Produce financial and market intelligence by querying data repositories and generating periodic reports. Devise methods for identifying data patterns and trends in available information sources.
17 of 17 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Manage timely flow of business intelligence information to users.
AI: Fully automatable - AI can fully automate the collection, processing, summarization, and timely distribution of BI (dashboards, alerts, reports) to users using pipelines and scheduling.
Collect business intelligence data from available industry reports, public information, field reports, or purchased sources.
AI: Fully automatable - As of 2025, ingestion pipelines (APIs, scraping, ETL, OCR/NLP on reports) can be fully automated given access and proper licensing.
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.
AI: Fully automatable - Automated reporting pipelines plus natural-language generation are capable of producing standard and custom executive-grade summaries with minimal human intervention.
Identify or monitor current and potential customers, using business intelligence tools.
AI: Fully automatable - Customer identification and monitoring are routinely automated via BI/CRM integrations, scoring models, and continuous alerting systems.
Maintain library of model documents, templates, or other reusable knowledge assets.
AI: Fully automatable - Cataloging, versioning, indexing and routine updates of document/template libraries can be fully automated with content-management systems and AI-assisted workflows.
Disseminate information regarding tools, reports, or metadata enhancements.
AI: Fully automatable - Dissemination (publishing reports, alerts, documentation and metadata notifications) can be fully automated through scheduled pipelines and notification systems.
Analyze competitive market strategies through analysis of related product, market, or share trends.
AI: Partial - AI can analyze market data and surface patterns and competitor moves, but full strategic analysis of competitive strategy requires human insight, proprietary context, and interpretation.
Synthesize current business intelligence or trend data to support recommendations for action.
AI: Partial - AI can synthesize BI and trend data and produce actionable recommendations, yet humans are typically needed to validate assumptions, risk tradeoffs, and make final decisions.
Communicate with customers, competitors, suppliers, professional organizations, or others to stay abreast of industry or business trends.
AI: Partial - AI can monitor, summarize, and conduct routine outreach, but relationship-building, nuanced negotiation, and trust-dependent communication remain primarily human responsibilities.
Identify and analyze industry or geographic trends with business strategy implications.
AI: Partial - AI can detect and quantify industry/geographic trends and surface implications, but translating those into strategic decisions still requires human judgment and contextual knowledge.
Analyze technology trends to identify markets for future product development or to improve sales of existing products.
AI: Partial - AI can analyze technology signals and propose market opportunities, yet selecting and validating product-direction choices typically needs domain expertise and business judgment.
Maintain or update business intelligence tools, databases, dashboards, systems, or methods.
AI: Partial - AI can automate routine updates, monitoring, and some fixes, but maintaining and updating BI tools/systems at the architectural and operational level still requires human engineers.
Create business intelligence tools or systems, including design of related databases, spreadsheets, or outputs.
AI: Partial - AI can generate prototypes, schema suggestions, and code for BI tools, but end-to-end design and integration of production-grade systems require experienced engineers.
Conduct or coordinate tests to ensure that intelligence is consistent with defined needs.
AI: Partial - Automated tests and validation checks are mature, yet defining acceptance criteria, handling ambiguous cases, and coordinating multidisciplinary tests need human oversight.
Document specifications for business intelligence or information technology reports, dashboards, or other outputs.
AI: Partial - AI can generate structured spec drafts from requirements and data schemas but still requires stakeholder validation and nuanced judgment to finalize them.
Create or review technical design documentation to ensure the accurate development of reporting solutions.
AI: Partial - AI can create and check technical design documentation for consistency and completeness but cannot fully guarantee implementation accuracy without domain testing and human oversight.
Provide technical support for existing reports, dashboards, or other tools.
AI: Partial - AI can diagnose many common report/dashboard issues and suggest or automate fixes, but complex, environment-specific troubleshooting and escalations still need human engineers.