Industrial legacy companies (those long-established manufacturers, suppliers, and service providers) are the backbone of the American economy. Yet many are struggling to keep up in a world rapidly transformed by data, automation, and artificial intelligence (AI). Outdated systems, analog workflows, and fragmented data architectures limit scalability and operational efficiency.

According to a 2024 Deloitte study, over 70% of industrial companies report that their digital transformation efforts are lagging due to legacy infrastructure and workforce resistance.

While newer entrants embrace AI to drive predictive maintenance, supply chain optimization, and quality control, legacy firms are increasingly at risk of being outpaced. The cost of doing nothing is steep: inefficiencies, declining market relevance, and reduced investor interest.

What’s more, these companies are sitting on a treasure trove of data accumulated over decades - data that is often underutilized or locked in silos. Without modernization, that data remains inert.

In a time when AI is expected to contribute over $15.7 trillion to the global economy by 2030 (PwC), legacy firms that fail to activate their data risk becoming obsolete.

AI Is the Key to Unlocking Value

Here’s the good news: legacy industrial companies are prime candidates for AI transformation. With deep operational history, established customer bases, and sector-specific know-how, they have the foundational ingredients to leapfrog into the next era of industrial growth—if paired with the right technology.

1. AI for Predictive Maintenance

Legacy firms often operate heavy machinery with long service lives. AI tools can predict failures before they happen by analyzing sensor data, leading to cost reductions of up to 40% in unplanned downtime (McKinsey, 2023).

2. AI for Process Optimization

Industrial AI models trained on historical production data can identify bottlenecks and adjust workflows in real time. According to BCG, AI-driven process improvements can boost productivity by 20-30% in manufacturing environments.

3. Supply Chain Resilience

Legacy supply chains are complex and prone to disruption. AI enables dynamic risk assessment, inventory forecasting, and routing adjustments. A Gartner survey found that AI-enabled supply chains were 35% faster and 30% more cost-efficient post-pandemic.

4. Computer Vision for Quality Control

AI-powered computer vision systems are replacing manual inspections, dramatically increasing precision. In industrial testing, this has been shown to reduce defect rates by up to 90% (MIT Technology Review, 2023).

5. Talent Augmentation, Not Replacement

Rather than displacing experienced workers, AI enhances their capabilities. Augmented intelligence tools provide real-time recommendations, allowing skilled technicians to make faster, more informed decisions, preserving institutional knowledge while boosting output.

6. AI to Reduce Workforce Burnout

Like virtual nursing in healthcare, AI can ease the burden on industrial workers. By automating repetitive tasks and streamlining decision-making, AI reduces physical and cognitive strain, helping companies retain experienced talent and attract new workers to a modernized environment.

Untapped Upside

Industrial legacy companies that integrate AI early will command a premium. A recent Bain report shows that industrial firms with embedded AI capabilities are now trading at 20–25% higher valuation multiples than peers.

We believe these firms are undervalued gems. Our investment strategy focuses on infusing legacy operations with AI-powered tools, from predictive analytics to automated procurement systems, to unlock operational efficiencies and drive exponential growth.

The next wave of industrial innovation isn’t coming from startups alone, it’s already embedded in the infrastructure of legacy companies across the Midwest and beyond. The winners will be those who modernize early, invest in smart tools, and embrace AI as a core capability.

For private equity, technologists, and operators alike, legacy industrial companies represent a rare combination: proven business models + unrealized digital potential. That’s a goldmine.

Sources

• Deloitte, 2024 Manufacturing Industry Outlook https://www2.deloitte.com/us/en/pages/manufacturing/articles/manufacturing-industry-outlook.html
• PwC, Sizing the Prize: What’s the real value of AI for your business and how can you capitalise?
  https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html
• McKinsey & Company, The Next Normal in Industrial AI
  https://www.mckinsey.com/industries/advanced-electronics/our-insights/the-next-normal-in-industrial-ai
• CB Insights, State of AI Q1 2024 Report
  https://www.cbinsights.com/research/report/ai-trends-q1-2024/
• Accenture, AI in Industry X: Unlocking Trapped Value
  https://www.accenture.com/us-en/insights/industry-x/ai-industrial-value
• World Economic Forum, How AI Is Transforming the Future of Manufacturing
  https://www.weforum.org/agenda/2023/11/ai-manufacturing-industrial-future/