Before Leveraging AI Tools, Data Ecosystems Must Be AI-Ready

Retailers are eager to leverage artificial intelligence (AI) tools to take advantage of unstructured datasets. Unlocking the untapped potential of both structured and unstructured data through AI will help retailers build more meaningful relationships with consumers, boosting brand loyalty and creating more upsell opportunities while optimizing the shopping experience and driving greater product innovation. However, AI integrations can be complex, meaning retailers can’t plug new solutions into their data ecosystems without preparation.

The Data Estate

For a retailer’s data ecosystem to become “AI-ready,” it must first gather and organize its data into a central repository or a data estate, where critical customer data is secure and readily available for those who need it to make data-driven decisions. A comprehensive view of the data estate also helps retailers maximize their data to improve cost efficiency and competitiveness. Regrettably, many retailers don’t have a deep understanding of their data estate and data assets, making a complete view of the consumer unattainable.

Retail companies can better understand their data estate by working with a technology-enablement partner with solutions like a unified generative AI orchestration platform. As a secure, scalable and customizable AI workbench, this platform empowers retail brands to comprehend their data estate. Likewise, it enables retailers to streamline and enhance experimentation and development across large language models (LLMs), AI-driven business solutions, custom add-ons and, most relevantly, data stores.

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Enhancing Data Processing

Retailers’ data technology tools and platforms can usually only use simple, structured data (e.g., transactional information) and cannot use heavily unstructured data within day-to-day customer interactions. Although AI can make sense of unstructured data, retailers must first modernize their tech stack before AI can leverage these complex datasets.

Once AI fuses successfully with a retailer’s data ecosystem, it will become an inseparable component of that data platform, empowering brands to enhance data processing by finally taking advantage of large quantities of messy or unorganized data. For example, AI tools can gather data from multiple sources, organize it, resolve inconsistencies, remove duplicates and perform other necessary cleanup. Likewise, AI can streamline the processing of complex assets, such as legal documents, contracts, call center interactions, etc.

Data Governance Framework

Before retailers’ data ecosystems are AI-ready, they must also adopt new data governance tools, approaches and methodologies. For context, data governance frameworks are relatively new and primarily focused on traditional data assets. To elevate CX to the next level, retailers must use unstructured data like personally identifiable information (PII), emails, customer feedback, etc., which will require an updated data governance framework.

Additionally, retailers must ensure they use AI technologies responsibly and in a way that safeguards customer and proprietary data as new regulations emerge around principles and associated practices to help guide the design, use and deployment of automated systems, including data privacy. In the EU, the EU AI Act prohibits evaluating people based on their social behavior or personal traits; likewise, it forbids categorizing people based on their biometric data.

Getting Help to Become AI-Ready

To be truly AI-ready, retailers can work with a partner to better understand their data estate and improve data processing technologies. Ideally, a partner will have technical expertise across multiple, interconnected disciplines outside AI, like cloud, security, CX, etc., and will also recognize the importance of agility. Those retailers unsure if a partner is right for them should conduct an internal assessment to determine if they possess the requisite technical expertise.

Pierre Samec is senior vice president, enterprise AI solutions at EPAM Systems, Inc., a digital transformation services and product engineering company.