centric innovation.
Retailers are exploring use cases across a wide range of functions, from new product discovery and personalization to streamlined fulfilment and enhanced services. Everest Group’s Generative AI in CXM survey report, supported by WNS, revealed that 55 percent of enterprises view enabling personalization as a key driver of Gen AI adoption, while 16 percent are investing over $10 million toward Gen AI initiatives in the next 12 months to 18 months.
While many retailers remain at a crossroads, there's no doubt that Gen AI represents an indispensable opportunity for the sector. Whether organizations take a proactive, reactive or balanced approach, a look at the retail industry’s Gen AI journey so far can uncover the vast opportunities that remain, and the barriers that must be overcome to realize them.
Retailer Readiness for the Gen AI Revolution
For Gen AI solutions to deliver their full potential, organizations must seamlessly integrate them with domain expertise, industry-specific technologies, process knowledge, cutting-edge data analytics, AI capabilities, and innovative commercial strategies. This entails incorporating large language models (LLMs) alongside sector-specific AI/machine learning (ML) models and deploying them within the organization's specific industry.
When it comes to technology, a large swath of the sector seems ready to go. Key parameters include computing power (integral to complex Gen AI models), cloud-based infrastructure (to enable flexible deployment) and, crucially, scalable architecture that can handle ever-growing datasets and use cases.
As Everest Group’s research reveals, a majority of enterprises report readiness for Gen AI across these areas. Many retailers also show a strong performance in the fields of data privacy and security.
However, the absence of high-quality training data for Gen AI models — a vital prerequisite for meaningful insights and enhanced decision making — is a roadblock to adoption. Less than a third of the surveyed enterprises report internal preparedness in this area.
To overcome this hurdle and optimize Gen AI's capabilities, organizations must train their models on (preferably current) data that has been assessed for quality and structured appropriately. Retailers should deploy the models within curated data environments, ensuring robust and relevant data use for training.
Putting the right people in place can also help unlock Gen AI transformation. A broad range of technological talent and domain expertise is required to effectively model training, testing and validation, fuel cross-functional collaboration, and ensure compliance in a fast-changing regulatory landscape.
Building Next-Generation Retail Experiences
Getting this mix right will prove critical as retailers strive to remain competitive in a dynamic market. The prize on offer is transformational: this is already being confirmed by the incredible achievements of future-facing retailers in their Gen AI exploration.
We've seen retailers streamline logistics, tracking and tracing leakages through the technology while offering customers greater transparency. Others have enhanced customer service capabilities through Gen AI, providing instant, accurate and tailored responses to queries. Next-generation personalization is another example, with leading retailers leveraging data to deliver hyperpersonalized offers in real time.
As the space evolves, we expect these use cases to become increasingly experiential. Think real-time product co-creation with customers, Gen AI-powered shopping assistants that browse on behalf of shoppers, and in-store environments that seamlessly respond to individuals, offering unique and immersive retail experiences.
The Next Step Toward Transformation
Gen AI represents the predominant trend reshaping the world of retail. While transformative, the journey ahead will also prove complex as retailers work to make sense of an industry paradigm shift that fundamentally transcends conventional capabilities. The best route forward will involve investing strategically in Gen AI exploration through a combination of in-house development and collaborative partnerships.
Tapping into external expertise will allow retailers to augment their capabilities and navigate challenges end-to-end, from developing Gen AI road maps to customizing models. In fact, 62 percent of enterprises are seeking third-party providers’ support in building Gen AI solutions and enhancing technical capabilities. Such partnerships can ensure the full transformative potential of Gen AI is harnessed, significantly impacting immediate and long-term success.
Sanjay Jain is chief business transformation officer for WNS, a leading provider of global business process management (BPM) solutions.
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Sanjay Jain, Chief Business Transformation Officer, WNS
Sanjay Jain supports the organization and clients in large and transformative deals. He is a member of the 'WNS Executive Management Council,' and assists with the development and positioning of new capabilities and technologies. Prior to WNS, Sanjay was the founding partner of several technology start-ups. Sanjay holds an engineering degree in Electronics and Communication from Delhi University.