Persistent Systems

Most AI conversations still start with the wrong question.
Which model. Which platform. Which use case.

The right question is harder: what does it actually take for AI to move from experimentation into enterprise ex*****on?
This video breaks it down — visually.

The 3C framework. Three layers that determine whether AI stays at the edges of work or gets built into the center of it. Core. Context. Coordination. And what it looks like when people, systems, workflows, data and AI agents finally operate as one connected model.

Watch the video to understand why Core, Context and Coordination are the foundation every enterprise AI strategy needs →https://www.persistent.com/ai/

AI spend is rising. But value isn’t keeping pace.
And that gap is where every enterprise leader needs to pause.

Because investment alone doesn’t remove the barriers that hold AI back from scaling.

Sameer Dixit – Corporate Vice President, Data & Integration, Persistent Systems unpacks what needs to change and where leaders need to think differently.

Explore how enterprises can close the AI readiness gap: https://www.persistent.com/ai/enterprise-data-ai-readiness/

AI has moved from experiment to ex*****on faster than anyone expected and it's still accelerating. What once felt experimental is now becoming part of everyday enterprise ex*****on and the pace of change is only increasing.

AI Hub brings together practical insights, real-world applications and evolving enterprise perspectives in one place, helping you cut through noise and focus on what actually drives impact.

Subscribe to AI Hub to stay close to how enterprise AI is really evolving: https://www.persistent.com/ai-hub/

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AI tools are everywhere.
The results aren’t.

Most enterprises are running AI experiments.
Far fewer are running AI as a core enterprise capability.

That is the gap, not the model, platform or pilot.

The difference is what gets built around AI — connected business priorities, AI-ready data, embedded governance and teams that can adopt with confidence.

Because AI creates the most value when it is engineered into how the enterprise works.
Jaideep Vijay Dhok, Chief Operating Officer – Technology, Persistent Systems, unpacks what it takes to move from AI experimentation to enterprise transformation.

Know more about how enterprises can move from AI experimentation to enterprise transformation Enterprise AI Transformation with the 3C Framework: Core, Context, Coordination

Responsible AI is often treated like a checkpoint.

Something to clear before innovation moves forward.

But, what if that framing is wrong?

Curious about how Responsible AI can move beyond a compliance checkpoint and become an enabler of speed, trust and scale?

Shivangi Nadkarni, Senior Corporate VP - Digital Trust, Persistent Systems, shares her perspective.

Learn more here: https://www.persistent.com/ai/responsible-ai/

AI is no longer an innovation experiment. It is becoming the operating layer of modern enterprises.

Yet many organizations are still struggling to move beyond fragmented pilots and isolated use cases. The real challenge today is not AI adoption alone, but scaling measurable business value across the enterprise.

In the report, Pritish Mishra shares perspective on what it takes to avoid the AI failure trap and move from experimentation to enterprise value.
What leaders need now:

• Clear ownership across business and technology
• Measurable outcomes instead of AI hype
• Governance embedded from day one
• Teams prepared for new ways of working
• Enterprise-wide strategy over disconnected initiatives

The next wave of AI leaders will not be defined by how much they invest in AI, but by how effectively they turn it into measurable business value.

Explore the joint report by Persistent and Indian Institute of Management Ahmedabad to discover how enterprises can move beyond fragmented pilots, scale AI with clarity, and unlock sustainable impact across the organization: https://www.persistent.com/insights/navigating-the-failure-trap-with-ai-value-compass/

AI pilots can work.
But, enterprise AI can still fail to scale. Why?

Because scaling AI is not about launching more use cases. It is about changing how AI connects to the enterprise: its data, workflows, systems, governance and people.

In Episode 1 of Re(AI)L Questions | Making Enterprise AI Work, Nitish Shrivastava explains what really needs to change for AI to move from experimentation to enterprise impact.

Watch now.

Explore Persistent.AI: https://www.persistent.com/ai/

AI strategy is becoming a boardroom priority.
But for many enterprises, the harder questions begin after the investment is approved.
What moves beyond pilots?
What gets governed?
What creates measurable impact?
What is worth scaling?

The Re(AI)magine Hub brings together enterprise perspectives, leadership conversations, transformation insights, and real-world stories on scaling AI across the organization.

Subscribe to follow the latest enterprise AI perspectives, stories and leadership conversations from Persistent:
https://www.persistent.com/ai-hub/