Once behind-the-scenes number crunchers, the role of the data analyst has evolved from a back-office function to a strategic business partner empowered by AI.
What does this shift mean for the future of analysts? For businesses?
As AI’s reliance on accurate data grows in importance, so does the importance of the data analyst. Not only can analysts accomplish more with AI, but businesses have an even greater reliance on analysts to power their AI technologies with reliable data.
But despite analysts’ rising importance, a burning question looms: Will AI eventually replace data analysts altogether?
We surveyed 1,400 professionals with roles in data preparation and business process improvement across the Americas, EMEA, and APAC to understand how data analysts are adapting to AI and analytics automation — including the challenges and opportunities this technological shift presents.
In this blog, we explore the key findings from our report.
AI and Automation: Putting the “Fun” Back in Data Functions
In the past year, data analysts have seen a wholesale adoption of AI (97%) and analytics automation (87%) tools. These technologies are helping data analysts do more faster — and with less stress, making analysts not only more productive but happier.
86% of analysts reported a boost in job satisfaction after implementing AI and analytics automation.
The reason? AI and analytics automation automate mundane, repetitive tasks and, in turn, help analysts focus more on strategic activities. Rather than manually collecting data from different spreadsheets and tech stacks only to spend hours manually cleansing and preparing that data, these technologies can automate those tasks, saving time, reducing errors, and making work more efficient — even fun.
Virtually all (98%) respondents reported saving time with AI, averaging 8.6 hours a week, more than a full day of focused work.
However, despite this newfound productivity and satisfaction, analysts still aren’t leveraging AI and analytics automation tools to their full potential.
Stuck in the Spreadsheet Trap: Why Analysts Are Still Losing Time
The more time analysts spend manually wrangling and preparing data, the greater the chance of mistakes — and burnout. Despite the widespread adoption of AI and automation, analysts still spend an average of 10–11 hours a week gathering and preparing data.
The biggest headache for analysts when preparing data is complexity, which topped the list at 51%, followed by data integrity, privacy, and security. As for integration, 38% of analysts struggle to merge data from different sources, with over half (55%) finding it difficult to combine multiple datasets.
Cleaning, organizing, and integrating this data takes time and effort, especially when systems don’t communicate well with each other. Part of these continued challenges and time drain is likely due to the tools analysts still rely on. While analysts are using AI, many (76%) still depend on legacy tools like spreadsheets for data cleansing and preparation.
From Behind-the-Scenes to the Main Stage
While the evolution of the data analyst role is still ongoing, analysts are nevertheless seeing a pivotal shift from back-office position to strategic business pillar.
Over the last year, data analysts have gone from operational support to key decision makers. In fact, 94% of analysts believe AI has enhanced their ability to influence strategy and business direction. This influence is only accelerating: 87% reported an increase in their role’s strategic importance over the past year.
What’s behind this shift?
First, data has been — and seemingly always will be — the lifeblood of organizations. Whether a retail company collects data about customer behavior or a telecom organization gathers insights from global marketing campaigns, the sheer volume and range of data means there are untapped insights simply waiting to be gleaned. Competitive advantage belongs to the most informed.
Second, our report showed that 86% of data analysts help their companies save money, improve efficiency, and guide spending decisions. Additionally, 84% contribute to revenue generation, 80% facilitate workforce planning, and 76% support mergers and acquisitions.
Data analysts today are far more than just number crunchers. Their role now includes strategic tasks, such as making predictions, streamlining operations, and personalizing customer journeys, helping businesses grow and perform better.
As one data scientist shared, “AI has transformed my role from being seen as primarily technical to being recognized as somewhat central to strategy and decision-making.”
AI as a Revolution, Not a Replacement
Finally, we asked the question on everyone’s minds: Could AI eventually replace data analysts altogether?
Some analysts are worried about job loss, legal issues, or the pressure to adapt quickly to new tools. Conversely, others see AI as a valuable technology to assist them, not replace them.
To understand the results of our survey, let’s first rewind a couple of years.
In our 2023 pulse survey, board members expressed concerns about generative AI, highlighting risks such as job displacement (49%), security issues (44%), and unaccountable processes (41%). Among those already using generative AI, challenges included over-reliance on the technology (30%), governance (23%), and data privacy concerns (23%).
Today, our research shows that while 17% of analysts are worried about job loss, the vast majority (83%) are cautiously optimistic. They believe AI needs human oversight to ensure accuracy and can improve efficiency without taking over their jobs entirely.
Sentiment has shifted. Perhaps irrevocably. Analysts now view AI as a career booster rather than a career buster. As AI continues to shape the future of data analytics, analysts are eagerly embracing these new tools.
AI as a Career Accelerant
One of the more considerable changes in the role of the data analyst is in workforce development. When it comes to upskilling, 90% of data analysts believe learning AI can help with career growth, and 88% see conquering automation tools as a way to boost their careers.
This is good news for organizations.
With the average hiring cost rising by 14% from 2019 to 2023, investing in AI training increases job satisfaction to effectively lower turnover and slash the expenses of recruiting and training new staff.
For data analysts, this means a chance to exponentially grow in their careers, stay updated with new trends, help their companies succeed, and, overall, focus on the parts of their jobs they love.
What’s next for data analysts?
As AI continues to evolve, so does the role of the data analyst. No longer confined to the back office, analysts have stepped into the spotlight as strategic business partners, driving decision-making, optimizing costs, and improving efficiency. The integration of AI and automation has made their work faster and more effective.
Despite concerns about AI replacing jobs, the overwhelming sentiment is that AI is an ally, not an adversary. Human oversight, critical thinking, and strategic interpretation remain irreplaceable.
Looking ahead, one thing is certain: AI is here to stay. And as its use cases and users expand, the role of the data analyst will only grow in importance — guiding businesses with the insights, expertise, and critical thinking that no algorithm can replace.
Read the full report to discover how the role of the data analyst has transformed in the age of AI.