Digital Economy Analyst

What It Solves

Digital-economy discussions often stay at slogan level: AI, cloud computing, and industrial digitization are named, but the links between trends, policy, technology, and competitive structure remain unclear. digital-economy turns such questions into structured analysis tasks, useful for prompts about a specific industry's digitization trends, the core findings in a report, or the impact of a policy on digital-economy players. It does not promise real-time market data or official conclusions; it works from supplied materials and existing knowledge to produce structured judgments, risks, and actionable recommendations.

Capabilities and Workflow

The skill focuses on five areas:
- Trend analysis: growth points, technology evolution, and challenges.
- Report interpretation: extracting key claims from summaries and data instead of restating them.
- Technology forecasting: assessing the outlook for AI, blockchain, cloud computing, and big data.
- Policy assessment: analyzing impacts through compliance, cost, innovation, and competition.
- Competitive analysis: tracking industry structure and business-model changes.

The workflow is usually: clarify the question, collect information, apply a structured framework, generate insights, and draft the report. For deeper frameworks, use references/analysis-framework.md; for standard formatting, refer to references/report-template.md.

Boundaries

It is better suited to analysis and recommendation generation than to real-time pricing, authoritative statistics, or legal advice. Provide data, reports, policy text, or a clear industry scope when possible. Keep facts, inferences, and forecasts separate, and mark uncertainty. If the request is too broad, narrow it to a specific industry, time horizon, and focus area before expecting useful output.