Global disruptions and corporate responses

In the last five years firms have faced a wave of shocks—from pandemics and armed conflict to fractured supplier networks and macroeconomic upheaval. Boards and operational leaders have reacted by prioritizing risk preparedness, investing in cybersecurity and shoring up data infrastructure.

Despite those efforts, many organizations still operate with limited ability to reroute or reconfigure their supply chains in real time.

Operational rigidity and measurable declines in resilience

That structural inflexibility has translated into slower reactions, longer recoveries and rising costs, exposing a critical weakness in operational resilience. Accenture’s research "Resilience Redefined" documents a 4% drop in operational resilience between 2018 and 2024.

Worse, 91% of companies that were in the bottom quartile before the pandemic remain there today. Those firms tend to run cost-optimized operating models that lack adaptability, and fewer than 15% consistently achieve sustained profitable growth as a result.

People resilience and workforce challenges

On the workforce front, the pandemic reshaped competitive positions. Only 38% of companies that led on people resilience before the pandemic have kept that advantage. Other organizations have overtaken them by reducing turnover, upskilling staff and redesigning roles for agility.

Many lagging firms continue to use static job structures, intermittent training and limited human–AI teaming, while losing institutional knowledge because of an aging workforce, shorter tenures and skill shortages.

Executive perspectives on operating model adaptability

Senior leaders are aware of the gap: 69% of C-suite executives say their operating models cannot keep pace with change, and 88% expect disruption to increase going forward. Without decisive action, companies risk longer recovery periods, deeper financial hits and declining market relevance.

The current state of autonomy in supply chains

Advances in artificial intelligence make autonomy a practical path to greater resilience. Yet supply chains remain largely manual: on average they score just 21% on an autonomy index that runs from 0% (fully manual) to 100% (fully autonomous).

True autonomy means intelligent systems that do more than automate tasks—they make fast, accurate decisions at scale and can detect, react and reconfigure when suppliers fail, tariffs change or cyberattacks occur.

Accenture groups typical supply chain processes into nine clusters to track progress. Examples include:

• Make which covers production, assembly and packaging
• Quality Control and Customer Support which are among the clusters adopting autonomy more quickly

Most activities across these clusters remain at low levels of automation and delegation, although manufacturers—such as automakers using AI-driven robotic assembly lines—are accelerating adoption.

Targets for autonomy and expected performance improvements

Supply chain leaders are setting ambitious targets: 66% of executives plan to increase supply chain autonomy, and roughly 40% aim for systems that handle the majority of operational decisions.

Those companies project substantial performance gains: a 62% reduction in reaction time to disruptions and a 60% reduction in recovery time. To illustrate, the typical reaction time today is 11 days; higher autonomy could cut that to about four days.

Leaders also expect commercial and sustainability benefits, including a 5% increase in On-Time In-Full (OTIF) delivery and a 4% decrease in Cost of Goods Sold (COGS). According to nearly 40% of respondents, autonomy could also deliver a 27% reduction in order lead times, a 25% rise in labor productivity and up to a 16% cut in carbon emissions—improvements that would boost margins such as EBITDA and ROCE.

Accenture’s analysis finds firms with the strongest operational resilience achieve EBIT margins nearly three percentage points above peers.

Agentic AI and the next wave of capabilities

Beyond rules-based automation, agentic AI represents the next frontier. These systems can independently orchestrate complex, dynamic decisions in real time without waiting for human input, compressing decision cycles, handling exceptions at scale and continuously adapting to new conditions.

When combined with autonomy across operations, agentic AI can accelerate response times and expand the scope of decisions that intelligent systems can take on.

Human augmentation and sector differences

Autonomy is positioned as augmentation, not replacement. Only 1% of executives expect a meaningful reduction in headcount due to automation. Instead, AI changes how work is performed: employees gain clearer ownership, see stronger links between their work and outcomes, and focus on higher-value tasks supported by intelligent tools—reviving skilled craftsmanship with digital enhancements.

Progress varies by industry. Discrete manufacturing sectors such as automotive, semiconductors and aerospace are farther along because of long-running automation investments. Process industries like oil & gas and chemicals tend to advance more slowly, constrained by legacy systems and complex compliance requirements.

Barriers to adoption and leadership actions

Organizations face several hurdles: inconsistent data quality across the supply chain, cybersecurity risks, gaps in process maturity and limited employee trust in AI-driven decisions. These issues slow adoption of autonomy and agentic AI.

Leaders are responding by building robust data foundations, deploying adaptable AI technology stacks and running pilots—often with generative and agentic AI—under clear guardrails. The most impactful shift is redesigning roles and processes to enable effective human–machine collaboration.

Investment needs and preparing for future technologies

Transitioning to more autonomous supply chains requires commitment: Accenture estimates an average investment of about 0.9% of revenue per year. While that cost is material, the potential returns span agility, efficiency, profitability and sustainability.

Autonomous systems also prepare organizations for future advances such as artificial general intelligence and quantum computing. By centering on outcome-based objectives and encouraging human/machine cooperation, companies can unlock higher efficiency and resilience across end-to-end supply chains.

Authors and source attribution

This analysis draws on Accenture research, including the report "Resilience Redefined." The piece was authored by Kris Timmermans, Global Supply Chain and Operations Lead at Accenture; Max Blanchet, Global Supply Chain & Operations Strategy Lead at Accenture; and Stephen Meyer, Principal Director, Supply Chain & Operations, Accenture Research.