An Interview With Chad Silverstein
Using Generative AI to Accelerate the Transition to a Paperless Operation: In conversations we have with manufacturing companies, a recurring theme emerges when discussing their transition to a paperless operation: the largest cost and burden often lies in the time and effort required to digitize existing paper-based materials.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Chris Kuntz.
Chris is the VP of Strategic Operations at Augmentir, where he oversees the planning and execution of the company’s go-to-market strategy. Chris has over 20 years of experience in high tech solution delivery, marketing, business development, and consulting in the industrial software sector. Previously, Chris held executive positions in marketing and business development at multiple successful software companies.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
I’ve been an entrepreneur for years. I started my career as a mechanical engineer, but quickly transitioned into computer science and internet technology. I’ve been fortunate enough to be a part of several successful technology startups, most of them in the manufacturing sector, and I have been a part of a great team who have built pioneering technology to solve some of the biggest issues in manufacturing. This journey led me to my current role as VP of Strategic Operations at Augmentir, where we’re applying AI to address some of the biggest challenges in manufacturing, including the skilled labor shortage..
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
One of Augmentir’s genAI assistant Augie’s most impressive capabilities is breaking down language barriers in industrial settings. Augie doesn’t just retrieve information — it contextually adapts to the user’s language needs. For example, when a worker at Colgate (a major customer of ours) needs troubleshooting guidance for a toothpaste manufacturing machine, Augie can access technical documentation written in English and automatically translate it to Vietnamese if that’s the worker’s preferred language. This context-aware translation happens seamlessly, making critical information accessible regardless of language differences.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Vision, resilience, and adaptability. I’ve been fortunate to be part of a team of serial entrepreneurs, and building pioneering technologies that have stood the test of time and delivered transformational results for our customers requires all three of these traits.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
As a company, we use AI internally across our organization — marketing, sales, customer support, and product development, and have benefited from some great efficiencies, and since day one, we’ve applied this to the technology we build — as an AI-first company, our product was built from the ground up on an AI foundation.
At Augmentir, we’ve focused on addressing some of manufacturing’s most fundamental business challenges: operational efficiency, workforce development, and productivity. Manufacturing companies today are facing unprecedented pressures to modernize their operations, while dealing with significant labor constraints and skills gaps.
Our solution leverages AI-powered connected worker platforms to transform how manufacturers train and support their frontline workers. Let me share a concrete example: When manufacturers implement our AI-driven platform, it analyzes the enormous amounts of operational data they generate — manufacturing is actually the most data-prolific industry, producing 1.9 petabytes annually. Our system turns this data into actionable insights for personalized worker training and support.
The platform acts as a ‘digital coach,’ providing real-time, personalized guidance to workers exactly when they need it. This has resulted in several tangible benefits for our clients: faster onboarding of new employees, reduced need for expert interventions, and systematic closure of skills gaps across their workforce. Instead of replacing workers, our AI solution augments their capabilities by providing targeted training content and support during their actual workflow processes.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
The biggest misconception I encounter is that AI will replace human workers. This couldn’t be further from the truth. What we’ve found is that AI serves as an intelligent collaboration tool that augments human capabilities rather than replaces them. Another common misconception is that implementing AI requires perfect data from the start. While data is indeed the lifeblood of AI, many manufacturers believe they need to have their entire data ecosystem perfectly organized before they can begin leveraging AI technologies. The reality is that AI implementation can be approached systematically, starting with specific use cases like worker training and support, while gradually building more comprehensive data capabilities.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
The most significant impact of AI today lies in its ability to empower human workers rather than replace them. In manufacturing, we’re seeing AI transform from a tool that simply optimizes individual processes into something that can fundamentally enhance human capabilities and decision-making across entire organizations. Using the vast amounts of data that manufacturing operations generate, AI can deliver targeted insights and guidance that help workers perform their jobs more effectively, safely, and confidently. This isn’t about automation replacing jobs — it’s about creating an intelligent collaboration tool that makes human workers more capable and efficient in their roles.
Ok, let’s dive deeper. Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges. If possible, please share examples or stories for each.
1. Using Generative AI to Accelerate the Transition to a Paperless Operation:
In conversations we have with manufacturing companies, a recurring theme emerges when discussing their transition to a paperless operation: the largest cost and burden often lies in the time and effort required to digitize existing paper-based materials.
Standard Operating Procedures (SOPs), work instructions, and checklists are typically built over years, representing a significant repository of organizational knowledge. Converting these into digital formats while maintaining accuracy and accessibility can be daunting.
Customers frequently express concerns about the resource-intensive nature of this transformation. It’s not just about scanning documents; it’s about rethinking and structuring them for digital workflows. Many find themselves needing to allocate substantial time to review, update, and adapt content to ensure it aligns with current operational realities and integrates seamlessly into new platforms.
This challenge is real for any industrial company undergoing a digital transformation. It also represents an opportunity, and this is exactly why we created Augie. We have a large food & beverage manufacturer that has reduced their initial digitization efforts by 68% — from months down to days.
2. Using AI as a Training Assistant to Address the Skills Gap in Manufacturing:
In another example, one of our customers is using Augie, our Gen AI assistant, for frontline worker training. They were able to use Augie to digitize their seldom-used safety placards and turn them into digital quizzes and One Point Lessons that are integrated into digital work instructions. This has resulted in a 12% decrease in safety incidents in the first 9 months — a significant impact.
3. Using AI as a Troubleshooting Assistant:
Another example is in troubleshooting on the shop floor — resolving unplanned equipment issues quickly to avoid unnecessary downtime. Faced with the reality of a less-skilled and less-experienced workforce, having the tacit knowledge required to quickly resolve issues is a challenge that many frontline workers experience. We have a large consumer goods manufacturer who is using Augie as a troubleshooting assistant — essentially acting as a digital SME, allowing workers to solve problems faster with instant access to context-aware information and personalized guidance in the flow of work.
4. Using AI to digitally capture tribal knowledge and convert to a corporate asset:
Augie can summarize the exchange of tribal knowledge via collaboration and convert these to scalable, curated digital assets that can be shared instantly across your organization.
5.Using AI for Continuous Improvement on the shop floor:
Much like AI has historically been used to improve the efficiency and output of machines, we can do the same with our frontline workforce. The Augie data assistant understands and summarizes your operational data, generates reports, and provides insights into continuous improvement opportunities.
From a Continuous Improvement standpoint, Augie is being used by one of our customers to help identify:
- Areas for content improvement, and make those improvements (e.g. measure training effectiveness)
- Identify skills gaps and targeted training needs
- Measure and improve workforce effectiveness
- Improve capacity planning
Overall, really helping them forecast more accurately, and optimize production.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
For smaller businesses, particularly in manufacturing, AI adoption doesn’t have to be complex or cost-prohibitive. Modern software platforms are specifically designed with SMMs in mind, featuring extensibility solutions that can be implemented in days or weeks rather than months or years. The key is to start with focused, practical applications that deliver immediate value. These platforms are designed to be user-friendly and accessible, requiring minimal technical expertise or infrastructure. The ROI becomes evident quickly through improved operational efficiency, better training outcomes, and enhanced worker productivity. Remember, you don’t need perfect systems or extensive technical resources to start — the latest AI solutions are built to work with existing operations and can scale as your business grows.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
I’d encourage business leaders to shift their perspective from viewing AI as a replacement for workers to seeing it as a tool for workforce empowerment. The data clearly shows that manufacturers who embrace AI-powered solutions are seeing tangible benefits in workforce development, safety, operational efficiency, and employee retention. The reality is that AI is about augmenting your workforce’s capabilities and helping them become more efficient, skilled, and satisfied in their roles. With the current skilled labor shortage, we can’t afford to let misconceptions hold us back from tools that can help develop and retain talent.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
One of the most fascinating aspects of AI that I (and I think we all) have witnessed is the pace of innovation and development — we’re not looking at 5–10 years anymore, but rather 5–10 months. So what will things look like just 1 year from now? What’s truly exciting is how quickly we’re progressing, with new opportunities and business models materializing faster than ever before.
The rapid ascent of Generative AI has been fascinating to watch, and now with the promise of Agentic AI in industrial settings, the future looks even more promising. The lines are blurring between Generative and Agentic AI — with cognitive agents, personalized copilots, more actionable insights, and autonomous operations emerging as just one example of this swift evolution.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
From what we’ve seen in manufacturing, AI is actually strengthening relationships across the board by creating more capable, engaged workforces. For frontline employees, AI-powered platforms provide personalized training and support that helps them excel in their roles, leading to higher job satisfaction and retention. Instead of feeling threatened by the technology, workers appreciate having an intelligent ‘digital coach’ that enhances their capabilities and supports their professional growth. For customers, this translates to better quality, consistency, and service since they’re working with more skilled and confident employees. As for the broader community, we’re seeing AI help address critical workforce development challenges. By making advanced training and support more accessible, we’re helping create more opportunities for workers to develop valuable skills and build sustainable careers in manufacturing.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
I think we are already doing this at Augmentir — and I’m excited to be part of it — helping to shape the future workforce in manufacturing.
How can our readers further follow you online?
The best way to connect with me is either LinkedIn or via email — [email protected].
This was great. Thank you so much for the time you spent sharing with us.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Chris Kuntz of Augmentir On How Artificial Intelligence Can Solve Business Problems was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.