The adoption of artificial intelligence in retail is delivering an unexpected dividend: data analysts, once buried in back-office tasks, are now driving strategic decisions across the sector. But according to new research, the full potential of AI is being throttled by outdated processes and legacy tools.
Alteryx’s 2025 State of Data Analysts in the Age of AI report reveals that 93 per cent of retail data analysts feel their role has become more strategically important over the past year. Nearly nine in ten say their job satisfaction has improved as a result of AI adoption, with 86 per cent citing analytics automation as a significant boost to their performance.
Far from being replaced by AI, retail analysts appear to be thriving because of it. Over half report that AI saves them time and enables them to focus on innovation and new ideas, while almost all see upskilling in AI and analytics automation as essential to long-term career growth.
Manual bottlenecks in an age of automation
Despite this optimism, the report highlights a structural issue that continues to hinder AI’s time-to-value: data preparation. Around 77 per cent of analysts are still using spreadsheets to clean and prepare data, a task that consumes between six to ten hours each week for 39 per cent of respondents. In the UK, this climbs even higher, with analysts spending an average of 11.29 hours per week managing data.
This reliance on manual tools is not just inefficient, it is strategically limiting. Nearly half of analysts say faster problem-solving is critical, yet the time lost to data wrangling reduces the agility needed to respond to customer expectations and shifting market conditions. The result is a paradox: analysts are closer than ever to the heart of business strategy but are being held back by tools better suited to a previous era.
Data complexity remains the single biggest challenge, cited by 51 per cent of respondents. Closely behind are data quality issues (46 per cent) and data privacy concerns (44 per cent). Over half of analysts say that integrating multiple data sources is a persistent problem, with four in ten identifying it as a critical barrier.
A strategic inflection point for retailers
The impact of AI is not limited to productivity gains. Retail analysts are increasingly seen as key contributors to financial planning, revenue generation and customer experience design. According to the report, 94 per cent say their work directly shapes strategic decisions, with 46 per cent stating it does so to a significant extent.
With nearly four in ten (39 per cent) describing the performance of AI in their work as exceeding expectations, there is growing awareness that the role of the analyst is evolving from task execution to strategic enablement. The majority now use AI for functions such as compliance, inventory management, and tax automation, with 37 per cent classifying themselves as experts in these applications.
Yet this evolution is being slowed by fragmentation in the data environment. Over three-quarters (78 per cent) of retail analysts report using between three and ten different tools for data preparation and analysis, and 69 per cent would prefer to consolidate their stack to just one to four platforms. The proliferation of disconnected tools increases complexity, cost, and cognitive load, undermining the very agility AI promises to deliver.
While PwC forecasts that retail technology spend will grow by 10 per cent annually until 2028, much of it driven by AI initiatives, the findings suggest that spend alone will not deliver transformation unless the underlying processes and systems are modernised.
The report concludes that AI is not a threat to data analysts, it is their strongest ally. But if retailers want to unlock its full power, they must first address the friction caused by legacy tools, fragmented platforms and time-intensive workflows. The analysts are ready. Now the infrastructure must catch up.
