AI-Powered Ports: Reimagining Efficiency and Operations

Detailed Summary

Speaker: Shri T.K. Ramachandran (Former Secretary, MoPSW) – 3 min opening.

thanked the VIO Chidambana Port Authority and the Institute for Governance, Policies and Politics (IGPP).
framed AI as a new “wave” that ports must ride, emphasizing that digital and data infrastructure are prerequisites for any AI layer.
Highlighted existing digital foundations: enterprise business systems in several ports, NLP‑Marine, “Sagar Setu”, “e‑Samudra” in the Directorate General of Shipping (DGS).
Stressed the need for standardised processes (“One Nation – One Port”):
- Initially ~800 distinct port‑related documents were consolidated to ~200, then distilled to ≈ 50‑60 core processes.
- Without common standards and interoperable data, AI cannot be effectively built.
Enumerated AI‑application domains: operations, environment, planning (predictive), monitoring, safety, compliance.
Identified key challenges: data silos, vendor lock‑in, lack of integrated SOPs, AI currently used only as advisory, accountability for AI‑driven decisions, HR capacity, need for a shared integration framework.
Contrasted “Smart Ports” (technology‑led) with “Thinking Ports” (decision‑led):
- Move from real‑time visibility → predictive visibility.
- Shift from siloed systems → system‑wide frameworks.
- Transition from reactive to anticipatory, learning systems that embed AI in decision making.

Key Insight: AI is not merely a tech add‑on; it must be woven into governance and decision‑making processes to transform ports into “thinking ports.”

2. Implementation Experiences – Operational View

Speaker: Shri Subrat Tripathi (Advisor, Adani Ports) – ~5 min.

Began with an anecdote about the need for algorithmic scheduling to improve punctuality in large venues (e.g., Bharat Mandapam).
Emphasised the systemic complexity of maritime trade: 85 % of global trade and ~95 % of India’s trade (by volume) rely on ports.
Outlined five thematic AI opportunities:
1. Design & Planning – Proposes digital twins for port layout, berthing precision, modular scalability, and traffic‑flow alignment.
2. Operational Impact – Cites Maersk’s “Captain Peter” (autonomous pilot) and notes AI’s role in just‑in‑time yard logistics, vessel‑arrival coordination, and multi‑terminal integration.
3. Safety & Risk Management – Highlights AI‑driven risk assessments, predictive safety analytics, and the need for sovereign data protection when fusing human‑machine‑vessel interactions.
4. Quality Assurance & Customer Interaction – Describes a “virtual concierge” that automates documentation, stakeholder communications, and service‑level monitoring without replacing humans.
5. Global Benchmarks – References Port of Rotterdam (AI reduced ship‑waiting time by ~20 %) and Port of Singapore (maritime single‑window platform) as models for Indian ports.
Cited the Suez Canal blockage (Evergreen, 2021) as a case study: over 430 vessels affected; AI could have offered predictive navigation and berth‑allocation to mitigate such disruptions.

Key Insight: AI must be integrated across the entire port lifecycle—from design and planning through real‑time operations and post‑event analytics—to build resilience against systemic shocks.

3. Technology Adoption & Use‑Cases

Speaker: Mr. Vaneesh Jaiswal (GM, Bug Support – IT vendor) – ~4 min.

Positioned AI as a ubiquitous, already‑present technology (e.g., ChatGPT, Gemini) that many professionals use without realizing its AI core.
Identified four practical AI application clusters in ports:
1. Resource Optimisation – AI‑driven scheduling of vessel arrivals, container handling, truck routing, and yard storage.
2. Behavioural Safety – Video‑analytics powered AI to predict unsafe worker behaviours and pre‑empt accidents (currently piloted at JM Baxi ports).
3. Fraud & Compliance Detection – AI‑enabled pattern‑recognition to flag irregularities in documentation, origin of cargo, and financial transactions; also supports sanctions‑screening.
4. Cyber‑Security – AI layers that monitor and defend automated equipment (cranes, AGVs) against ransomware and intrusion attempts.
Forecasted a near‑term evolution from predictive AI (forecasting outcomes) to prescriptive AI (recommending actionable solutions).

Key Insight: AI is already delivering tangible efficiencies; the next leap will be automated decision‑making that not only predicts but also prescribes corrective actions.

4. Legal, Governance & Liability Considerations

Speaker: Ms. Aprajita Rana (Partner, AZB & Partners) – ~6 min.

Stressed that AI deployment in ports raises contractual, liability, and regulatory challenges.
Highlighted the absence of a dedicated Indian AI law, making liability attribution ambiguous.
Warned that technology‑vendor contracts often contain broad indemnity clauses, potentially leaving port authorities exposed.
Called for a formal AI‑governance framework covering:
- Auditability & Explainability – mechanisms to trace AI decisions and validate model outputs.
- Testing & Validation – rigorous pre‑deployment trials, especially for safety‑critical functions.
- Data Stewardship – ensuring data integrity, provenance, and sovereign protection across multiple stakeholders (port operators, OEMs, technology providers).
- Liability Allocation – clear contractual clauses delineating responsibility between operators and vendors for AI‑induced errors.
Suggested that industry‑wide standards (perhaps modeled on the European AI Act) are needed before large‑scale autonomous AI is rolled out.

Key Insight: Robust legal and governance structures are prerequisite for scaling AI; without them, the risk of costly litigation and operational disruption is high.

5. Economic Impact & Policy Imperatives

Speaker: Prof. (Dr.) Gaurav Vallabh (Economic Advisory Council to the PM) – ~7 min.

Framed AI in ports as a national economic lever aligned with the “Atma Nirbhar India – Viksit Bharat 2047” vision.
Presented key macro‑statistics:
- 95 % of India’s trade (by volume) moves through maritime routes.
- Current capacity utilisation of major ports is only ≈ 50 % despite handling ≈ 855 Mt in FY 2025.
- Performance gaps: dwell time is 2.5× the global best; vessel turnaround is 2×; crane productivity is ~50 % of world‑class ports.
Introduced Eight “AI Pillars” for transformation (summarised below).
Economic benefit projection: AI‑enabled efficiency could save roughly ₹20,000 crore in handling costs and ₹15,000 crore annually in logistics expenses.
Urged policy acceleration:
- Fast‑track the Sagar Mala and National Logistics Policy initiatives.
- Promote PPP models for AI‑driven infrastructure.
  Call to Action: Government must provide clear policy direction, funding, and regulatory certainty to enable ports to become “intelligent ecosystems” rather than merely “physical assets.”

Key Insight: AI is not a futuristic concept; it is an immediate catalyst for substantial cost savings and competitive advantage for India’s maritime sector.

6. Closing Remarks & Session Wrap‑Up

The moderator (Dr. Manish Tiwari) thanked all panelists, reiterated the need for coordinated AI rollout, and invited further offline discussions.
A brief photo‑op and acknowledgments to the VIO Chidambana Port Authority and IGPP concluded the session.

Key Takeaways

Digital Foundations Are Mandatory: AI cannot be layered on legacy, siloed systems; ports must first achieve standardised processes, common data frameworks, and interoperable software (“One Nation – One Port”).
From Smart to Thinking Ports: The shift is from technology‑driven automation to AI‑enabled decision‑making that is predictive, anticipatory, and learning.
Eight Critical AI Pillars (as identified by Prof. Vallabh):
1. Infrastructure Availability – leverage existing capacity but improve utilisation.
2. Performance Assessment Index – benchmark dwell time, turnaround, crane productivity.
3. Impediment Removal – eradicate documentation and process delays.
4. Authentic Integration – predictive maintenance, digital twins, intelligent berth scheduling.
5. Automated Initiatives – port‑community services, unified logistics, Sagar Setu.
6. Strategic Investment – Sagar Mala, national logistics policy, PPPs.
7. New Port Development – Vizinjam, Wadwan, Greater Nicobar ICTP.
8. Accelerated Road‑Map – immediate (automated gates), medium‑term (digital twins, AI‑driven berths), long‑term (autonomous terminals, hydrogen fuel).
Economic Gains: AI can potentially save ₹20 k crore in handling and ₹15 k crore annually in logistics costs, reinforcing the urgency of adoption.
Legal & Governance Gaps: Absence of a dedicated AI law in India creates liability uncertainties; a sector‑wide governance framework (auditability, explainability, contractual clarity) is essential before deploying autonomous AI.
Global Benchmarks Matter: Learning from Rotterdam (20 % ship‑waiting reduction) and Singapore (maritime single‑window) can accelerate Indian ports’ AI maturity.
Human Factor Remains Central: AI should augment—not replace—human workers; safety, behavioural analytics, and skill‑transition programs are vital for workforce acceptance.
Policy Accelerators Needed: Rapid implementation of Sagar Mala, National Logistics Policy, and PPP incentives will provide the requisite financing and regulatory clarity.

The panel painted a comprehensive picture: AI is already reshaping parts of port operations, but to unlock its full potential India must harmonise digital infrastructure, institute robust governance, and enact supportive policy—all while keeping the human workforce at the heart of the transformation.

See Also:

India AI Impact Summit 2026

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