What challenges did Telenor Norway face before AI implementation?

A legacy BI stack was expensive and increasingly inefficient to maintain. Data copying between disparate systems created silos and slowed decision-making. Business users had to file formal requests and wait for specialists to build dashboards, limiting agility.

What was the impact of the AI solution?

Reduced time-to-insight by shifting from centralized requests to self-service. Hundreds of employees in the consumer division use Looker dashboards with conversational features daily. Enabled production use with anonymized data. Improved insight-to-action loops for targeted campaigns.

Source

GCPEvidence: Low40/100

Telenor Norway: Conversational Analytics personal analyst grounded with LookML in Looker

Use case typeConversational analyticsUpdated 1 day ago

Telenor Norway, a telecommunications operator in Norway, moved from a centralized legacy BI model to self-service conversational analytics on Google Cloud. Using Looker and LookML, the company lets non-technical users ask questions in natural language, drill into audiences, and support targeted actions.

Organization: Telenor Norway
Industry: Tech & Comms
Location: Norway
Published: July 2026

Reported outcomes

Strategic outcomes

Employee experienceDemocratized advanced analytics across consumer value streamsBetter decisions & insightReduced time-to-insightCustomer experience & trustImproved insight-to-action loop for targeted campaigns

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Telenor Norway
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Stories

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Conversational analytics
2Decision support
3Workflow orchestration

A legacy BI stack was expensive and increasingly inefficient to maintain.
Data copying between disparate systems created silos and slowed decision-making.
Business users had to file formal requests and wait for specialists to build dashboards, limiting agility.

Adopted Looker as the analytics platform and used LookML semantic modeling to ground and govern AI responses.
Enabled conversational analytics as a “personal analyst” for non-technical users.
Explored workflows that push identified audiences into downstream tools for campaign execution.

Technologies

Looker LookML Conversational Analytics Google Cloud

Reduced time-to-insight by shifting from centralized requests to self-service.
Hundreds of employees in the consumer division use Looker dashboards with conversational features daily.
Enabled production use with anonymized data.
Improved insight-to-action loops for targeted campaigns.

Architecture

Telenor Norway adopted Looker and LookML on Google Cloud to ground conversational analytics responses in governed business logic. The workflow supports natural-language questioning, drill-down analysis, and downstream activation of audience segments.

Sources & evidence1

Evidence: Low40/100Evidence strength