Manhattan Launches AI Explanation Tool for Supply Chain Decisions

By Ben Ames, Senior Technology Correspondent

Manhattan Associates Introduces Sightline Tool to Explain AI Decisions

According to www.dcvelocity.com, Manhattan Associates has launched Sightline, a new tool within its ActivePlanning suite that explains the reasoning behind agentic AI-driven supply chain decisions in plain business language. The tool aims to reduce user skepticism by revealing how AI arrives at forecasts, inventory recommendations, and replenishment strategies.

“Advanced AI forecasting can often feel like a black box that requires a data scientist to do the analysis, so practitioners may have difficulty understanding exactly why it’s doing what it’s doing.” — Manhattan Associates

Addressing the AI Transparency Gap in Supply Chain Planning

Sightline provides a forensic-level breakdown of decision factors, including forecast inputs, safety stock levels, vendor minimum order quantities, lead times, promotional impacts, fulfillment shifts, and network movements. The tool was introduced at Manhattan’s annual Momentum user conference in Las Vegas, held in May 2026. According to the company, this move establishes a new standard for planning software by embedding explainability directly into the planning process.

• Manhattan Associates introduced Sightline at its Momentum user conference in Las Vegas, May 20–22, 2026.
• The tool is part of the ActivePlanning suite, used by supply chain professionals to manage inventory and demand forecasting.
• It analyzes over 15 distinct factors influencing AI-driven recommendations, including lead times and promotional effects.
• Manhattan reported that 68% of supply chain planners expressed hesitation in trusting AI decisions without transparency.

Industry Context: The AI Productivity Paradox in Procurement

According to a Gartner survey of 101 chief procurement officers (CPOs) conducted in January–February 2026, only 36% of CPOs are very confident in their ability to redesign roles and processes around AI. Gartner describes this as the “AI productivity paradox,” where individual productivity gains from GenAI do not translate to team or organizational outcomes unless processes are redesigned.

“Procurement teams are seeing productivity gains from GenAI, but without intentional redesign of roles and processes, those gains remain confined to the individual level.” — Fareen Mehrzai, Senior Director Analyst, Gartner Supply Chain Practice

Despite improvements in individual output, time savings, and quality, Gartner found that team-level performance gains declined significantly. The report recommends that CPOs redesign roles to separate human and AI-native tasks, align AI outcomes with financial results like cost optimization and revenue growth, and update productivity metrics to include innovation and new outputs.

Practical Implications for Supply Chain Professionals

Sightline enables planners to trace AI-generated recommendations back to their root data inputs, such as a 14-day lead time from a supplier or a 22% increase in demand due to an upcoming promotion. This transparency supports faster decision-making and builds trust in AI systems. For instance, if AI raises safety stock levels by 30%, planners can now review whether the change stems from a supplier delay, market volatility, or a promotional event.

Manhattan Associates emphasized that AI decisions in planning systems now affect forecasts, replenishment, and allocation—actions with direct financial and operational impact. With Sightline, users can interrogate each decision in plain language, reducing reliance on data scientists and enabling broader adoption across teams.

Source: DC Velocity

Compiled from international media by the SCI.AI editorial team.