Rajashree Goswami
Rajashree Goswami is a professional writer with extensive experience in the B2B SaaS industry. Over the years, she has honed her expertise in technical writing and research, blending precision with insightful analysis. With over a decade of hands-on experience, she brings knowledge of the SaaS ecosystem, including cloud infrastructure, cybersecurity, AI and ML integrations, and enterprise software. Her work is often enriched by in-depth interviews with technology leaders and subject matter experts.
Articles by Rajashree Goswami
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 ModelsÂ
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 AIÂ
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  Â
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 2026Â
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.…
AI Governance Models: The New Risk Surface Every CTO Must Manage
As companies expand their use of generative and agent-based AI, the focus of AI governance is changing. It’s not just about policies or compliance checklists anymore. The main challenge now is how organizations design their AI governance models to oversee,…