Why AI won’t replace your Data and BI Analyst – and why that is a good thing

24 Mar 2025

With self-service BI and AI tools, more employees than ever have direct access to data and insights. They can build dashboards, generate reports, and ask AI for answers. So… does that mean analysts are becoming obsolete?

Absolutely not. In fact, in today’s data-driven world, skilled analysts are more essential than ever. They ensure data is used responsibly, insights are accurate, and – perhaps most importantly – the right questions are being asked.

The role of Data and BI Analysts

They ask the right questions and challenge the business

AI tools can analyze and visualize data, but they don’t validate whether the question being asked actually leads to meaningful insights. Analysts play a crucial role in this by challenging business users on their initial questioning. They help prevent incorrect assumptions from leading to misleading analysis and ensure that the focus is on the core of the problem.

Example

A marketing manager asks, “Which ad campaign performed the worst?” An AI tool might quickly deliver a report based on clicks and conversions. But a good analyst will push further: “Are we looking at absolute performance or return on investment?” “Have seasonal trends or competitor activity skewed the results?”

By asking these questions, the analyst discovers the broader context and avoids drawing one-sided conclusions.

They safeguard data integrity

Self-service BI empowers everyone to build their own analyses—but who ensures the data is accurate and interpreted correctly? Analysts are key to maintaining data quality and protecting against misinterpretation. They spot errors, biases, and inconsistencies, helping decision-makers avoid costly mistakes.

Example

A marketing team sees low conversion rates in a few regions and conclude the campaigns there have failed. They consider shifting budget elsewhere. An analyst steps in, reviews the data, and discovers that a recent change in how conversions are tracked has skewed the numbers. By catching the error, they prevent the business from making decisions based on flawed data.

They translate data into actionable advice

AI and BI tools can analyze data, detect trends, and flag anomalies, but without the right interpretation, insights remain meaningless. Analysts ensure that data is not only interpreted correctly, but also translated into concrete advice that aligns with business goals.

They not only help with the ‘what’, but especially with the ‘why’ and ‘what now?’. Through their knowledge of both data and organization, they provide strategic advice that goes beyond just a single analysis. This makes it easier for management and teams to make informed decisions.

Example

AI highlights that the product segment is underperforming, and customer satisfaction is declining. The analyst digs deeper and advises:
"The decline seems to be related to longer delivery times. We can invest in supply chain optimization or use temporary promotions to retain customers." In this way, an analyst ensures that data not only provides insight, but also leads to effective actions and strategic decisions.

Why Self-Service BI actually makes analysts more important

Self-service BI has transformed how organizations work with data, making it more accessible across departments. But with more people analyzing data, the need for analysts to provide guidance and oversight is greater than ever.

They ensure consistency: Analysts ensure that everyone in an organization uses standardized definitions and metrics. This prevents conflicting insights. With increased user autonomy, there is less control at the end of the data chain. A well-designed semantic layer helps keep data consistent and unambiguous, and that means more work for data engineers and analysts.
They foster a data-driven culture: Analysts help teams not only with analysis, but also with better understanding and using BI tools.
They elevate strategic decisions: Analysts combine data with business context to deliver deeper, more actionable insights than AI alone can provide.

AI and analysts: a powerful partnership

Rather than replacing analysts, AI and self-service BI enhance their work. Here is how the two complement each other:

AI handles the volume; analysts ensure relevance.

AI can analyze data and generate insights at lighting speed, but analysts ensure that the right data is used and that insights are aligned with the business context.
AI detects patterns; analysts catch the outliers.

Where AI follows rules, analysts recognize unique situations that fall outside the model.
AI speeds up the process; analysts focus on the strategy.

By automating routine tasks, AI frees up analysts to tackle more complex challenges and long-term planning.

For example, AI can identify patterns in customer behavior, but it is the analyst who advises how to translate those insights into a better customer experience or design a targeted marketing campaign.

Conclusion: In a data-driven world, people still matter

AI and self-service BI have made data more accessible and analysis more efficient. But no tool can replace human judgment. Analysts remain essential to ensure that data is used correctly, that insights are understandable and actionable, and that the organization makes the right decisions.

Put simply: AI may help bring the data to life, but it is the analyst who tells the story and ensures that it creates real business value. And that is exactly why analysts are more important than ever.

Want to know more?

Every dataset tells a story. At Orange Business, we help you bring those stories to life. Whether you need support designing dashboards, building data visualizations, or training your teams—we create solutions tailored to your challenges. Together we ensure that your organization has reliable insights that you can build on with confidence.

Curious about how self-service analytics or data visualization can work for your organization? Get in touch and let’s explore the possibilities.