DELIVER Asia 2026 Conference Recordings

Artificial intelligence is rapidly transforming supply chain operations, yet most organisations remain stuck at the experimentation stage.

At DELIVER Asia 2026 in Singapore, a panel of industry leaders explored why fewer than 20% of AI initiatives move beyond pilot programmes — and what companies must do to successfully scale adoption.

The discussion highlighted that while technology capabilities continue to advance, the real barrier to adoption lies in skills, leadership alignment and organisational readiness.

Across supply chain planning and operations, AI is already demonstrating tangible benefits in several areas.

Abhishek Rajpal explained that in strategic planning, AI tools can analyse historical datasets to identify patterns and provide recommendations for forecasting and inventory management. Retailers are increasingly using AI to monitor stock levels, automate reporting and analyse customer behaviour within stores.

In warehousing, automation technologies are already transforming storage and picking processes. However, many operational tasks — particularly packing and quality control — still rely heavily on human judgement.

As a result, AI is currently most effective in supporting decision-making rather than fully replacing operational roles.

While AI has primarily supported planning and analysis, the next phase of adoption is beginning to impact operational execution.

Pankaj Sharma highlighted how advanced forecasting models can now automate demand planning processes that were previously performed manually by planners.

These systems analyse large datasets to predict demand more accurately, improving product availability on shelves and reducing stockouts.

AI is also increasingly being used in production environments, where computer vision tools can perform rapid quality checks that once required manual inspection.

However, these systems must operate within clearly defined boundaries.

Supply chain professionals still play a critical role in setting guardrails, validating outputs and ensuring AI-driven decisions align with business strategy.

One of the most important capabilities emerging for supply chain professionals is prompt engineering — the ability to interact effectively with AI tools.

According to Amit Garg, the quality of AI outputs depends heavily on the quality of inputs provided.

Understanding how to frame questions, refine prompts and interpret AI responses will become an essential skill for future supply chain leaders.

Organisations must therefore invest in training programmes that help employees build AI literacy across the business.

This shift requires both technical education and a broader change in mindset.

Beyond technical skills, leadership behaviour plays a crucial role in successful AI adoption.

Many companies launch AI initiatives from the top down, yet fail to create the learning culture required for real transformation.

Amit Garg shared how leadership teams must actively participate in training and experimentation rather than delegating AI adoption entirely to technology departments.

In some organisations, leaders are creating regular internal sessions where teams experiment with AI tools, build simple prototypes and learn how different models operate.

These initiatives help employees develop confidence and understanding before more advanced solutions are implemented.

Despite rapid technological advances, the panel emphasised that AI will not replace human judgement in supply chain decision-making.

Many aspects of supply chain management — including negotiations, relationship building and complex strategic decisions — require emotional intelligence and contextual understanding that AI cannot replicate.

Abhishek Rajpal illustrated this point using retail procurement as an example.

Even with advanced forecasting models, purchasing fresh products from suppliers involves negotiation, trust and human relationships that remain central to successful business outcomes.

In these situations, AI can support analysis but cannot replace human interaction.

As AI capabilities expand, supply chain professionals must adapt by developing new skills.

Key areas of focus include:

• Understanding how AI models work and how to interact with them
• Interpreting AI-generated insights and recommendations
• Managing hybrid human-AI workflows
• Maintaining strong analytical and strategic thinking capabilities

Organisations that prioritise continuous learning and experimentation will be best positioned to integrate AI effectively.

The panel concluded that the future of supply chain operations will not be defined by AI alone, but by the balance between human expertise and intelligent technology.

Companies that succeed will be those that combine strong data foundations, skilled teams and thoughtful leadership to unlock the full potential of AI.

Rather than replacing supply chain professionals, AI will reshape the role — enabling teams to focus more on strategy, creativity and decision-making.