GenAI will soon write bulk of analytics reports, Gartner says

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Generative AI will automatically generate at least three-fourth of analytics content by 2027, up from just 10% in 2023, according to global research firm Gartner—a striking shift that shows how fast AI is reshaping business decision-making.

Firms are no longer using machines just to crunch numbers but to tell the story behind the data—clearer, faster, and more actionable than ever.

The idea behind the forecast is that generative AI tools—those that can produce text, summaries, explanations, or even visuals—will soon be embedded in most dashboards, reports, and business intelligence platforms.

Instead of raw charts and complex graphs, users will be presented with smart summaries and observations that help them grasp what’s happening, why it matters, and what they might do next.

Gartner referred to this as a move toward “contextual intelligence,” where the focus is not only on data but on the relevance of that data to each user’s goals.

Gartner analysts said the shift is happening because many companies find it hard to get value from traditional analytics.

Often, the data is there but not easily understood by those making decisions.

Managers may see trends in graphs but still be unsure what action to take. Generative AI changes that by adding natural language explanations, identifying possible causes or risks, and even suggesting responses—all based on the data being analyzed.

A common example would be a sales dashboard that not only shows a dip in revenue but also adds a note saying that three major clients reduced their orders and that this drop coincided with a price increase last quarter.

This kind of contextual insight can save time, reduce guesswork, and improve the quality of business decisions.

The technology is already finding early use in sectors such as retail, finance, healthcare, and logistics, where teams need to make fast decisions using complex data.

Gartner said the pace of adoption will accelerate as tools become easier to use and more accurate.

It expects that by 2027, most business users will interact with some form of generative AI when reviewing their analytics—whether that’s in the form of a written summary, an alert, or a question-and-answer interface that explains the data in real time.

Despite the excitement, Gartner also pointed to challenges.

Integrating genAI into analytics systems requires reliable data, strong security measures, and new forms of oversight to ensure that the AI isn’t introducing errors, biases, or misleading conclusions.

Companies will need to train employees not only to read AI-generated insights but also to question them and cross-check them when necessary. Governance will be key, especially as these tools are given more autonomy in shaping how information is interpreted and used.

To prepare for this shift, Gartner said businesses should review their current reports and dashboards and look for opportunities where generative AI could improve understanding.

It also suggested experimenting with pilot projects and ensuring that teams have the skills to work with AI-generated content responsibly. At the same time, organizations will need to develop clear rules for how data is used and how AI insights are checked before being acted upon.

While the timeline is short, Gartner said the benefits are too strong to ignore. By automating the creation of insights, companies can speed up decision-making, reduce dependency on analysts for every report, and make data more accessible to everyone—not just experts. This could lead to better performance, faster responses to market changes, and more informed strategy at every level of the business, the report added.