By Mike Carney, President of Quality Hydraulics and Pneumatics, Inc., and Sami Senapathy, Endeavor.ai
What AI Means for Hydraulic Distributors and Manufacturing from the Perspective of an AI CEO and a Distribution CEO
AI is no longer a future topic for manufacturing and hydraulic distribution. It is already showing up in quoting, order entry, documentation, forecasting, pricing, and customer support. To understand what that really means, we asked the same questions to two people looking at the industry from very different angles: Mike Carney, President of Quality Hydraulics & Pneumatics, and Sami Senapathy of Endeavor.ai. Their answers do not always sound the same, but together they paint a useful picture of where AI is headed and what companies should do next.
Can you retire before AI impacts your job?
Mike’s answer is the bluntest in the entire interview: no. In his view, AI is already affecting work, and the real question is not whether it arrives, but how intelligently companies adopt it. He sees meaningful use cases today in order entry, predictive maintenance, quality inspection, and engineering support, with broader mainstream adoption likely over the next two to five years as companies work through legacy systems, integration issues, training, and regulation.
Sami agrees the change is already underway, but frames it through adoption. He says the timing depends in part on how tech-forward a company is, and notes that even workers close to retirement are using AI tools successfully when those tools are simple and accessible. His point is that AI is not just for digital natives. If the software is designed well, the barrier to adoption drops quickly.
Is AI going to help jobs or hurt them?
On this question, both CEOs land in roughly the same place: AI will help the people and companies that use it well. Mike believes AI will strip away repetitive administrative work like quoting, documentation, documentation review, forecasting, and order entry. But he is equally clear about what it will not replace: accountability, troubleshooting, customer trust, and relationships. In his view, AI helps the job, but it does not replace the person responsible for the result.
Sami pushes that idea even further. He describes AI as giving every employee a kind of co-worker that handles the least valuable parts of the day, like forms, scanning, and manual data entry. That creates room for employees to do more valuable work such as building customer relationships, finding opportunities, and improving service. His argument is that AI should not trap good people in low-value work when it can free them up to contribute more and earn more.
Which roles will change first?
Mike sees the earliest disruption in roles built around repeatable tasks: order entry, basic engineering work, purchasing, accounting, and manual reporting. At the same time, he believes highly technical, customer-facing, and safety-critical responsibilities will remain human-led because they depend on experience, judgment, and oversight.
Sami’s answer tracks closely, but adds a commercial angle. He believes inside sales reps, customer service staff, and other inside roles will feel the first wave as AI takes over manual processing. After that, he sees AI helping field sales identify leads, surface complementary products, and stay better organized. He even expects executives to gain better visibility into strategic decisions, such as which customers and product lines deserve the most attention.
Will engineers still matter, or does AI eventually take over?
This is where Mike sounds most like an industry veteran. He says engineers will absolutely still be needed to design hydraulic circuits in 2030. AI may help draft and optimize early versions, but final validation, safety review, testing, system integration, and accountability will remain human responsibilities. He makes the same point when discussing AI-assisted fluid simulation: the tools may already exist, but knowledgeable engineers and real-world testing still have to validate the result.
Sami is more cautious about predicting exactly where design work will be by 2030. He is bullish on AI’s ability to handle unstructured business data like emails, PDFs, spreadsheets, and calls, but less certain about where simulation and hydraulic circuit modeling will land. What he is firm on is the human-in-the-loop principle. In his view, AI should function more like an “Iron Man suit” than an autonomous decision-maker: it can amplify people, but people still carry the responsibility.
Does AI justify the cost?
Mike’s answer is practical. He believes AI will justify the cost if it delivers faster and more accurate order entry, improved inventory decisions, reduced customer downtime, fewer engineering errors, and better documentation. But he also points out that software licenses are only part of the equation. The larger investment is often integration, cybersecurity, training, and process redesign. Most mid-sized companies, he says, will start small and scale once the return becomes clear.
Sami is even more direct: AI is worth it only when it solves a specific business problem. A generic chatbot will not transform a manufacturer or distributor overnight. His case for AI is based on tightly integrated, industry-specific tools that automate work like sales order entry and quoting while also improving pricing, lead generation, and upsell opportunities. Just as importantly, he stresses training and change management, arguing that the value comes from the full solution, not just the software.
So what happens next?
Mike sees the near future as one of copilots: tools that assist with engineering documentation, coding support, quoting, troubleshooting, and supply chain work. In five years, he expects AI to show up more deeply in plant operations and planning. In ten years, he can imagine certain constrained processes becoming semi-autonomous, but only with strong human oversight.
Sami sees the next wave arriving even faster on the commercial side. Today’s automation is centered on order entry and quoting. The next phase, he says, is revenue-focused intelligence: price optimization, upsell and cross-sell recommendations, and lead generation. In other words, AI will not just cut cost. It will increasingly be asked to grow the business.
The real takeaway
The most interesting part of these two perspectives is not where they disagree. It is where they align. Neither sees AI as a wholesale replacement for people. Both see it as a force multiplier. Both believe routine work is the first target. Both believe human oversight remains essential. And both imply that the winners will not be the companies that talk the most about AI, but the ones that use it to make work faster, smarter, and more valuable.
For hydraulic distributors and manufacturers, that may be the clearest answer of all: AI is coming for the repetitive work first. What companies do with the time, insight, and capacity it creates will determine who benefits.
To explore this topic further, we invite you to email us at info@qualityhydraulics.com.
