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    Home»AI & Automation»GS1 US Study Finds AI and Automation Investments Are Outpacing Supply Chain Data Readiness
    AI & Automation

    GS1 US Study Finds AI and Automation Investments Are Outpacing Supply Chain Data Readiness

    myappsplusBy myappsplusNovember 4, 2026002 Mins Read
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    GS1 US Study Finds AI and Automation Investments Are Outpacing Supply Chain Data Readiness
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    This is a paid press release. Contact the press release distributor directly with any inquiries.

    GS1 US Study Finds AI and Automation Investments Are Outpacing Supply Chain Data Readiness

    Nearly 60% of Surveyed Organizations Report Advanced Automation or AI Use, Yet Only 38% Report Centralized, Real-Time Data Integration

    EWING, N.J., Nov. 3, 2026 /PRNewswire/ — A new GS1 US study, The Supply Chain Readiness Gap, reveals that many organizations are investing in AI and automation faster than they are building the trusted, integrated data foundation needed to realize the full value of those investments. While nearly 60% of surveyed organizations have automated most supply chain processes or implemented artificial intelligence (AI) and machine learning technologies, only 38% report centralized systems that collect and integrate data in real time. Meanwhile, 32% still rely on manually integrating data from multiple sources, creating bottlenecks that limit visibility, slow decision-making and hinder growth.

    The findings point to a broader risk: Technology investments can stall when the underlying data foundation is fragmented. Although organizations continue to invest in innovation, 41% say they can successfully pilot new technologies but struggle to scale them across their operations. Data fragmentation is among the most significant barriers to innovation, cited by 62% of respondents, second only to lack of funding (63%).

    The research also provides a benchmark for organizations to assess their supply chain readiness and identify the capabilities needed to move from isolated technology investments to enterprise-wide scale. Based on capabilities across data integration, governance, automation, collaboration and standards adoption, respondents were grouped into three maturity tiers: 20% high maturity, 72% medium maturity and 8% low maturity.

    High-maturity organizations distinguish themselves in several key areas:

    • Data integration: 81% report centralized, real-time data integration, compared with 38% of all respondents.

    • Data governance: 85% report a clear and actively executed governance strategy, compared with just 13% of low-maturity organizations.

    • Partner collaboration: 89% report highly effective external collaboration, compared with 59% of the overall sample.

    • Internal alignment: 78% report strong internal alignment, compared with 50% of all respondents.

    These capabilities are also associated with stronger business outcomes, reinforcing that data readiness is a business imperative, not simply an operational concern. High-maturity organizations are more likely to report easier regulatory compliance (60%), reduced costs (52%) and faster time to market (46%).

    Automation finds investments outpacing Study
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