Exploring how artificial intelligence is changing the role of analytics, from helping organisations understand data to actively supporting what they do next.
Artificial intelligence is rapidly becoming part of the business intelligence landscape, but its real value extends well beyond adding another feature to a dashboard.
For years, analytics has helped organisations organise information, identify trends and understand performance. AI introduces a new layer: the ability to interact with data more naturally, identify important changes automatically and increasingly turn insights into practical action.
This represents an important evolution for modern analytics. The question is shifting from “What does our data tell us?” towards “What can we do with it?”
Making Analytics More Accessible
One of the most immediate impacts of AI is changing how people interact with business data.
Traditionally, answering a new business question could require building a report, creating a query or asking an analyst to investigate the data. Generative AI and natural language capabilities are beginning to reduce that barrier by allowing users to ask questions in everyday language and receive relevant insights without needing to understand the technical structure behind the data.
This has significant implications for organisations. Analytics can become accessible to a much broader group of employees, allowing operational teams, managers and executives to investigate information directly rather than relying exclusively on specialist resources.
The result is not the replacement of analysts, but a shift in where their expertise can create the most value: away from repetitive reporting and towards deeper analysis, governance and strategic decision support.
From Finding Insights to Surfacing Them Automatically
Traditional business intelligence generally relies on people knowing what they are looking for. A user opens a dashboard, reviews a KPI or investigates a particular trend.
AI-assisted analytics can take a more proactive role.
Modern analytics platforms can help detect anomalies, recognise patterns and surface changes that may require attention. Instead of relying on someone to notice that a metric has moved unexpectedly, analytics can help bring that change to the right person sooner.
This is particularly valuable as organisations manage increasingly large volumes of data. The objective is not to generate more information, but to help people identify what matters within it.
Used effectively, AI can shorten the distance between a change occurring in the business, someone understanding its significance, and a decision being made.
Turning Insights Into Business Applications
Perhaps the most significant development is the movement from AI-assisted analysis towards AI-assisted action.
The next generation of analytics platforms is beginning to combine data, AI, automation and application development within the same environment. This allows organisations to create tools that don’t simply show what is happening, but support the processes that follow.
Domo’s App Catalyst is one example of this evolution. Using natural language, organisations can describe a business application and use AI to accelerate the development of a working solution built around their governed data.
That could mean an executive briefing automatically generated from live operational information, an approval workflow designed to identify potential compliance issues, or an application that helps teams respond to changing business conditions.
It represents a significant shift: from building dashboards that inform decisions to building intelligent applications that help organisations execute them.
Trusted Data Remains the Foundation
As AI becomes more embedded in business intelligence, the quality and governance of organisational data become even more important.
AI can only provide useful business insights when it has access to reliable, relevant and appropriately governed information. Disconnected systems, inconsistent definitions and poor-quality data do not disappear when AI is introduced; in many cases, they become more visible.
For organisations considering enterprise AI, building a strong data foundation is therefore just as important as selecting the technology itself.
This is where modern analytics platforms have an important role to play. By connecting information across the organisation and establishing trusted, governed data, they create the foundation from which AI can deliver meaningful business value.
Looking Ahead
AI is changing what organisations can expect from business intelligence.
Analytics is moving beyond dashboards and historical reporting towards environments where people can interact with data naturally, discover important insights faster and build intelligent applications that support action.
Through Analytics360 and Domo’s modern analytics capabilities, organisations can begin exploring this next stage while keeping their own governed business data at the centre.
The opportunity isn’t simply to add AI to analytics. It’s to use AI to make analytics more useful, accessible and actionable.
Traditional BI tells you what happened. Analytics360 helps you decide what happens next.
Next in the Series
Why Connected Data Is the Foundation of Better Analytics
In Part 6, we’ll explore why AI, automation and real-time analytics depend on something much more fundamental: connected, trusted data, and why breaking down information silos is becoming a priority for modern organisations.
