A new report has highlighted eight key trends shaping the business intelligence market.
The Global Business Intelligence (BI) Solutions Industry Pulse: Q3 CY 2025 captures a pivotal moment in the evolution of business intelligence amid the growth of artificial intelligence (AI) driven automation, governance frameworks, and deeper ecosystem convergence.
Business intelligence vendors are moving beyond visualization toward AI-powered insight generation, embedding intelligence directly into business workflows and aligning business intelligence architectures with cloud-native, open data ecosystems, according to the report by AIM Research.
What is business intelligence?
Business intelligence describes the technology-driven processes and frameworks used to collect, integrate, analyze, and present business data. It aims to enable business leaders and employees to make informed decisions based on a clear and accessible view of organizational performance.
Business intelligence systems typically consist of several key layers including data collection and storage (often in data warehouses), data cleansing and integration, analytical engines, and visualization tools. These components work together to transform raw data into meaningful insights, which are then presented through dashboards, reports, and interactive interfaces.
What trends are shaping business intelligence?
AIM Research’s report reflects a turning point where business intelligence is no longer a passive reporting layer but a dynamic decision-enablement platform. Market direction reflects two key focus areas – democratization through natural language and copilots, and accountability through explainability, trust, and FinOps-led cost governance.
The report indicates that competitive advantage will increasingly hinge on how well business intelligence vendors blend innovation with enterprise control, scalability, and measurable business outcomes.
The eight trends shaping business intelligence are:
- AI copilots are becoming the norm in business intelligence. Conversational and guided analysis features are the new default across business intelligence tools.
- Trust, explainability, and governance take priority. Semantic layers, trust scores, and governed workflows anchor responsible AI adoption.
- Lakehouse-native business intelligence gains traction. Native support for open formats like Iceberg and Delta aligns business intelligence with modern lakehouse architectures.
- Embedded business intelligence is evolving into full data apps. Analytics is moving inside business workflows through writeback and embedded intelligence.
- Unified platforms and niche solutions reshape business intelligence strategy. The market is splitting between all-in-one analytics ecosystems and highly specialized, domain-specific tools.
- FinOps-driven cost optimization becomes central. Enterprises are embedding FinOps principles into business intelligence consumption and licensing models.
- Ecosystem alliances reshape the business intelligence stack. Partnerships between vendors, hyperscalers, and AI providers are accelerating integration and innovation.
- Self-service NLQ expands to broader user bases. Natural language querying is going mainstream, extending business intelligence access beyond analyst teams.