Will AI replace data analysts?

Updated

Data analysts score 65 of 100 for AI exposure. The largest share of their task time, 76%, is work AI speeds up while they stay in charge. AI can take over 19% outright, and 5% stays with people.

  • 19% AI can do it
  • 76% AI helps
  • 5% Needs a person
650100

High exposure

Higher than 96% of the 923 occupations we scored.

Task by task

We graded 17 tasks, listed here from most to least exposed. AI can do 3 of them today, speeds up 13 and leaves 1 to people.

TaskAI exposure
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders. LLMs and BI tools generate report drafts from data quickly.70% AI can do it
Disseminate information regarding tools, reports, or metadata enhancements. Drafting release notes and announcements is routine writing.65% AI can do it
Maintain library of model documents, templates, or other reusable knowledge assets. AI handles tagging, organizing, and retrieval of reusable templates.60% AI can do it
Document specifications for business intelligence or information technology reports, dashboards, or other outputs. AI drafts specs quickly, but requirements gathering needs stakeholder input.55% AI helps
Synthesize current business intelligence or trend data to support recommendations for action. AI summarizes trends well; recommendations need accountable human decisions.55% AI helps
Identify or monitor current and potential customers, using business intelligence tools. Segmentation and lead scoring tools automate much customer monitoring.55% AI helps
Create or review technical design documentation to ensure the accurate development of reporting solutions. AI drafts design documents well; technical accuracy needs expert review.55% AI helps
Manage timely flow of business intelligence information to users. Scheduled delivery automates much; coordination stays with people.50% AI helps
Provide technical support for existing reports, dashboards, or other tools. AI assistants can answer common report questions and troubleshoot issues.50% AI helps
Create business intelligence tools or systems, including design of related databases, spreadsheets, or outputs. Code assistants help write SQL, schemas, and dashboard logic.50% AI helps
Show the other 7 tasks
TaskAI exposure
Analyze competitive market strategies through analysis of related product, market, or share trends. AI speeds trend analysis; competitive interpretation stays with analysts.50% AI helps
Maintain or update business intelligence tools, databases, dashboards, systems, or methods. AI coding copilots speed up dashboard and database upkeep.45% AI helps
Identify and analyze industry or geographic trends with business strategy implications. AI synthesizes trend data well; strategic implications need human judgement.45% AI helps
Collect business intelligence data from available industry reports, public information, field reports, or purchased sources. AI handles document research; field reports need human collection.45% AI helps
Conduct or coordinate tests to ensure that intelligence is consistent with defined needs. AI generates test cases and validation checks; users confirm fit.45% AI helps
Analyze technology trends to identify markets for future product development or to improve sales of existing products. AI speeds tech trend scanning; market bets need human judgement.45% AI helps
Communicate with customers, competitors, suppliers, professional organizations, or others to stay abreast of industry or business trends. Live conversations with customers and peers need human relationships.22% Needs a person

See what AI can take on across a data team

How data analysts compare

All occupations (923)

Computer and mathematical (36)

Data analysts score 65, marked by the dark line. Each dot is a score, darker where more occupations share it. The short marks show the averages, 37 for all occupations and 60 for computer and mathematical.

Pay and outlook in the US

Median pay
$120,230 a year, May 2025
Projected change in jobs
+34.6% from 2024 to 2034

Skills to build

  • Write SQL queries against data warehouses in AWS or Azure
  • Build Tableau dashboards for executive review meetings
  • Run pattern and trend analysis in Python or R
  • Gather stakeholder requirements before writing dashboard specifications
  • Check AI-drafted reports against source data in Microsoft Excel
  • Present trend-based recommendations in PowerPoint with clear decision logic

Safer roles nearby

5 related occupations with lower scores.

Questions about data analysts and AI

Will data analysts be replaced by AI?

Partly. About 5 in 10 working hours go to tasks AI can already do, mostly drafting reports and disseminating findings. What stays with people is the stakeholder work of deciding which questions matter and standing behind the recommendations that come out of the numbers.

Will AI take over data analytics?

AI can already do 19% of the task time in data analytics and speeds up another 76%. People still do 5% of it.

Which tasks is AI taking over for data analysts?

AI is taking over report drafting and release notes first. Generating standard or custom reports scores 70 on exposure, and disseminating updates on tools and metadata scores 65, because LLMs and BI tools turn query results into draft summaries and announcements in seconds. Maintaining template libraries, at exposure 60, follows since tagging and retrieval are routine.

Which data analyst tasks stay with people?

Live conversations with customers, competitors, and suppliers score 22 on exposure, the lowest in this job. Trust built in person and insight picked up on a call come from people, so these conversations stay with analysts. Fully human tasks make up 5% of task weight, so most of the work will be shared with AI.

How can data analysts stay valuable as AI changes the job?

Check every AI-drafted report against source data in SQL before executives see it. Lead stakeholder requirement sessions, since AI drafts specifications quickly but needs your input on what the business actually asks for. Build Python or R pattern checks, and present trend recommendations in Tableau or PowerPoint with the decision logic spelled out.

Next steps for data analysts

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