Getting Ready for AI Entrepreneurs of the Future: Linking AI Literacy & Entrepreneurial Readiness & Career Optimization

Glory Aguzman — Fri, 21 Aug 2026 00:00:00 +0800

The aim of this study is to investigate how future entrepreneurs build and mobilize AI literacy, exploring how these capabilities translate into entrepreneurial action readiness and ongoing career development. To examine this, the study employs a structured narrative literature review combined with abductive thematic synthesis. The analysis revealed that AI-related capabilities build entrepreneurial action readiness, which subsequently drives the continuous development and optimization of entrepreneurial careers through a blend of human-AI collaboration, critical evaluation, and experimentation. This research introduces notable originality by shifting the theoretical focus away from traditional entrepreneurial intention to position entrepreneurial readiness as a crucial intermediate step before action, while defining career optimization as a continuous, emerging process fueled by AI integration, experiential learning, and adaptive judgment.

Ask, and You Shall Receive: AI Answers and the Fragility of Platform Co-Creation

Jessica Wahyudi — Wed, 02 Sep 2026 00:00:00 +0800

This article analyzes how generative AI features (e.g., Google’s AI Overviews) shift search engines from multi-sided platforms that route traffic to publishers into closed systems that directly answer user queries. The text frames this transformation through a three-stage cycle: intermediation (routing traffic), disintermediation (answering directly on the search page), and reintermediation (reinserting the platform as an interpreter while relying on publisher content for raw data). This shift threatens traditional value co-creation by reducing publisher referral traffic, incentivizing low-quality content, and favoring algorithmically predictable prose. However, the paper also presents nuanced evidence: generative AI can expand total search demand, act as a discovery channel, and yield higher conversion rates for referred traffic. To maintain long-term ecosystem viability, the author argues that platforms must establish sustainable governance structures, such as API-level licensing frameworks, standardized machine-readable terms, transparent usage analytics, and multi-tiered compensation models (including pay-per-crawl, pay-per-citation, and pay-per-inference). Ultimately, the study concludes that long-term platform durability depends not merely on generative model performance, but on maintaining fair value co-creation with content complementors.

Journal of Business, Management, and Social Studies

Getting Ready for AI Entrepreneurs of the Future: Linking AI Literacy & Entrepreneurial Readiness & Career Optimization

Ask, and You Shall Receive: AI Answers and the Fragility of Platform Co-Creation