Cost Optimization, Productivity, and Streamlined Operations in a Digital Era

In an exclusive conversation with Media Infotainment, Veeranath Srikar, Founder of A2Z Assist, shares how digital transformation is unlocking new efficiencies across industries. For him, cost efficiency isn’t about cutting corners but eliminating friction. From AI-powered claim reviews in healthcare to predictive analytics and automation in media, he highlights how emerging technologies drive speed, intelligence, and resilience. Beyond tech, Srikar stresses cultural shifts—positioning AI as a co-pilot, not a replacement—and sees AI-driven simulation as key to reducing risks while accelerating creativity.

Leveraging Digital Transformation for Cost Efficiencies

In my work, I’ve learned that cost efficiency isn’t about cutting corners; it’s about removing friction. In healthcare automation, we identified repetitive tasks like claim reviews and manual data checks that slowed everything down. By integrating AI and predictive analytics, we reduced manual effort by over 60% and saved millions in potential revenue leakage.

For media and entertainment, the principle is the same: to find where processes are manual, redundant, or slow. Whether it’s automating metadata tagging, streamlining localisation, or using AI to predict content performance, digital transformation should free up people to focus on creative, high-value work, not routine operations.

Impact of Emerging Technologies

Of all the technologies I’ve worked with – AI, RPA, and low-code platforms – AI has been the real game-changer. But it only worked because we scaled it properly. For example, in one project, low-code tools helped us rapidly prototype workflows, but AI was what made them intelligent. It wasn’t just about speed; it was about learning from real-world data and improving as we went.

In M&E, AI can accelerate post-production, power real-time dubbing, or personalise content delivery. But scaling adoption means tracking hard metrics like time saved, error reduction, and faster turnaround, not just deploying tech for the sake of it.

Also Read: Balancing Functional Value with Emotional Storytelling

Organisational & Cultural Shifts

This was the hardest part, not the tech. We had to move teams from worrying about ‘AI replacing roles’ to seeing it as a co-pilot. We built a culture where every AI deployment started with one question: What problem are we solving for the business or the customer?

Once people saw AI removing repetitive work and letting them focus on creative problem-solving, adoption grew naturally. For media teams, it’s the same: building trust, proving value, and showing how AI can enhance, not replace, the creative process.

Balancing Streamlining with Resilience

In my experience, efficiency is only sustainable if resilience is built in. We modularised workflows so automation could run most processes, but HITL (Human In the Loop) fallback was always there for exceptions, keeping operations running even when AI hit uncertainty.

For M&E, this means using hybrid cloud, AI orchestration, and HITL safeguards. So, streamlining never compromises continuity for live events or high-value content delivery.

Also Read: The AI Disruption of Filmmaking - and the New Models It Will Spawn

Role of AI-Driven Prototyping & Simulation

‘Edit before you make’ is a concept I strongly believe in. We used simulation extensively, testing hundreds of claim-processing scenarios before deploying AI live. It helped us catch compliance issues and data quality issues early and avoid costly fixes later. For media, imagine testing a dubbing AI, visual effects workflow, or ad-placement model virtually before production. You reduce risk, save costs, and shorten the feedback loop dramatically.