Rajashree Goswami
Rajashree Goswami is a professional technology writer with 13+ years of experience covering AI, cybersecurity, cloud computing, SaaS, fintech, regtech, healthtech, sustainable technology, digital transformation, and enterprise innovation. She also specializes in software and app analysis, emerging technologies, and enterprise technology trends. Her work is grounded in research and in-depth conversations with industry leaders, subject matter experts, and technology practitioners, with a focus on the business impact of technology on innovation, operational efficiency, growth, and ROI.
Articles by Rajashree Goswami
The Rise of the AI Generalist, and the Decline of the “Unicorn” Data Scientist
The AI generalist is no longer a fringe profile in enterprise hiring conversations. In boardrooms and sprint reviews alike, CTOs are quietly acknowledging what the market is signaling: the era of the unicorn data scientist is fading, and a more adaptive, cross-functional…
Artificial Intelligence Governance in the Age of Exponential Technology with Dr. Andrea Bonime-Blanc
AI and Tech Leadership This interview series is grounded in lived experience. It explores how technology leaders move AI from experimentation into day-to-day operations, where decisions carry real consequences for teams, customers, and the business. Through conversations with practitioners who…
AI and Healthcare: Adrian Jennings, Chief Product Officer at Cognosos, on Scaling RTLS in the Post-AI Era
AI and Tech Leadership: This interview series is grounded in lived experience. It explores how technology leaders move AI from experimentation into day-to-day operations, where decisions carry real consequences for teams, customers, and the business. Through conversations with practitioners who…
Operational Resilience is Not a Dashboard: Mahesh Paolini-Subramanya on DORA and Bank Architecture
AI and Tech Leadership This interview series is grounded in lived experience. It explores how technology leaders move AI from experimentation into day-to-day operations, where decisions carry real consequences for teams, customers, and the business. Through conversations with practitioners who…
Here’s Why AI Literacy Is Now a Core Engineering Requirement
There was a time when AI lived on the margins of the enterprise. A small data science team ran experiments. A proof-of-concept sat in a lab environment. Most engineers built deterministic systems and left probabilistic ones to specialists. That separation…
Why AI Value Now Depends More on People Than Models
The AI talent shortage is no longer a line item in HR reports. It is quietly reshaping boardroom conversations, capital allocation, and the pace of AI transformation itself. For years, executives have been obsessed with model size, GPU clusters, and benchmark scores. Today, the constraint is far more human.…
Auditability in the Age of Autonomous AI
Auditability in AI has moved from a technical afterthought to a boardroom mandate. For CTOs leading enterprises into the era of autonomous systems, visibility is now power, and protection. A decade ago, AI was experimental. Today, it approves loans, flags fraud, triages patients and moderates speech. As…
Is AI-native Architecture Shifting the Focus? Denis Romanovskiy, Chief AI Officer Weighs In
AI and Tech Leadership: This interview series is grounded in lived experience. It explores how technology leaders move AI from experimentation into day-to-day operations, where decisions carry real consequences for teams, customers, and the business. Through conversations with practitioners who…
Compliance Risk Management: Why Over-Governance in AI Is as Risky as No Governance
CTOs often see compliance risk management as a way to protect their businesses from operational, legal, and regulatory threats. However, excessive controls can be counterproductive in the AI era. As businesses advance in AI adoption, they often swing between excessive…
Why Technical Leadership is Now Ethical Leadership
For many years, system performance, speed, and scale were the defining characteristics of technical leadership. You would perform well if you could build robust platforms, ship more quickly, and deliver quantifiable returns on investment. That definition is no longer accurate.…
Data Platforms for Agentic AI: Why Agentic AI Demands a Rethink
Enterprises are discovering that scaling agentic AI depends more on data platforms that enable real-time reasoning and learning than on the models themselves. Enterprise AI has reached a new stage. Technology leaders now ask whether current foundations can support AI,…
From Principles to Practice: What AI Governance Actually Looks Like in 2026
Artificial intelligence has reached a new stage.By 2026, AI is no longer an experimental technology, it is embedded in core business workflows. But as organisations scale AI, a pattern is becoming clear: AI transformation is no longer a technology challenge.…