AI Will Make You 10X the Data Analyst, Not Take Your Job

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Read more about author Jon Reilly.

AI isn’t here to replace data analysts; it’s here to unlock their full potential and dramatically scale their work. With AI as their powerful ally, data analysts can unlock latent value in data and lead the charge in the fourth industrial revolution.

In a world where AI creates viral images and crafts hit music, it’s clear that we’re living in a time of rapid change. While some might worry about the implications of such developments, they also signal a promising new era for data analysts. Instead of being replaced by AI, data analysts are increasing their impact and gaining new skills.

Consider, for instance, that despite the presence of millions of industrial robots and a significant decline in manufacturing jobs, unemployment rates have remained at record lows. Earlier, the introduction of Excel wiped out some basic accounting and data entry jobs, but it also paved the way for countless new finance and analyst positions, enabling professionals to perform more complex tasks and deliver greater value to their organizations.

In fact, a study of census data over 140 years found that technology has undeniably created more jobs than it has destroyed, with job losses in fields like agriculture being offset by growth in fields such as caregiving, creativity, technology, and business services.

These examples illustrate that every new technology has the potential to replace low-impact, repetitive work with high-impact, strategic jobs, rather than simply eliminating people from the workforce. As we venture into the Fourth Industrial Revolution, AI is poised to create even more possibilities, particularly for data and business analysts.

A New Frontier for Data Analysts

AI is already transforming the way data analysts work, providing them with powerful tools to make their jobs more efficient, accurate, and valuable. Traditional data analysis tasks, like building models and creating data pipelines, were labor-intensive, resource-heavy, and time-consuming.

Historically, building a scalable model often required a team of data scientists and engineers working together for several months, iterating through various versions to find the best fit for the data.

Similarly, creating visually appealing charts and graphs required significant manual effort, involving hours of data manipulation, formatting, and design tweaking. Analysts often had to navigate complex software and work with designers to ensure that the final product effectively communicated their insights.

Today, AI-driven tools have dramatically streamlined these processes. Data preparation tools allow analysts to clean and prepare data more efficiently. By automating repetitive tasks and reducing the need for manual intervention, these tools empower analysts to focus on high-impact tasks such as analysis and decision-making. 

Visualization tools have integrated AI capabilities to suggest the best charts and graphs for any data, making it easier for analysts to effectively communicate their insights. With these AI-driven tools, creating visually compelling charts no longer requires extensive manual effort or collaboration with designers.

Another fascinating example of AI’s potential in the world of data analysis is the creation of a GPT-4 “Warren Buffett” financial analyst. This AI model was built to “chat” with users and analyze multiple PDF files, specifically Tesla 10-K annual reports from 2020 to 2022, making up over 1,000 pages. Another startup, Finchat, bills itself as “the ChatGPT for finance,” and is able to provide reasoning and sources for its conclusions. These solutions demonstrate how AI can enhance human capabilities by providing real-time, expert-level analysis of complex data sets. 

The Fourth Industrial Revolution: A Golden Age for Analysts

As Industry 4.0 unfolds, data analysts stand to benefit significantly from the AI-driven transformation of the enterprise landscape. With AI tools at their disposal, analysts can unlock the latent value in data, identify patterns and trends that were previously inaccessible, and lead the charge in driving business innovation.

Put simply, AI is not a threat to data analysts; rather, it’s an opportunity for them to become more valuable and integral to their organizations. By embracing AI and using it to enhance their skills, analysts can become irreplaceable parts of the organization in the rapidly changing world of technology and data.