Exponential progress in artificial intelligence (AI) and machine learning, fuelled by the combination of cloud, big data and new algorithms, is transforming the retail industry.
As AI leverages big data to automate, predict and personalise, retail is testing and implementing these applications to garner robust competitive advantages. The key focus for AI in retail is customer relationships.
In times of concerns for the retail sector in the UK where sales posted biggest quarterly fall since 2010, the refashioning of this industry comes as a breath of fresh air with many opportunities to come.
Global Artificial Intelligence Opportunities in Retail, 2017, new research from Frost & Sullivan’s Connected Industries Growth Partnership Service, offers an overview of AI and its relevance to business in 2017.
The study assesses the commercial viability and impact of retail applications for AI, either through integration with existing workflows or by creating new ones. It also explores strategies for navigating AI as a retail or information technology (IT) vendor, and the imperative for both to adopt a data-focused mind set. Key market participants include Amazon, Ocado, IBM and Softbank.
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“Improving and refocusing the customer experience online and offline must be the guiding principle for all retail businesses,” says Digital Transformation research analyst Vijay Michalik.
“Large tech-driven firms and retail tech startups are leading growth, particularly in e-commerce, and data network effects may mean that laggards never catch up. Older e-commerce and brick-and-mortar retailers must urgently adopt these technologies to regain their competitive footing.”
Retailers and tech industry players are investing in AI and creating opportunities that will disrupt incumbents. Emerging use cases include:
- Chat bots and virtual assistants: These AI tools of direct customer engagement allow for a seamless experience when ordering products. Chat bots have question-answer and recommendation capabilities that make it a highly scalable yet personal sales channel.
- Marketing and segmentation: AI models can use data sets to predict and prioritise the most successful campaigns and channels, and provide these insights to decision makers.
- Inventory and supply chain optimisation: In addition to increased accuracy and timeliness over traditional systems, AI tools can predict future supply-demand scenarios.
“In the AI age, data is digital gold and data inequality will prove a major battleground,” concluded Michalik. “Optimisation across all business functions will require an ever-growing pipeline of data collection that will demand new hardware, software and networking investments. The market must also pay attention to security requirements for AI and customer-analysis data collection.”
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