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BCG says industrial AI leaders grow revenues more than twice as fast as laggards
BCG says industrial companies leading in AI grew revenue more than twice as fast as sector laggards from 2022 to 2025. Its modeling estimates that fully AI-first companies in three industrial subsectors could raise EBIT margins by 2.5 to 5.
AI.info Team · Written with AI · fact-checked ·
Boston Consulting Group says industrial companies leading in AI grew revenue more than twice as fast as sector laggards from 2022 to 2025, and delivered roughly double the three-year total shareholder return. The firm’s new analysis argues that the gap is between businesses that reorganize operations around AI and those that add tools to existing work without changing how the organization operates.
The findings appear in a report based on BCG’s Applied AI Index 2026, a survey of 1,330 senior executives across more than 20 sectors, alongside modeling of potential financial effects in chemicals, aerospace and defense, and automotive. BCG says AI leaders also achieve more than twice the share of AI-enabled cost savings.
Redesigning work, not just adding tools
BCG calls redesigning processes, functions and operating models with AI at the center “reshaping.” Its contrasting category, “deploying,” refers to adding tools such as copilots to individual workflows while leaving the organization unchanged.
The firm estimates that deploying AI can save individual workers 10% to 15% of their task time. Reshaping core functions and processes, by comparison, can deliver a 30% to 50% improvement in efficiency and effectiveness, according to BCG.
Most industrial companies remain at the deploying stage, the report says, and only a few have dedicated, multiyear AI transformation programs. Citing US Census Bureau data, BCG says almost 70% of industrial companies in the United States that adopt AI make no organizational, data or process changes, while only 12% build new workflows.
Modeled margin gains differ by subsector
BCG modeled the potential effect of becoming AI-first in three industrial subsectors. For large, global, predominantly strong-performing chemical companies, the analysis estimates an EBIT margin improvement of approximately 2.5 to 4.5 percentage points.
In aerospace and defense, established AI-first players could improve EBIT margins by up to 3.3 percentage points in original equipment manufacturing operations and 5.6 percentage points in aftermarket operations at full maturity, BCG says. For established automotive manufacturers, it models a long-term gain of approximately 3 to 5 percentage points, with sourcing and research and development accounting for much of the potential value.
BCG describes the figures as illustrative modeling of established companies after comprehensive AI transformations, not forecasts or projections for individual companies.
Data and trust hurdles
Only 12% of industrial companies have the data capabilities BCG considers necessary to be future-built for AI, compared with an average of 18% in other sectors. The report identifies the largest gap in data strategy and points to siloed information, undocumented expertise held by senior managers, and multitiered supply chains as challenges.
Safety and durability requirements also mean companies must set a high bar before giving AI agents decision-making authority, the report says. BCG proposes an “enterprise cortex,” a layer in the AI technology stack that holds business rules, decision logic and operational context to guide agents and help avoid what it calls “cognitive lock-in” to external models.
The report also recommends building trust in stages: agents would advise first, then act with approval, and only later act independently within defined limits. BCG’s five priorities for industrial leaders include setting ambitious business-wide AI targets, making CEOs and boards responsible for the transformation, redesigning workflows around people and agents, managing the enterprise cortex as a strategic asset, and helping employees adopt new ways of working.
Carsten Schaetzberger, a BCG managing director and senior partner and report coauthor, said: “Industrial companies won't unlock AI's full potential simply by putting copilots in the hands of engineers and planners.” He said the opportunity is to rethink how plants operate, aircraft are maintained and production is planned.