AI AND INEQUALITY: CAN EDUCATION KEEP UP?
EXECUTIVE SUMMARY (ABSTRACT):
The rise of artificial intelligence has amplified global inequality across countries, firms, and individuals. Initially expected to boost productivity and promote equitable growth, AI has instead widened the technological divide between developed and developing nations and concentrated economic gains among a few global tech giants. Middle-class workers now face growing job insecurity, as automation threatens both skilled and routine roles. Education systems struggle to keep pace, often failing to equip individuals with the skills required in an AI-driven economy. To counter these disruptive effects, urgent reforms in education and targeted upskilling and reskilling policies are needed to ensure broader access to opportunities in the digital age.
EXECUTIVE SUMMARY (ABSTRACT):
This research investigates the role of digital resilience (DR) as dynamic capability in capital-intensive industries, particularly telecommunications, in recovering from successive economic shocks such as the 2016 oil price decline and the 2020 COVID-19 pandemic. The findings support the hypothesis that operators with advanced DR demonstrate superior financial and market performance post-shock. The study introduces a DR capability maturity framework, highlighting that mere digital infrastructure investment (Stage 1) is insufficient. Effective recovery begins at Stage 2 with internal operational excellence, while greater advantages are observed at Stages 3 and 4 with business model innovation and ecosystem integration. The research provides a conceptual framework for managers to monitor digital resilience progress capabilities, emphasizing the importance of achieving advanced digital maturity to outperform competitors after turbulence.
EXECUTIVE SUMMARY (ABSTRACT):
Scientists studied thoroughly the phenomenon of information and communication technologies impact on productivity. In 1987 Sollow summarized the puzzle with the well-known conclusion – “You can see the computer age everywhere but in the productivity statistics”. It took two decades for businesses to develop a so-called intangible capital concept composed of human, organizational capital, and new process knowledge needed to achieve effectiveness with ICT implementation. Recent advancements of digital technologies created a similar pattern issue with large investments into Artificial Intelligence, big data, and other technologies but very limited economic returns. The innovativeness of this paper is based on the analysis of 5 large-scale digitalization programs with AI as a leading tool that was expected to provide the largest return on investment. Key failure factors are analyzed that impeded the organizations to reach planned results and return on investments. Three factors were identified as primary obstacles for the success of comprehensive AI-based solution implementations – complexity, managerial capability, and compatibility.
EXECUTIVE SUMMARY:
In times of economic turmoil, businesses confront a crucial dilemma: should they prioritize ongoing investments or drive innovation? Conventional wisdom offers two paths: respond immediately to market demands or adopt a "wait and see" approach. But which one truly leads to resilience and success?
Current theories, broadly categorized as reactive market responses and passive observation, fall short in providing clear direction. Our research recently presented at the International Conference on Economics, Finance & Business, Prague explored how leading investments and business model innovation drive resilience, especially in capital-intensive sectors.
Key Findings:
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