Data Analysts Gain Strategic Role as AI Reshapes Industry

Enterprise data analysts have embraced AI despite clinging to spreadsheets for core tasks, according to research that highlights a growing divide between traditional and automated workflows.

The findings from data analytics software provider Alteryx show 70% of analysts report productivity gains from AI tools, yet more than three-quarters still rely on Microsoft Excel and similar applications for data preparation.

This persistent dependence on manual processes threatens to undermine the benefits of automation, warns Alteryx, whose platform is used by 8,000 companies worldwide for data analytics and process improvement.

The company’s survey reveals that 45% spend over six hours weekly on basic data cleansing – time it says could be redirected to strategic work through automation.

Spreadsheets risk quality as AI adoption accelerates

The research, spanning five sectors including banking, insurance and manufacturing, points to a critical challenge facing enterprises. While AI promises enhanced efficiency, the continued use of manual data preparation methods introduces risk of errors that could compromise AI system outputs.

Data quality is a primary concern, with the reliance on spreadsheets creating potential bottlenecks in AI implementation, and the manual nature of spreadsheet work increasing the likelihood of errors that could subsequently propagate through automated systems.

Jay Henderson, Senior Vice President of Product at Alteryx, says: “For data analysts, the results are crystal clear. Leveraging AI as an everyday tool has boosted job satisfaction and reclaimed valuable hours for analysts.”

However, as Jay notes, organisations must address fundamental data preparation practices: “The challenge is to optimise these productivity gains. This involves building a tech stack to manage advanced AI applications effectively.”

Data roles shift despite traditional tools

The evolution of analysis work continues regardless of tool choice. The survey reveals 94% of respondents now influence strategic decisions, with 87% reporting increased business impact over the past year.

This transformation appears most pronounced in financial services, where regulatory requirements drive demand for both accuracy and efficiency. Manufacturing and retail sectors show similar trends as supply chain analytics grow in complexity.

The public sector and education organisations report comparable shifts, though adoption rates lag behind commercial sectors. The research indicates government agencies face unique challenges in modernising data practices while maintaining compliance requirements.

Analysts express confidence in AI era

Fear of job displacement through automation has largely subsided among data professionals. Only 17% of analysts express concern about AI replacing their roles – a marked contrast to IT leaders, where 65% anticipated generative AI would eliminate positions within three years.

The research indicates 90% believe AI will enhance rather than threaten their careers, with 48% expecting significant advancement opportunities through AI adoption.

The disparity between analyst optimism and leadership concerns suggests a disconnect in how different levels of organisations perceive AI's impact on workforce development.

Survey methodology included responses from workers responsible for data preparation and business process improvement across organisations with direct experience implementing AI solutions.

“Plans to implement AI across workforces must go hand in hand with providing data workers the tools that consistently validate confidence in AI outputs,” says Jay. “A strong starting point is determining whether your data preparation capabilities can meet these shifting demands.”

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