State of AI in Distribution - DSG

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Introduction

The State of AI in Distribution 2026 report synthesizes findings from the Distribution Strategy Group’s third annual survey conducted in December 2025.

Based on a comprehensive survey of 233 respondents, the report provides a strategic window into how wholesale distribution leaders are transitioning from the initial AI hype cycle toward disciplined execution and production value.

The main message is clear: executive buy-in exists, funding is available, and widespread piloting is underway. The bottleneck has shifted from strategic commitment to execution capacity.

Quick Summary

• Wholesale distribution has moved from AI curiosity to execution. Leaders are now focused on turning pilots into production value.
• 63% of distributors remain in the “exploring” or “piloting” stages, while only 4% have AI central to their strategy.
• The biggest AI adoption barriers are people-related: skills gaps account for 33%, and change resistance accounts for 19%, combining for 52% of responses.
• Data quality strongly shapes confidence in AI ROI. Distributors with strong data infrastructure are 4.5 times more likely to express confidence in AI ROI than those with siloed or inconsistent data.
• Practical AI use cases gaining traction include email order automation, cybersecurity, internal chatbots, automated AP/AR, quote automation, and AI-enhanced CRM.
• 65% of distributors plan to increase AI investment over the next two years.

What You Will Learn

• Why execution capacity is the new bottleneck.
• Which AI applications deliver early ROI.
• How data governance impacts ROI confidence.
• Why role-based training is critical before technology investment.
• Strategic recommendations for scaling AI adoption.

Why It Matters for Distributors

Strategic intent is high, with 65% of distributors planning to increase AI investment over the next two years. However, the differentiator in 2026 is execution velocity.

Organizations that prioritize upskilling their workforce and refining their data governance before chasing “moonshot” technologies will create a sustainable competitive advantage that laggards will struggle to replicate.

Memorable Quotes from the reporting

• Leadership buy-in is not the problem- executives have committed. The problem is execution capacity.
• Assess data readiness application by application rather than pursuing
  enterprise-wide data cleanup as a prerequisite to all AI work.

Visual Takeaway

DCKAP Insights

Companies that focus on integration, data governance, and process standardization will steadily move ahead of their peers. It’s not the flashy AI tools that create lasting impact, but the discipline of connecting systems, ensuring data quality, and aligning processes. Those who commit to these areas – often seen as mundane-gain the strongest predictor of technology ROI.

In simple terms: execution is about building maturity in integration and data governance. When systems talk to each other, when data flows cleanly, and when processes are standardized, every new AI investment delivers greater value. Without this groundwork, even the most advanced tools struggle to show results.

Read this report if

• You are currently stuck in the “pilot phase” and struggling to scale AI applications across your organization.
• You are facing significant internal resistance or a skills gap within your workforce.
• You want to prioritize technology investments based on proven ROI potential and implementation complexity.

Who Should Read It

Executive Leadership: 57% of respondents, including C-suite leaders with budget authority.
Operations Managers: Those focused on warehouse efficiency and workflow automation.
IT & Sales/Marketing Leaders: Professionals tasked with implementing customer-facing AI and cybersecurity.

Access the report

Report: State of AI in Distribution 2026
Publisher: Distribution Strategy Group