The Monday morning shift: How conversational AI changes the daily rhythm of enterprise analytics

You log in, open up your messaging channel of choice, and find a series of ad-hoc requests: “Can I get this chart filtered by region?”, “Why did inventory drop in week 3?”, or “Can you modify this report layout for our afternoon meeting?”

Meanwhile, business managers spend their mornings clicking through static dashboards, trying to figure out which drop-down filter will explain why a key performance metric is off target.

With the release of the ibi^™ WebFOCUS^® Data & Analytics Platform version 9.3.8, we set out to fundamentally change that daily rhythm. The goal wasn't just to add an AI feature to a menu—it was to eliminate the small, daily points of friction that slow teams down.

Here is what the work looks like when a conversational AI assistant is built directly into your analytics workspace.

1. Authoring complex visual content in natural language

In a traditional workflow, when a department lead needs a new view of operational data, the process involves multiple handoffs: writing a ticket, waiting for a developer slot, explaining the business logic, and reviewing draft reports.

With the ibi AI Assistant in WebFOCUS, that iteration loop happens in seconds through natural conversation:

Traditional Workflow:

Business Question →  IT Ticket →  Queue Delay →  Spec Review →  Draft Approval

WebFOCUS 9.3.8 Workflow:

Business Question →  Conversational Prompt → Live Interactive Dashboard

Instead of filling out a form asking for the business analytics team to build a new version of a report, a user simply types what they are trying to understand—using everyday business terms rather than database field names. The assistant builds the visual canvas on the fly, assembling charts and applying formatting.

The business user gets immediate answers, and the data team's queue remains clear for strategic architectural projects.

2. Moving seamlessly from tracking trends to taking action

One of the most time-consuming parts of operational management is investigating an anomaly. When a manager sees a metric highlighted in red, their next step is usually a manual scavenger hunt: opening five different tabbed reports, cross-referencing dates, and guessing which variables caused the shift.

The AI Assistant shifts the experience from manual searching to guided diagnostic clarity.

When a metric variance appears, the assistant automatically runs secondary and tertiary background queries against the governed data source. Instead of making the user click through multiple drill-down layers, it presents the underlying explanation alongside the visual data:

• What shifted: The primary metric variance.

• The underlying drivers: Contextual factors, regional outliers, or supply chain bottlenecks identified in the background data.

• What to check next: Suggested operational follow-ups based on the data patterns.

It changes the user experience from looking at data to knowing what to do next.

3. Empowering IT with an embedded coding assistant

For data engineers and report developers, self-service tools have sometimes felt like a double-edged sword—offering agility for basic users, but leaving technical teams to clean up unoptimized queries or write complex procedural code by hand.

Inside the WebFOCUS development environment, the AI assistant functions as an active technical partner. For those not familiar with the underlying language, this assistant empowers them to reap the benefits of the robust data and analytics engine without extensive training. Regardless of skill level, the new AI assistant in WebFOCUS increases the velocity of deployment exponentially–allowing every user to do more and go further, faster. 

When building or refining complex reporting logic, developers can use natural language to draft FOCUS procedures, optimize database queries, or troubleshoot syntax errors in real time. Rather than replacing developer expertise, it acts as a co-pilot that handles the repetitive syntax construction, letting technical teams focus on data modeling, pipeline performance, and system security.

4. Maintaining total data trust at conversational speed

The real test of any AI tool in an enterprise environment is trust. If users aren't sure where the numbers came from, or if security teams are worried about data exposure, adoption stalls.

That is why the conversational experience in WebFOCUS 9.3.8 is anchored entirely in governed data lineage.

When the assistant generates a report or explains a variance, it doesn't operate as a black box. Technical users can inspect the generated query logic, view the underlying data sources, and verify the calculations. Because the assistant operates within the platform's role-based security framework, every user sees only the data they are authorized to access—ensuring that convenience never comes at the expense of enterprise governance.

A more fluid way to work with data

The ultimate value of conversational AI isn't found in a feature matrix, it's found in unlocking instant answers for business users while freeing technical teams to focus on strategic innovation.

By removing the syntax barrier for business consumers, automating diagnostic insights, and providing developers with a real-time coding partner, WebFOCUS 9.3.8 makes working with enterprise data a fluid, natural part of the workday.