Data Analysts & Scientists: Surfing the AI Wave

Future-Proofing Your Career – a series exploring how AI reshapes specific professional roles.

This series empowers professionals to stay ahead of automation with the right skills, mindset, and tools. We cover career transitions, essential “future skills,” AI’s influence on roles like analytics, accounting, project management—and real stories of adaptation.

Artificial intelligence is already transforming the daily workflow of data analysts and scientists. AI-powered tools now automate repetitive tasks—making strategic thinking, experimentation, and business impact the true frontier of the role.

AI and Data Analysis

AI-Powered Automation: Efficiency Unleashed

According to Alteryx’s "2025 State of the Data Analyst" survey (1,400 respondents globally):

  • 97 % of analysts use AI-powered analytics platforms, and 87 % use analytics automation daily. Source
  • 70 % agree these tools improve their efficiency and effectiveness. Source
  • 76 % still rely on spreadsheets for data prep, and 45 % spend 6+ hours/week cleaning data. Source

AutoML, augmented analytics, and anomaly detection platforms now automate key tasks, including:

  • Data cleaning and preprocessing
  • Feature engineering
  • Anomaly detection
  • Model selection and hyperparameter tuning
  • Dashboard and report generation

The result: faster insights, fewer errors, and more time for strategic work.

The Evolving Role: From Executor to Advisor

Automation is reshaping the role. As noted in Alteryx findings:

  • 94 % of analysts say their work now influences organizational strategy. Source
  • 87 % report their role has become more strategic over the past year. Source
  • 86 % report increased job satisfaction after adopting AI tools. Source

Key new responsibilities include:

  • Framing high-impact business questions
  • Interpreting automated results and advising stakeholders
  • Designing and validating experiments
  • Guiding cross-functional decision-making with data insights

Essential Future Skills: Navigating the AI Landscape

  • AI/ML Tool Fluency: Confidently use AutoML, anomaly detection, and augmented analytics platforms.
  • Statistical Literacy: Understand sampling, bias mitigation, and validation.
  • Communication & Storytelling: Translate complex insights into business value.
  • Governance Awareness: Ensure data privacy, fairness, and transparency in AI models.

Opportunities & Risks: Balancing Automation with Oversight

  • Human Oversight: Analysts must validate AI outputs for errors and bias.
  • Data Quality Risk: Continued reliance on spreadsheets (76 %) undermines automation. Source
  • Ethical Concerns: Risk of biased or opaque models if oversight is lacking.

Industry Trends: Growing Demand for AI & Data Skills

The U.S. Bureau of Labor Statistics projects data scientist employment will grow by 34 % between 2024 and 2034—one of the fastest-growing roles, with about 23,400 openings annually. Source

Operations research analysts and related roles are expected to grow about 23 % over the same period. Source

Broader industry forecasts also confirm rapid growth across AI and data-driven roles as companies increasingly rely on analytics for decision-making. Source

Ready to Elevate Your Analytics Career?

If you want to leap ahead in your data career or embed AI into your analytics workflows, apply for RunWAI today.