Artificial Intelligence (AI), and Generative AI (GenAI) in particular, is steadily bringing about change in all sectors. The retail sectors are no exception, with AI bringing about changes both in business operations but also how consumers experience their products and services. The foundation of AI systems is to be able to draw new conclusions from the inputs they receive, in order to create new outputs. GenAI is particularly exciting as these new outputs open a world to generating new content, previously the reserve of human ingenuity. 

The prospect of being able to generate  new content, insights and personalised experiences in the retail space is particularly attractive, whether you are operating in the business-to-business (B2B) or business-to-consumer (B2C) space. As retailers integrate AI into their business strategies, they are realising quantifiable benefits, with many more on offer In this article we will dive further into this as we look at some of the real-world applications of AI in retail and what this means for businesses. 

Generative AI in retail: B2B and B2C applications

Generally when we think about the application of AI in business, we'll think about use cases designed to enhance or optimise existing processes or those that more radically transform the nature of an activity.  Specifically in the retail industry, GenAI has a variety of use cases to deliver these benefits,  which can influence both B2B and B2C interactions.

In both B2B and B2B contexts, GenAI can be employed to support businesses manage their operations better, with use cases such as supply chain optimisation, demand forecasting and inventory management. For example, using AI to optimise supply chains may lead to more accurate demand forecasts, resulting in more efficient decision-making and streamlining operations.

Specifically in B2C settings, GenAI can enable hyper-personalisation, driving tailored customer experiences based on individual consumer preferences and behaviours. This can include features such as personalised shopping recommendations, engaging and interactive product displays, and targeted marketing campaigns. Retailers using AI for personalised customer experiences have reported increased revenue growth, with this being a good example of the transformative power of AI. The benefits are clear and supported by an increasing weight of data in retail space, pointing to higher customer satisfaction and improved sales conversion rates when customers are browsing. In addition, retailers using AI-driven insights have reported to have seen improvements in search engine optimisation (SEO) and customer engagement and those using chatbots have reported improved satisfaction and reduced costs in combination.

Attitudes towards AI in the luxury retail market

Luxury brands also continue to explore GenAI, but with more caution than high street brands. While there is evidence that the technology can enhance supply chain management and demand forecasting, the incremental benefit may be more limited where supply chains are less complex and volume lower. There also appears to be a concern that over reliance on AI may compromise the "human touch" that is viewed by many as crucial in the luxury retail experience. In the long term luxury brands will be looking to find that balance between technological innovation alongside the preservation of brand authenticity and high-end customer experience.

Embedding AI into retail strategy

For retailers looking to adopt AI, a clear strategic approach to implementation is needed to maximise the benefits of new technology, but also to manage the risks. This involves making critical decisions such as what use cases will deliver most benefit and whether to develop AI solutions in-house or to partner with third-party providers. A successful AI strategy will identify clear performance indicators to track and measure the successes of AI initiatives for example by monitoring customer satisfaction scores and revenue growth.

Retailers should also consider the ethical and legal implications of AI use, both from a compliance perspective but also to promote trust in the use of AI. Existing law will apply to AI, creating a focus on regulated areas such as data privacy and security, and new laws such as the EU AI Act in Europe will more firmly regulate certain use cases associated with AI.   Risk needs to be examined through a fresh lens, for example would the use of AI with customer introduce the potential for bias in AI-generated content or recommendations, with dramatic reputational (and potentially financial) impacts for businesses? Also where previously "standard" contractual IP clauses and terms may have offered protection, more thought is now required when negotiating (or simply subscribing to) contracts for AI, catering for a technology stack that is different to traditional software and which could generate new content that businesses want to protect.  These are not necessarily all legal issues, an AI strategy needs to make space for ethical considerations as well, looking at the impact on suppliers, consumers and employees. 

How business will adapt to the AI challenge

Aside from legal and ethical scrutiny, GenAI adoption in retail will face other challenges. The reality is that retailers are likely to face hurdles such as a lack of IT preparedness, employee training needs, and cultural shifts within organisations. So strategy is important to realise return on investment for AI initiatives, but AI governance structures will be necessary to ensure that AI adoption is done responsibly. This may not only justify further investment in AI from a financial perspective but also ensure that the use of the technology is governed in a way that aligns with business risks, goals and consumer expectations.

In conclusion, this is an exciting time to be in retail, AI will play a monumental role in shaping retail businesses and consumer offerings. AI is already in the process of revolutionising the sector and lots of further opportunity remains. However, successful adoption requires a strategic approach and a clear AI-governance framework to responsibly harness the opportunities AI offers.