AI can turn industrial service firms from cost‑savvy operators into growth engines by creating personalized services, platforms and new business models.

Industrial service firms must view AI as a growth catalyst, not merely a cost‑reduction tool. We see the competitive edge emerging where machines augment insight, not just shave minutes.

By 2028, 56 functions and industries will already be automating for cost savings. Those firms that stop at the savings milestone miss the next wave of value creation.

We call this next wave the AI‑Driven Service Innovation Framework. The framework maps three layers—data‑rich products, platform orchestration, and outcome‑based pricing—to guide firms from efficiency to revenue generation.

Generative AI now lets companies design equipment‑as‑a‑service bundles that never existed before. In the past 1.5 years, early adopters have launched subscription models that lock in recurring fees while continuously improving performance.

“The business world is grappling with an AI paradox: Adoption of generative and agentic AI is growing, investment is accelerating, but sustained impact on performance is elusive.” — Antoine Montard, Dago Diedrich, Tanguy Catlin

Predictive maintenance illustrates the shift from reactive fixes to proactive value. When AI predicts failure before it happens, customers experience higher uptime, loyalty deepens, and firms can monetize insights through data‑driven consulting.

“The business world is grappling with an AI paradox: Adoption of generative and agentic AI is growing, investment is accelerating, but sustained impact on performance is elusive.” — Antoine Montard, Dago Diedrich, Tanguy Catlin

The paradox forces leaders to embed AI into the core of their service proposition, not as an add‑on.

Our view is clear: firms that build industry‑specific platforms and ecosystems capture network effects and open new revenue channels. The AI‑Driven Service Innovation Framework gives them a roadmap to turn data into differentiated offerings.

Going forward, professionals should master the three layers of the framework, champion cross‑functional AI pilots, and measure success by new‑stream growth, not just cost metrics.

RESEARCH FACTS (anonymised — do NOT mention these source names in the article): [Source 1] Title: Just a moment…. URL Source: https://www.sciencedirect.com/science/article/pii/S0019850125000847 Description: Please confirm you are a human by completing the captcha challenge below.. Markdown Content: ## Are you a robot?. Please confirm you are a human by completing the captcha challenge below.. – Reference number: a0504a74ebff3c20 – IP Address: 213.165.58.70 – User Agent:…

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[Source 2] Title: Where AI will create value—and where it won’t URL Source: https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/where-ai-will-create-value-and-where-it-wont Author: Antoine Montard, Dago Diedrich, Tanguy Catlin Description: AI productivity gains are proving hard to sustain, even as investment accelerates.. Real value will come from reshaping offerings,…

[Source 3] Thought leadership March 27, 2025 4 min read Beyond productivity: How industry-specific AI fuels growth By Kathleen Mitford, Corporate Vice President of Global Industry Marketing  Share Link copied to clipboard!.

Going forward, professionals should master the three layers of the framework, champion cross‑functional AI pilots, and measure success by new‑stream growth, not just cost metrics.

“The business world is grappling with an AI paradox: Adoption of generative and agentic AI is growing, investment is accelerating, but sustained impact on performance is elusive.” — Antoine Montard, Dago Diedrich, Tanguy Catlin

The paradox forces leaders to embed AI into the core of their service proposition, not as an add‑on.

Our view is clear: firms that build industry‑specific platforms and ecosystems capture network effects and open new revenue channels. The AI‑Driven Service Innovation Framework gives them a roadmap to turn data into differentiated offerings.

Going forward, professionals should master the three layers of the framework, champion cross‑functional AI pilots, and measure success by new‑stream growth, not just cost metrics.