Artificial intelligence is becoming embedded in routine planning workflows, yet companies are deliberately keeping human judgment at the center of execution. New data from RELEX Solutions points to a hybrid model taking hold, one that blends machine-driven insight with human accountability as volatility continues to shape operating conditions.
Confidence Rises, but Full Autonomy Remains Limited
Findings from the RELEX State of Supply Chain 2026 report show a clear increase in confidence: 67% of respondents say their trust in AI has grown over the past year. Even so, only 10% are prepared to let AI operate independently in decision-making. Most organizations are opting for a structured middle ground, where AI generates recommendations but planners retain final authority, an approach cited by 54% of respondents.
This reflects a broader recalibration of how automation is deployed in planning environments. Rather than removing human involvement, companies are redefining it. AI is being used to process larger data sets, simulate scenarios, and flag risks faster than manual methods allow, while planners focus on interpreting outputs, applying context, and managing trade-offs.
Dr. Madhav Durbha, Group Vice President of Manufacturing Industry Strategy at RELEX Solutions, noted that companies are investing in AI-driven forecasting and optimization to respond more effectively as conditions shift. The emphasis is on speed and consistency, but within a controlled decision framework.
Adoption is also concentrating in core planning functions. The report shows 47% of companies are using AI for inventory and supply optimization, while 41% are applying it to logistics and routing. These are areas where decisions directly affect service levels, working capital, and network efficiency, making the integration of AI particularly consequential.
Investment Expands as Risk Strategies Evolve
Spending plans indicate that this shift is not incremental. Around 71% of respondents expect to invest in generative AI over the next three to five years, while 60% plan to expand predictive AI capabilities. The investment focus aligns with persistent operational pressures, with 44% citing demand volatility as a primary concern.
At the same time, companies are adjusting how they manage that volatility. Traditional buffers, such as higher safety stock or broader supplier bases, are being supplemented, and in some cases partially replaced, by digital capabilities and closer ecosystem coordination. According to the report, 59% of organizations are strengthening collaboration with logistics partners, signaling a move toward shared visibility and coordinated execution rather than standalone risk hedging.
This direction is consistent with patterns seen across recent trade and operations data, where companies are seeking to control variability through better synchronization rather than inventory expansion. The combination of AI-enabled planning and tighter partner integration allows for faster response without proportionally increasing cost or complexity.
The survey, conducted in January 2026, draws on responses from 514 organizations across retail, manufacturing, and distribution, providing a cross-sector view of how planning models are evolving.
When Faster Decisions Expose Structural Gaps
As AI compresses planning cycles, it is beginning to surface constraints that were previously absorbed or hidden, capacity mismatches, supplier inflexibility, and misaligned service policies become more visible when decisions are made in near real time. According to trade reports and recent network optimization studies, companies that pair AI-driven planning with operational adjustments, such as flexible capacity contracts or revised service-level segmentation, are seeing more consistent performance gains than those relying on planning tools alone. The advantage is not in speed by itself, but in aligning execution capabilities with the pace of decision-making, ensuring that faster insights translate into outcomes that the network can actually deliver.
