2. Which growth levers are moving the P&L?
Corporate venture building and price optimization stand out as the growth levers most often associated with disproportionate profit and loss (P&L) impact. Manufacturers appear to be looking beyond traditional scale plays toward new business models, sharper commercial decisions and faster ways to test emerging opportunities.
In an environment shaped by tariff exposure, input-cost volatility, supply chain redesign and shifting customer expectations, pricing is becoming a growth capability. Manufacturers that can connect cost, demand, customer value and channel insight can protect margin while identifying where customers are willing to pay for differentiated performance, reliability or service.
Key takeaway: The most promising levers are not isolated initiatives. Venture building, pricing and partnerships require manufacturers to coordinate strategy, capital allocation, data, operations and commercial execution.
3. Why is AI adoption not yet translating into full growth impact?
AI is central to the industrial growth agenda, but the survey points to a trust-and-impact gap. About 88% of companies are either piloting or fully executing AI for growth strategy and decision-making, yet many applications remain concentrated in efficiency and productivity rather than growth-shaping decisions.
Industrial leaders are also more cautious than peers. While 78% of respondents across industries see AI as a positive factor for growth, only 71% of industrial manufacturing leaders say the same and 24% see AI as creating downside risk, compared with 16% overall. Manufacturers are also less likely to be fully executing AI to improve customer service or interaction: 38% of industrial manufacturing respondents vs. 51% of respondents in the total sample.
The opportunity is not simply to automate tasks. Manufacturers can use AI to improve engineering productivity, reduce downtime, strengthen demand sensing, personalize service, optimize pricing and unlock new value from connected products. The challenge is moving from operational efficiency gains to growth-shaping decisions.
Key takeaway: Manufacturers appear to be using AI as an enabler of operational and commercial resilience. The challenge is that operational improvements alone rarely translate directly into revenue growth unless paired with changes to pricing, customer engagement, service models and capital allocation.
4. What explains the gap between confidence and execution?
The most interesting finding may be the industrial manufacturing paradox. Leaders are confident, active and disciplined. Ninety-six percent say they can focus on the most critical growth initiatives and roughly 90% regularly define intended outcomes. Fifty-three percent strongly agree that their organizations know how to leverage data and AI to enable growth. Yet only 54% say more than half of their initiatives achieved expected results.
Taken together, these findings point to a potential explanation that manufacturers are stronger at optimizing operations than transforming operating models. Skills gaps, risk and compliance concerns, outdated technology and infrastructure, decision paralysis, lack of agility, siloed data and budget constraints make it harder to scale new growth initiatives across the enterprise.
Key takeaway: Manufacturers are discovering that operational excellence does not automatically translate into growth excellence. Their challenge is converting ideas, technology and partnerships into measurable business outcomes.
5. What should industrial manufacturers do next?
Manufacturing leaders can build on their ability to adapt to carry out transformations for growth decision-making and execution, especially in five key areas:
- Build a digital thread across engineering, manufacturing, supply chain, sales and service to connect operational insight with growth decisions.
- Fund growth platforms not disconnected pilots, reallocating capital and talent toward initiatives with clear paths to scale and measurable returns.
- Rewire commercial decision-making around pricing, customer value, service and aftermarket growth to translate operational capabilities into revenue and margin.
- Treat risk and compliance as growth enablers by embedding governance early enough to accelerate rather than constrain innovation.
- Use ecosystems, partnerships and acquisitions to accelerate capability building where developing capabilities internally would limit speed to market.
Key takeaway: The manufacturers that stand to grow fastest will be those that build adaptive operating models that combine AI, pricing, partnerships and innovation into a single growth system rather than managing them as separate initiatives.