The global retail sector has had a traumatic five years, from COVID-19 and is now adjusting to the disruption that artificial intelligence (AI) brings.
Adoption of AI in the retail sector is growing, with approximately 87% of retailers already integrating AI into their operations, and the value of AI in retail, a modest $5.50 billion in 2022, projected to grow to $55.53 billion by 2030.
So it may be unsurprising that Microsoft and multi-national software company SAP are independently looking to enter the sector, unleashing a range of tools for SMBs and enterprises.
Is this a case of tech giants looking for new markets? Or, as they claim, helping lower the hurdles that retail must jump if they don’t want to be left behind in an AI-dominated sector?
This swift adoption of AI is fueled by the industry’s need to adapt to an increasingly digital and data-centric landscape, causing retailers to explore AI technologies that enable rapid learning and effective scaling.
Therefore, it is not surprising that tech behemoths Microsoft and SAP are rolling out AI solutions.
Last month, both tech giants announced new AI-driven capabilities for retailers, spanning from predictive planning to personalization, customer insights, data analysis, and generative AI models that can adapt to changing customer behavior, act as customer support, and create marketing campaigns on the fly.
Their intent is that if AI is a hurdle that retail must cross, it is a hurdle that has been lowered with simple tools rather than needing a specialist touch.
Microsoft’s AI Tools for the Retail Sector
Microsoft introduced new tools that aim to help retailers easily incorporate generative AI across the shopper journey, including new Microsoft Copilot capabilities in Microsoft products, Copilot templates for building applications, and retail data solutions in Microsoft Fabric.
These offerings are part of the Microsoft Cloud for Retail service, which connects customers, people, and data across the retail value chain.
Some of the new features that Microsoft announced include:
Copilot template for personalized shopping on Azure OpenAI Service:
This template enables retailers to build tailored shopping experiences that allow consumers to shop using natural language processing (NLP), similar to consulting with a shop attendant in a store. The template leverages the retailer’s current systems and data, as well as publicly available information, to offer personalized advice and expert recommendations.
Retail Media Creative Studio:
This is an end-to-end banner ad creative solution tailored for retail media, powered by generative AI, where retailers can create engaging and relevant ads that match the shopper’s intent and context, as well as optimize their ad performance and ROI, without needing in-house talent or outsourcing to an ad agency.
This capability adds generative AI via a large language model (LLM) assistant to facilitate interactions with store documentation.
From accessing operating procedures to creating tasks through natural language, this technology, according to Microsoft, is geared at enhancing workflow, and ensuring swift and efficient information retrieval in operations.
SAP’s AI-Driven Retail Capabilities
Similar to Microsoft, SAP’s new AI-driven capabilities are aimed at helping retailers optimize their business processes and drive profitability and customer loyalty, which they call the ‘intelligent customer experience’ strategy.
These capabilities, according to SAP, leverage the company’s embedded SAP Business AI technology to deliver end-to-end retail solutions.
Some of SAP’s new capabilities for retailers include:
SAP Predictive Demand Planning:
This offers retailers precise, long-term demand predictions by using a self-learning model that integrates various data sources like weather, events, and social media. It will also help in inventory optimization, waste reduction, and sales enhancement.
Predictive replenishment is aimed at optimizing inventory across the supply chain, considering demand fluctuations, business goals, and constraints to determine cost-effective order quantities.
Should Retail Implement AI in Their Stores, Marketing, and Supply Chain?
It is a double-edged sword for retailers: On the one hand, they can benefit from enhanced customer experience, operational efficiency, and potentially increased profitability. On the other hand, they will have to cope with the financial pressure that comes with adding these AI capabilities to their business processes.
Add to that the threat of being left behind if they don’t act.
Addressing the challenges, Tommi Vilkamo, Director of supply chains specialist RELEX Labs, told Techopedia that the challenges of AI adoption in retail go beyond the financial pressure.
He advised that while AI has the potential to permeate every fabric of business, retailers should be wary of investing in AI stretched beyond its capacity, and over-reliance on AI and AI-generated content.
“Retailers need to watch out for three major pitfalls as they adopt and invest in AI:
- The jagged-frontier issue of stretching AI beyond its capabilities, which damages productivity and customer experience;
- Becoming overreliant on AI output without enough human verification, leading to errors;
- The ‘elevator music’ effect: AI-generated content, though creative, can lack the uniqueness and soul of human-created content after a while.”
The existing retail landscape is bound to undergo a continuous transformation, and AI presents retailers with new shifting sands to make sense of.
However, the significant changes these tools bring are also laden with potential hazards, especially if the pace of adoption surpasses abilities or if the focus is excessively concentrated on cost-cutting at the expense of human necessities.
Given how close the retail sector is to the final consumer, the most rewarding approach to AI adoption is to integrate AI in a way that secures customer confidence and values employees.