Vol 4, No 1 (2025) |
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Managing Human Resources in Industry 4.0: Implications for Engineering Organizations
Pages 1-13 || Authors: Salman Salem Shinwary, Maimuna Tasnim Nusaiba, Ferdouse Ara Tuli, Raihana Sadia
ABSTRACT
This paper examines the widening gap between engineering organizations' lagging human resource frameworks and Industry 4.0's rapid adoption of technologies. Both identifying the new skills engineers need in this age of technology and investigating how traditional management structures are inadequate to support digital workflows were key objectives. The study synthesizes evidence on the relationship between automation and human capital through a qualitative review of secondary data collected over the past 10 years from industry reports and databases, including Scopus. Our key findings point to a hybridity gap in which success now requires a combination of soft skills, such as cognitive flexibility and digital fluency, rather than just technical skills. Additionally, we discovered that many engineering firms treat human resources as a secondary support function rather than a key strategic component of the 4.0 transition, leaving them trapped in a productivity paradox. To address the ethical implications of digital performance monitoring, policy considerations call for new labor laws and updated engineering curricula that cross organizational and technical silos. The study concludes that engineering leaders need to adopt a more decentralized, human-centered workforce model rather than a command-and-control mindset if Industry 4.0 is to fulfill its promise.
Key words:
Industry 4.0, Digital Transformation, Human Resource Management (HRM), Smart HRM 4.0, Smart HRM 4.0
Cite as:
Shinwary, S. S., Nusaiba, M. T., Tuli, F. A., Sadia, R. (2025). Managing Human Resources in Industry 4.0: Implications for Engineering Organizations. Silicon Valley Tech Review, 4(1), 1-13.
ABSTRACT
This paper examines the widening gap between engineering organizations' lagging human resource frameworks and Industry 4.0's rapid adoption of technologies. Both identifying the new skills engineers need in this age of technology and investigating how traditional management structures are inadequate to support digital workflows were key objectives. The study synthesizes evidence on the relationship between automation and human capital through a qualitative review of secondary data collected over the past 10 years from industry reports and databases, including Scopus. Our key findings point to a hybridity gap in which success now requires a combination of soft skills, such as cognitive flexibility and digital fluency, rather than just technical skills. Additionally, we discovered that many engineering firms treat human resources as a secondary support function rather than a key strategic component of the 4.0 transition, leaving them trapped in a productivity paradox. To address the ethical implications of digital performance monitoring, policy considerations call for new labor laws and updated engineering curricula that cross organizational and technical silos. The study concludes that engineering leaders need to adopt a more decentralized, human-centered workforce model rather than a command-and-control mindset if Industry 4.0 is to fulfill its promise.
Key words:
Industry 4.0, Digital Transformation, Human Resource Management (HRM), Smart HRM 4.0, Smart HRM 4.0
Cite as:
Shinwary, S. S., Nusaiba, M. T., Tuli, F. A., Sadia, R. (2025). Managing Human Resources in Industry 4.0: Implications for Engineering Organizations. Silicon Valley Tech Review, 4(1), 1-13.
The Agent-to-Agent (A2A) Protocol: The "HTTP" of the Agentic Web
Pages 14-16 || Authors: Saumya Aghera
ABSTRACT
As AI agents transition from research curiosities to production workloads, the industry faces a critical bottleneck: the lack of a universal communication standard. Currently, multi-agent systems rely on brittle, bespoke integrations that fail to scale. This paper evaluates the Agent-to-Agent (A2A) protocol, Google’s 2025 open standard, as the emerging 'HTTP of the AI age.' We break down A2A’s four-layer architecture, analyze its procedural JSON-RPC transport over traditional REST, and demonstrate how it composes with Anthropic’s Model Context Protocol (MCP) to create a modular agentic web. By shifting from point-to-point 'glue code' to a standardized orchestration layer, engineers can build heterogeneous pipelines that are natively interoperable across vendor boundaries. We conclude that A2A represents the foundational infrastructure necessary for the next decade of distributed reasoning systems.
Key words:
Agent-to-Agent Protocol, Multi-Agent Systems, LLM Orchestration, Agentic AI, JSON-RPC, Interoperability
Cite as:
Aghera, S. (2025). The Agent-to-Agent (A2A) Protocol: The "HTTP" of the Agentic Web. Silicon Valley Tech Review, 4(1), 14-16.
ABSTRACT
As AI agents transition from research curiosities to production workloads, the industry faces a critical bottleneck: the lack of a universal communication standard. Currently, multi-agent systems rely on brittle, bespoke integrations that fail to scale. This paper evaluates the Agent-to-Agent (A2A) protocol, Google’s 2025 open standard, as the emerging 'HTTP of the AI age.' We break down A2A’s four-layer architecture, analyze its procedural JSON-RPC transport over traditional REST, and demonstrate how it composes with Anthropic’s Model Context Protocol (MCP) to create a modular agentic web. By shifting from point-to-point 'glue code' to a standardized orchestration layer, engineers can build heterogeneous pipelines that are natively interoperable across vendor boundaries. We conclude that A2A represents the foundational infrastructure necessary for the next decade of distributed reasoning systems.
Key words:
Agent-to-Agent Protocol, Multi-Agent Systems, LLM Orchestration, Agentic AI, JSON-RPC, Interoperability
Cite as:
Aghera, S. (2025). The Agent-to-Agent (A2A) Protocol: The "HTTP" of the Agentic Web. Silicon Valley Tech Review, 4(1), 14-16.