Industry

Enterprise AI · intelligent automation · digital operations · regulated enterprise systems

About the client 

iOPEX is an Intelligence-as-a-Service provider helping large enterprises redesign operations using artificial intelligence, automation, and orchestration. 

The company operates at the intersection of technology, operations, and business outcomes, serving leaders responsible for scale, efficiency, and resilience.

Why this work was thought leadership

This was not content created to explain existing categories. It was content created to define a position in a new one.

Agentic artificial intelligence is still a disruptive and emerging space. 

There is confusion in the market between assistants, automation, orchestration, and true autonomous systems. iOPEX needed to make its stance clear, credible, and technically grounded without sounding speculative or promotional.

What I worked on

I wrote and shaped iOPEX’s thought leadership narrative around agentic AI, autonomous operations, and enterprise transformation.

This included:

- Technical yet accessible explanations of agentic systems

- Clear positioning around why traditional automation and chatbots fail at scale

- Social media copy for the brand’s LinkedIn presence

- Narrative alignment across customer experience, risk, IT operations, and security

Some of the thought leadership pieces I authored include:

Why Healthcare CX Fails at the Handoff and How Agentic AI Cuts Resolution Time by 75 Percent

Why UX Is the Missing Layer in AI Adoption and How to Fix It

Agentic AI Use Cases: From Assistance to Action

What Enterprise Leaders Must Know About Operationalizing Agentic AI

Salesforce CRM Is Smart, Agentic AI Makes It Unstoppable for Enterprises

One Decision That Can Safeguard or Sink Your Salesforce ROI

7 Agentforce Use Cases for Customer Service Your Organization Cannot Afford to Ignore

Building Autonomous Operations with AI Agent Orchestration in ServiceNow

Why Your ITSM Automation Is Not Smart Enough and How Agentic AI Can Fix It

Reimagining Enterprise Risk and Resilience in the Age of Intelligent Automation

SIEM Optimization Strategies for Stronger Cybersecurity 

The Future of Customer Support: AI Agents That Think and Empathize with Customer Needs

AI vs AI: Proactive Defense Against AI-Powered Attacks

How I rethought research for these 

To write with credibility, I went deep into the technical realities behind enterprise platforms.

This meant:

- Understanding how Salesforce data models, workflows, and agent frameworks shape real customer operations

- Studying ServiceNow orchestration, IT service management flows, and automation limits

- Exploring how artificial intelligence infrastructure, including NVIDIA acceleration and model deployment considerations, affects what is actually possible in production systems

This research shifted how I think about enterprise technology. It forced me to write from the perspective of systems, constraints, and trade-offs.