The Year of Agentic AI: Capturing Early Wins and Defining Priorities

Arjun Vishwanathan
Chief Insights Officer
StrategINK

As Agentic AI moves from experimentation to execution, Global Capability Centers (GCCs) are evolving into intelligence-led enterprise hubs. This panel examines how autonomous agents are reshaping GCC operating models, leadership mandates, and global value creation.

• From Delivery to Decision-Making – How Agentic AI is transforming GCCs from execution centers into autonomous decision hubs.
• Operating Models Reimagined – Redesigning GCC workflows, talent models, and KPIs for agentdriven systems.
• Governance, Trust & Control – Managing autonomy, accountability, and risk in AI-led GCC environments.
• Scaling with Impact – Moving beyond pilots to enterprise-wide adoption and measurable business outcomes.

Sridevi Vadapalli
Chief Data Scientist
Daimler Truck Innovation Center India

Vidyadhar Joshi
Director - Global Data Analytics & Data Governance
Schneider Electric

Sharmistha Chatterjee
Industry Leader

Dr. Shivani Rai Gupta
Chief Data Scientist
Jio

Moderator
Prateek Tokas
Chief Knowledge Officer
StrategINK

As autonomous agents begin making real-time decisions, enterprises must ensure complete visibility into their actions. Observability and traceability provide the trust layer—capturing what the agent did, why it acted, and which data influenced its choices. Without this transparency, risks around governance, compliance, and security escalate rapidly in an AI-native enterprise.

• Enterprise-grade logs capturing every agent action, trigger, and outcome
• Explainability layers revealing the reasoning behind decisions
• Audit trails and data lineage ensuring compliance and trusted inputs
• Real-time monitoring and fail-safe controls to prevent unintended consequences

Samrat Bhatt
SVP 1 - IT & Security
Axis Bank

Chandan Vijay
Global Chief Data Officer
ABB Energy Industries

Shubhradeep Nandi
Chief Data Scientist
Government of Andhra Pradesh

Vishal Nagpal
Director - Data & AI
Best Buy

Moderator
Arjun Vishwanathan
Chief Insights Officer
StrategINK

By enabling autonomous, context-aware decisions that increase productivity, lower costs, and improve agility, agentic AI is revolutionising industrial operations. These intelligent agents go beyond static automation by dynamically optimising processes and adapting in real-time. However, there are still issues, particularly with workforce adoption, scalability, data privacy, and legacy system integration. investigating how businesses can realise the full potential of agentic AI in the manufacturing sector by striking a balance between innovation and real-world application.

• Understanding the Shift: How Agentic AI differs from traditional industrial automation systems.
• Bridging the Gap: Strategies for integrating Agentic AI into legacy manufacturing environments.
• Securing Smart Factories: Addressing data privacy and cybersecurity in autonomous operations.
• Scaling and Skills: Human-AI collaboration and roadmap for enterprise-wide deployment.

Mitali Dutta Das
Senior Director & Head - Insights & Analytics | Enterprise Architecture Data & Integration | Group IT
Philips

Ganapathy V
VP & Head - Global Advanced Analytics CoE
Holcim

Praveen Krishnamurthy
Zone IT Director, Greater India
Schneider Electric

Urvinder Singh
General Manager - Data Science & Machine Learning
Linde

Vikas Marwaha
Head - Data Science & Engineering (Digital & AI)
TVS Motor Company

Moderator
Prateek Tokas
Chief Knowledge Officer
StrategINK

Agentic AI is not the future, it is already redefining how digital-first enterprises operate. In this highlevel discussion, technology leaders unpack how autonomous AI agents are reshaping IT architectures, decision systems, operational models and enterprise-wide intelligence. From smart automation to real-time orchestration, discover how CIOs are building organisations where AI is not just a tool but a trusted co-pilot powering agility, resilience and scalable innovation.

The new governance blueprint: How Technology Leaders govern autonomous agents, ensure compliance, and build real-time, AI-native operating models

• Architecting cross-enterprise intelligence: Breaking silos with interoperable systems and autonomous workflows that learn and adapt
• Agentic AI in action: Real-time decision support, anomaly detection, predictive operations and cost optimisation
• Autonomous experience engines: Using agents for hyper-personalization, campaign automation, and end-to-end journey orchestration

Venugopal Medicherla
Group CIO
MSPL Limited (Baldota Group)

Ramkumar Mohan
SVP & CIO
Air Works Group

Anirudh Kunjal
Head - Digital & Technology - Data, AI & Marketing
Diageo

Suvro Shankar Ghosh
Head – AI Solutions (MFCWL), AI Division
Mahindra Group

Moderator
Arjun Vishwanathan
Chief Insights Officer
StrategINK

Agentic AI may signal a future of autonomous decision-making, but enterprises today are still wrestling with the hard realities of taking AI from prototype to production. This session cuts through the noise to examine what truly holds back scale, value, and governance in real-world deployments.

• Exposes the real friction points in enterprise AI adoption — cost, governance, customer experience, and production readiness.
• Brings perspectives from across the AI value chain, including global finance where an “Ethical Quotient” is foundational.
• Hear from a leading CIO on converting AI investments into measurable customer NPS gains.Learn from logistics analytics experts on enforcing true ROI through “actionable data” that drives outcomes.

Mayank Kant
SVP & Head - Data Science
Nykaa

Achal Ananth
Head - Analytics, BI & Data Platform
PhonePe

Rohit Chatter
Chief Data Officer
Angel One

Gaurav Agrawal
SVP & Head - Product Growth, Curriculum & Analytics
Simplilearn

Shreedharma Vijayan
Sr. Account Manager
TiDB

Moderator
Prateek Tokas
Chief Knowledge Officer
StrategINK

Digital natives were built for AI. Legacy enterprises must now redesign for autonomy.

• Platform-First Thinking: Move beyond siloed AI pilots. Build reusable data, API, and model platforms that enable continuous, scalable intelligence.
• Real-Time Decisioning: Shift from batch analytics to live orchestration, fraud detection, personalization, pricing, and operations powered by instant feedback loops.
• Human-on-the-Loop Governance: Autonomy needs guardrails. Embed oversight, explainability, monitoring, and incident response into AI systems from day one.
• AI-Native Operating Model: Align product, engineering, and data teams. Treat AI as a growth engine — not just a cost optimization tool.

Dhruv Rastogi
SVP - AI & Data Technology
Medi Assist

Anand Mahalingam
Vice President - Data Science
Digit Insurance

Pradeep Sharma
Head - Technology
Cars24

Biswajit Biswas
Chief Data Scientist
Tata Elxsi

Vivek Kaushal
Associate Group Manager - AI
Tally Solutions

Moderator
Prateek Tokas
Chief Knowledge Officer
StrategINK