UK retailers confront barriers to AI adoption, study finds
There's no denying that Artificial Intelligence (AI) is a hot topic across multiple industry sectors at the moment. Many UK businesses are keen to harness the potential benefits, specifically within the retail sector. However, fresh research from Fluent Commerce reveals that several significant barriers are preventing complete AI integration. In fact, only 27% of retailers are currently using AI/Machine Learning (ML) to augment their inventory and order processes, despite their projected development plans.
According to Fluent Commerce, a substantial 69% of retailers are planning to implement AI and ML technologies within the next 12 to 24 months. This emerging data indicates heightened awareness of AI's capabilities and its potential to revolutionise retail operations. However, there is a consensus among retailers that several substantial obstacles are impeding full AI/ML adoption. These difficulties range from the technical challenges of data preparation to talent deficiencies and a lack of organisational support.
From the research participants, 43% recognised that preparing retail data for AI/ML models presents a considerable complexity. As retail data is often spread across multiple systems not initially designed for AI training, this can severely complicate the data preparation process. A significant 41% of retailers also reported a lack of in-house AI/ML expertise as a significant barrier. Even with the increasing availability of dedicated courses, open-source models and AI-first vendors, the rapid pace of AI advancement demands consistent learning and adaptation.
Furthermore, the lack of executive backing was stated by 35% of respondents as a crucial challenge. However, this factor is expected to evolve as AI success stories proliferate and confidence in AI technologies solidifies. One critical aspect highlighted by the research was the gap in historical data, which is vital for predicting AI models. Only 40% of retailers have records of stock quantities at each location during order placement, and a mere 36% monitor stock allocations across sales channels. This deficiency in historical insight into inventory levels and the absence of order processing and delivery data presents formidable challenges to AI implementation.
Despite these hurdles, the immense potential benefits of AI for retailers cannot be ignored. The survey pointed to increased inventory returns, improved first-attempt delivery success rates, and reduced markdowns as the top benefits. Specifically, more than 62% of fashion and apparel retailers identified 'reducing out of stocks' as a core benefit. This highlights the influence AI has on operational efficiency and customer satisfaction.
Nicola Kinsella, SVP of Global Marketing at Fluent Commerce, commented on this, saying, "Utilising Predictive AI in retail, especially for enhancing backend operations, poses challenges but promises significant rewards. Retailers aiming to capitalise on AI must identify their target business issues and gather a robust dataset, ideally spanning 2-3 years, to effectively train AI models. By carefully selecting or developing AI models that align with their strategic goals, retailers can achieve a competitive advantage that translates into operational efficiency and improved customer satisfaction. The process requires effort, but the benefits – ranging from better inventory management to enhanced delivery success – are potentially highly significant."
