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Supercharging TWI with Augmentir’s Connected Worker Software

For more than 80 years, Training Within Industry (TWI) has been a proven foundation for building skilled, capable workforces. Organizations in manufacturing, food and beverage, and other industrial sectors have relied on its structured approach to Job Instruction (JI), Job Methods (JM), Job Relations (JR), and Job Safety (JS) to ensure quality, productivity, and employee […]

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For more than 80 years, Training Within Industry (TWI) has been a proven foundation for building skilled, capable workforces. Organizations in manufacturing, food and beverage, and other industrial sectors have relied on its structured approach to Job Instruction (JI), Job Methods (JM), Job Relations (JR), and Job Safety (JS) to ensure quality, productivity, and employee engagement.

supercharging training within industry with twi software from augmentir

At Augmentir, we’re not here to reinvent TWI. We’re here to amplify it—to give it the tools it needs to thrive in the modern, connected, data-driven world.

Recently, a food and beverage company that has followed TWI principles for over 20 years shared with us how Augmentir’s Connected Worker software is helping them unlock value they didn’t realize they were losing.

Our TWI software builds on TWI’s four pillars by combining their time-tested structure with modern digital capabilities—AI-driven personalization, real-time data capture, integrated safety workflows, and collaborative improvement tools—that close long-standing gaps, preserve the integrity of the methodology, and extend its impact across today’s fast-changing industrial landscape.

Pillar 1: Job Instruction – From Good to Great

One of our client’s first observations was that Job Instruction isn’t as simple as writing a standard operating procedure. Get the structure wrong, and the benefits of TWI start to slip away.

Their feedback? Our ability to configure job instructions exactly to their needs is helping them reclaim value that had been leaking from their process for years. Instead of rigid templates, Augmentir’s TWI software allows Job Instructions to be built and delivered in ways that match the precise structure, flow, and visual cues required for mastery.

Even better, our AI continuously assesses each worker’s knowledge and adapts the training to meet them where they are—so no one sits through irrelevant steps and no one is left behind.

Beyond personalization, our AI agents act as always-on digital trainers. Workers can ask questions in natural language at the moment of need, get step-by-step coaching during unfamiliar tasks, and receive proactive nudges when an agent detects hesitation, errors, or a deviation from the standard. The result is true on-the-job training—where Job Instruction is reinforced every shift, not just during onboarding.

Pillar 2: Job Methods – Continuous Improvement, Powered by the Frontline

In classic TWI, Job Methods is about refining the way work gets done. Our client has seen this pillar transformed with Augmentir.

By enabling workers to contribute improvement ideas at any step of work, they have seen a 20% increase in job improvement recommendations over last year. These aren’t just suggestions—they’re captured, evaluated, and acted on with a closed feedback loop, creating a living system of operational improvement.

Our AI detects variability in work execution and pinpoints where skills gaps exist, driving targeted upskilling opportunities that improve both productivity and consistency.

Pillar 3: Job Relations – Objective Insights that Build Stronger Teams

For TWI, Job Relations is about fostering trust, communication, and engagement. Augmentir’s AI agents continuously monitor skill progression, certification status, and on-the-job performance—giving leaders a real-time view of how each operator is developing, where they’re excelling, and where they need support.

This isn’t about surveillance—it’s about partnership. Supervisors can have objective, meaningful conversations with workers, backed by clear metrics and personalized development paths. Our client reported that this is improving retention, engagement, and happiness scores—and ultimately strengthening the relationship between employees, leaders, and the organization as a whole.

Pillar 4: Job Safety – The Modern Essential

While traditional TWI implies safety as a byproduct of strong training, modern operations demand more. Our client pointed out something powerful:

“Having an employee trained makes them safer. But Augmentir’s ability to tailor training to the specific knowledge of each person makes them even safer.”

With Augmentir, safety becomes a core, trackable element of daily work:

  • Safety prompts embedded directly into digital workflows.
  • Real-time hazard alerts and compliance checks.
  • Data-driven insights to proactively address risks before incidents occur.

By elevating Job Safety to a pillar of its own, organizations can make safety culture measurable, visible, and consistently reinforced.

Extending TWI Software with Custom AI Agents

Every TWI program is unique. The way one organization captures skill progression, validates certifications, or coaches new hires looks very different from the next. That’s why Augmentir’s TWI software and AI Agent Studio gives manufacturers the tools to build their own AI agents—purpose-built for their specific TWI workflows, terminology, and operating standards.

industrial ai agent studio - build custom ai agents for manufacturing

With AI Agent Studio, teams can deploy custom agents that:

  • Track operator skill progression against TWI-defined competencies and surface gaps before they affect quality or safety.
  • Coach new hires through Job Instruction breakdowns, adapting guidance to the worker’s experience level and learning pace.
  • Recertify operators on critical tasks by quizzing them in context, scheduling refreshers, and flagging expirations to supervisors.

Rather than waiting for a vendor roadmap, manufacturers can stand up agents in minutes—turning their hardest-won TWI knowledge into a system that scales across lines, plants, and shifts.

The Future of TWI Software is Connected

TWI’s principles have stood the test of time since their introduction during World War II because they work. But today’s operations are more complex, the pace of change is faster, and the demand for agility is higher than ever.

By combining TWI’s enduring framework with Augmentir’s AI-powered Connected Worker platform, companies can:

  • Deliver Job Instructions that truly fit the work and the worker.
  • Make Job Safety a measurable, proactive outcome.
  • Harness frontline input for continuous improvement at scale.
  • Use objective insights to strengthen relationships and grow talent.

This isn’t about replacing TWI—it’s about giving it the digital muscle to thrive for the next 80 years.

Ready to take TWI further? See how Augmentir’s Connected Worker platform and AI Agent Studio can amplify every pillar of your training program. Book a Demo.

 

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AI in Action: How Hunter Industries Reinvented Workforce Training with AI

Learn how Hunter Industries is transforming workforce training and operational performance using Augmentir’s AI-powered Connected Worker platform to reduce scrap, improve changeovers, and close skills gaps.

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Manufacturers today face a familiar but increasingly urgent challenge: how to train, upskill, and support a less-skilled, less-experienced frontline workforce while maintaining productivity, quality, and operational efficiency. As product complexity increases and experienced workers retire, traditional training methods simply can’t keep pace.

hunter industries transforms training with ai

A recent Assembly Magazine feature highlights how Hunter Industries, a global manufacturer of irrigation and outdoor lighting products, is tackling this challenge head-on using Connected Worker technology powered by Augmentir. The results demonstrate how AI-driven digital tools can transform training from a static process into a measurable, performance-driven strategy.

The Challenge: Complex Operations and Workforce Variability

Hunter Industries operates advanced manufacturing processes, including injection molding and extrusion, where changeovers and setup tasks require precision and expertise. Like many manufacturers, Hunter faced variability in skill levels across shifts and facilities. Tribal knowledge, paper-based instructions, and manual tracking made it difficult to standardize execution and measure training effectiveness.

As operations scale and workforce demographics shift, these challenges become more pronounced:

  • Skills gaps between new and experienced workers
  • Inconsistent execution of standard operating procedures
  • Limited visibility into training effectiveness
  • Downtime and scrap caused by human error
  • Difficulty scaling best practices across teams

Hunter recognized that improving frontline performance required more than digitizing documents—it required a connected, intelligent system that could adapt to workers in real time.

The Solution: AI-Native Connected Worker Platform

By implementing Augmentir’s Connected Worker platform, Hunter Industries digitized and transformed how work is delivered, supported, and optimized on the shop floor.

augmentir ai-native connected worker platform

Augmentir combines:

  • Digital work instructions to standardize processes
  • AI-driven insights to personalize guidance
  • Skills tracking and competency management
  • Mobile-first tools for frontline accessibility
  • Remote collaboration capabilities
  • Generative AI tools to accelerate content creation and knowledge capture

Instead of relying on static PDFs or binders, workers now receive contextual, step-by-step digital guidance tailored to their skill level. The system continuously analyzes performance data to identify where workers may need additional support, helping reduce errors before they impact production.

This shift from reactive troubleshooting to proactive workforce optimization represents a significant evolution in how manufacturers manage training and performance.

Improving Training Effectiveness with Real-Time Insight

One of the most impactful outcomes of Hunter’s deployment is improved visibility into training effectiveness.

Traditionally, manufacturers measure training completion—not training impact. Workers attend sessions, complete certifications, and move on. But do those sessions actually translate to better performance on the floor?

With Augmentir, Hunter can now connect training data directly to operational outcomes. Supervisors gain insight into:

  • How quickly workers complete tasks
  • Where errors occur most frequently
  • Which procedures require additional coaching
  • Whether recently trained employees are performing at expected levels

This real-time feedback loop enables continuous improvement. As noted in the Assembly Magazine article, Hunter’s operations training leadership can now evaluate whether training efforts are delivering measurable results.

“The use of Augmentir within our manufacturing operation highlights our commitment to our people and innovation in the workplace,” says Yunior Murillo, operations training manager at Hunter Industries. “Augmentir’s platform allows our technicians to perform at their best while improving efficiency across our manufacturing departments. Additionally, the operational insights provided by Augmentir’s AI allow us to focus our training efforts on individuals that need them most and intelligently guide our technicians in their day-to-day activities.”

By linking workforce development directly to performance metrics, Hunter has transformed training from a cost center into a strategic lever for operational excellence.

Reducing Scrap, Downtime, and Changeover Time

Beyond training visibility, the platform has driven tangible operational gains.

Standardized digital workflows reduce process variation, ensuring that critical steps are followed consistently. Built-in validation and guidance minimize mistakes that previously led to scrap or rework.

In high-impact areas like injection molding changeovers, this consistency is critical. Even small improvements in setup execution can significantly reduce downtime and improve overall equipment effectiveness (OEE).

Since implementing connected worker technology, Hunter has seen:

  • Reduced scrap rates
  • Decreased unplanned downtime
  • Faster and more consistent changeovers
  • Improved execution across shifts

These improvements demonstrate that workforce enablement directly influences production performance.

Capturing and Scaling Institutional Knowledge

Another key advantage of connected worker platforms is knowledge retention.

Manufacturers across the industry are facing a wave of retirements among experienced workers. When that expertise walks out the door, companies risk losing years of operational know-how.

Augmentir enables Hunter to digitize tribal knowledge and embed it directly into workflows. Experienced operators can contribute insights, tips, and best practices that become part of standardized digital instructions.

Generative AI further accelerates this process by helping convert legacy documents and subject-matter expertise into structured, accessible guidance. This ensures knowledge is preserved and easily shared across facilities and teams.

Expanding Beyond Manufacturing

The success of Hunter’s initial deployment is driving expansion into additional operational areas, including maintenance teams.

Connected Worker technology isn’t limited to production lines. Maintenance, quality assurance, safety, and field service teams all benefit from real-time guidance, skills tracking, and AI-driven performance insights.

By extending the platform across functions, Hunter is building a more agile, data-driven workforce ecosystem.

A Blueprint for Modern Manufacturing

Hunter Industries’ success story reflects a broader shift occurring across industrial organizations. Manufacturers are recognizing that operational excellence starts with workforce excellence.

Connected Worker platforms powered by AI allow companies to:

  • Close skills gaps faster
  • Standardize work across distributed teams
  • Improve quality and productivity
  • Capture and retain critical knowledge
  • Continuously optimize frontline performance

Rather than treating training as a one-time event, organizations can create a living, evolving system that adapts to workers and operations in real time.

The Future of Workforce Enablement

As manufacturing becomes more complex and competitive, companies that invest in intelligent workforce tools will be better positioned to scale, innovate, and outperform.

Hunter Industries’ journey illustrates what’s possible when AI, digital workflows, and skills intelligence come together in a unified platform.

At Augmentir, we’re proud to partner with forward-thinking manufacturers who are redefining how frontline work gets done.

 

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FAQs About AI for Manufacturing Workforce Training

  • How is Hunter Industries using Connected Worker technology to improve workforce training?

    Hunter Industries is using Augmentir’s AI-powered Connected Worker platform to digitize work instructions, personalize training, and provide real-time guidance to frontline workers. By replacing paper-based processes with intelligent digital workflows, Hunter can standardize execution, close skills gaps, and directly connect training efforts to measurable operational performance.

  • What are the benefits of AI-powered Connected Worker platforms in manufacturing?

    AI-powered Connected Worker platforms, like Augmentir, help manufacturers minimize downtime, improve changeover consistency, and accelerate employee onboarding. These systems provide digital work instructions, skills tracking, and performance analytics that allow companies to continuously optimize frontline workforce performance while improving overall equipment effectiveness (OEE).

  • How can manufacturers measure the effectiveness of workforce training?

    With Augmentir, manufacturers can link training data directly to operational outcomes. Instead of only tracking training completion, organizations gain visibility into task completion times, error rates, procedural adherence, and post-training performance metrics. This real-time feedback loop allows companies to continuously improve training programs based on measurable results.

  • How does Connected Worker technology help capture and retain institutional knowledge?

    Connected Worker platforms like Augmentir allow experienced operators to embed best practices, troubleshooting tips, and tribal knowledge directly into digital workflows. Generative AI tools can convert legacy documents and subject-matter expertise into structured digital work instructions, ensuring critical knowledge is preserved and scalable across shifts, facilities, and teams.

3 Ways Manufacturers are Using Technology to Train, Develop, and Retain Talent

AI-powered technology may be the missing puzzle piece for today’s workforce crisis.

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AI-powered technology may be the missing puzzle piece for today’s workforce crisis in manufacturing.

Is it just us or does recruiting, training, and retaining top talent today feel a lot like searching for that one elusive puzzle piece? The seismic shift in the workforce is forcing us to get creative and be adaptable like never before.  It’s a new generation and if we want to be competitive in hiring in this ultra-competitive environment, we need to re-access how we train, develop, and retain talent, embrace the variable nature of the labor market, and meet workers where they are. 

We can no longer try to force-fit the old model of staffing and training into a space that looks drastically different. It’s not just about a labor shortage or the supply chain challenges created by the pandemic. Workers themselves are changing. What they want from work, and how they want to work.

The solution to this head-scratching puzzle? AI-based technology. Digital work instructions and individualized training and on-the-job training (OJT) can improve productivity, reliability, independence, and safety for every worker. It offers flexibility in scheduling for operations managers. It reduces downtime. All of which contribute to a more efficient – and profitable – operation.

Sound too good to be true? Brace yourselves. It’s not. Here are three ways that AI-powered technology can help.

1. Moving onboarding and training closer to the point of work

Imagine if we could train and develop someone in the context of doing their work, leading to increased engagement and allowing organizations to retain top talent. Furthermore, we could see an increase in productivity as they constantly evolve their learnings.

AI is allowing companies to understand a worker’s skillset and provides the ability for personalized digital work instructions to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets and get those individuals productive faster.

2. Give support at the moment of need

Are you a people watcher? We are. Ever take notice of who is on the factory floor? Last time I checked, we got the “newbies” and “veterans”. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach to troubleshooting and performance support.

Enter AI.

Give workers the support and guidance they need, at the moment of need, whether it’s immediate access to a digital troubleshooting guide, or connecting virtually with a subject matter expert.  Delivering personalized work procedures for every worker allows for continuous learning and growth.

3. Improve engagement and retention

Workers that are connected and empowered with digital technology can discover and nurture diverse skills based on their unique competencies and experience. They can earn greater responsibility and independence. This increases confidence and job satisfaction. Which in turn can improve employee retention and slow the revolving door of continual recruiting and training. 

The aftermath?

Workers are likely to stay and want to grow in the company when they feel included. Shortly, workers begin walking with poise and a “can-do” attitude to their next job task.

 

What else is possible with AI-powered connected worker technology?

AI-based technology is ideal for training workers in this variable environment. AI-based systems individualize information about workers based on previous training and data-driven performance insights and augments their capabilities. It offers step-by-step guidance at the moment of need for regularly scheduled maintenance as well as troubleshooting. It helps managers learn about workers’ existing skills and build a rationale for specific roles, resources, and certification support and then make clear recommendations based on demands.

Technology should fit into your business as simply as sliding that last puzzle piece into place. Workers are the heart of your business, and you should adapt technology to fit your business, not the other way around.

Technology should fit into your business as simply as sliding that last puzzle piece into place. That includes how you train your workers. But no two workers are exactly alike. Each will learn and approach problems differently. So why not use the technology that recognizes and adapts to those differences to your advantage?

 

To learn more about how Augmentir can help you embrace this opportunity, contact us for a personalized demo.

The Great Resignation in Manufacturing

Recently, Augmentir completed a rigorous qualification audit as part of a Tier 1 Pharmaceutical Manufacturing company’s Good Manufacturing Practice (GMP), and we are pleased to announce that our product successfully passed the audit.

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A recent article published by The Washington Post shows some shocking numbers on the amount of Americans leaving their jobs over the past year. It’s no surprise that hotel and restaurant workers are resigning in high numbers due to the pandemic, but what is surprising is the fact that the manufacturing industry has been hit the hardest with “a nearly 60 percent jump” compared to pre-pandemic numbers. This “Great Resignation in Manufacturing” is the most of any industry, including hospitality, retail, and restaurants, which have seen about a 30% jump in resignations.

However, if you dig deeper, this trend isn’t new. This recent increase in job quitting in manufacturing has simply magnified a problem that had already been brewing for years, even prior to the start of the pandemic. In fact, in the four years prior to the pandemic (2015-2019), the average tenure rate in manufacture had decreased by 20% (US Bureau of Labor Statistics).

This accelerating workforce crisis is placing increased pressure on manufacturers and creating significant operational problems. The sector that was already stressed with a tight labor market, rapidly retiring baby-boomer generation, and the growing skills gap is now facing an increasingly unpredictable and diverse workforce. The variability in the workforce is making it difficult, if not impossible to meet safety and quality standards, or productivity goals. 

Manufacturing leaders’ new normal consists of shorter tenures, an unpredictable workforce, and the struggle to fill an unprecedented number of jobs. These leaders in the manufacturing sector are facing this reality and looking for ways to adjust to their new normal of building a flexible, safe and appealing workforce. As a result, managers are being forced to rethink traditional onboarding and training processes.  In fact, the entire “Hire to Retire” process needs to be re-imagined. It’s not the same workforce that our grandfather’s experienced, and it’s time for a change.

The Augmented, Flexible Workforce of the Future

The reality is that this problem is not going away. The Great Resignation in manufacturing has created a permanent shift, and manufacturers must begin to think about adapting their hiring, onboarding, and training processes to support the future workforce in manufacturing – an Augmented, Flexible Workforce.

What does this mean?

  • It means adopting new software tools to support a more efficient “hire to retire” process to enable companies to operate in a more flexible and resilient manner.
  • It means starting to understand your workforce at an individual level and using data to intelligently closes skills gaps at the moment of need and enables autonomous work.
  • And it means taking advantage of data.  More specifically, real-time workforce intelligence that can provide insights into training, guidance, and support needs.

Investing in AI-powered connected worker technology is one way to boost this operational resiliency. Many manufacturing companies are using digital Connected Worker technology and AI to transform how they hire, onboard, train, and deliver on-the-job guidance and support. AI-based connected worker software provides a data-driven approach that helps train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities. 

As workers become more connected, manufacturers have access to a new rich source of activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, contact us for a personalized demo.

AI Manufacturing 2021 – Event Recap

After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November and discuss how AI is shaping the future of the manufacturing workforce.

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After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November. This year’s event was hybrid, face-to-face on November 3 and 4th, and virtually on November 5th. While it was refreshing to be able to network face to face with leaders in the Manufacturing industry, it was great to have the opportunity to also network virtually on November 5th. If you aren’t familiar with the AI Manufacturing conference, this conference is the leading Artificial Intelligence event for Manufacturing Industries. This year’s event focused on:

  • The use of AI to Improve Quality, Reduce Defects, and Increase Profits
  • Developing a Digital Twin to Optimize Plant Operations
  • Using Building Blocks to Modernize Manufacturing Activities and Facilitate Growth
  • Designing  Products Enabled by Additive and Hybrid Manufacturing Techniques
  • Exploring the Use of AI in Industrial Attacks and Defense

Using AI to Unlock the True Potential of Today’s Modern, Connected Workforce

Dave Landreth, Augmentir’s Head of Customer Strategy had the opportunity to present on “Using AI to Unlock to the True Potential of Today’s Connected Workforce”. In this session, he discussed the variability of the workforce with generations, how they need to be trained differently, and how AI can assist in worker proficiency. Dave also discussed Bob Mosher’s 5 moments of need and how AI can be applied at the time of learning. 

The Misunderstood Fear of AI

Our founders saw that the humanistic approach was missing with traditional connected worker platforms and realized that AI was the key to saving the manufacturing world and unlocking worker potential. However, companies are reluctant to adopt AI in fear that automation will take over and eventually replace human workers in manufacturing. Others fear that AI would be used negatively to track workers, in a “big brother” type of way.  

As we’ve seen with our customers, this couldn’t be farther from the truth. When AI is leveraged ethically with the workforce in mind, it can be used to help improve and ultimately grow the talent of your workers. Assessing workers on their performance has been done for years through subjective performance reviews. Using AI allows the assessments to be based on data and can provide a path forward for worker improvement and continued growth. 

Understanding Today’s Struggles Within Manufacturing

Manufacturing workforce challenges

The struggles that manufacturers face today aren’t the same struggles that were present 40 years ago. One of the number one issues in manufacturing is hiring. Today, most manufacturers believe that hiring is a risk, with a limited pool of candidates. They are struggling with employees who don’t have the needed skill set and are questioning how they can train them and evaluate their performance. 

Manufacturing companies also struggle with retaining employees. We are all aware of the workforce retention issues right now. Employees are feeling like they aren’t heard and that they can’t contribute to the company, which causes them to look for a new career. There is also the struggle of thoughtful upskilling, meaning that formal training programs only recognize one type of worker. The average manufacturing plant sees 4 generations of workers, ranging from those fresh out of high school to the ones that have worked on a plant floor for 40+ years. Different generations learn differently and require different levels of support. There isn’t a one size fits all approach for teaching different generations. 

Another challenge with the workforce that isn’t as obvious, is with mergers and acquisitions. An acquisition means that companies now consist of two workforces doing things differently and needing to understand what part of procedures from the newly acquired company is worth incorporating into the existing procedures.

Leveraging AI to Help Build and Grow a Top Performing Workforce

Build and grow a top performing manufacturing workforce

AI is uniquely suited to solve these challenges, and we recognized that early on at Augmentir. We started looking at how AI could help build and grow a top performing workforce. One way AI can help is the ability to hire for potential by increasing the hiring of candidates to those not as skilled. AI allows companies to understand a worker’s skillset and provides the ability for personalized workflows to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. AI can also help with the “Right person – Right Job – Right Time” approach – always ensuring that the correct person is performing the task at the most efficient time. 

The use of AI allows all workers to contribute by allowing inline feedback to optimize work procedures. In addition, AI can be used to ensure personalized career job competency allows workers to be hired even if they do not have the optimal set of skills and experience. Measuring a worker’s proficiency when they are completing the work allows the worker to focus on each specific step and guides them at the time of need, instead of during classroom training. AI provides workers with predictive and stable data to help them grow in their roles. Having a data-driven way to measure success and provide advancement opportunities helps establish career paths as well as opportunities to grow. 

With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If we can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. We also see an increase in productivity and are constantly evolving their learnings. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company. The ability to train workers in the field while doing their jobs with AI personalization allows you to clearly and quickly assess how a worker is doing, where you focus the help to them, and driving those 1:1 work procedures is a game-changer.

AI in Manufacturing will solve many of the challenges that we are seeing. 

Learning & Development and the 5 Moments of Need

The Five Moments of Need methodology was created by Bob Mosher, a thought leader in learning and development with over 30 years of experience. He realized that after 20 years, classroom teaching was the wrong approach since it rarely teaches you things that you do in your job on the shop floor. Classroom learning allows an individual to gain a certain level of confidence, but quickly falls off when it’s time to apply it within context to a given workflow.  

According to Bob’s methodology, the 5 moments when our workforce needs knowledge and information consists of: 

  • When people are learning how to do something for the first time (New).
  • When people are expanding the breadth and depth of what they have learned (More).
  • When they need to act upon what they have learned, which includes planning what they will do, remembering what they may have forgotten, or adapting their performance to a unique situation (Apply).
  • When problems arise, or things break or don’t work the way they were intended (Solve).
  • When people need to learn a new way of doing something, which requires them to change skills that are deeply ingrained in their performance practices (Change).

The approach that Bob and his team adopted in the last 10 years is to think more about performance support. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach. This is where AI comes in: being able to deliver personalized work procedures for every worker, allowing for continuous learning and growth. Based on proficiency, there may be a more guided set of work instructions, a session with a remote expert, or a supervisor sign-off required in order to complete the job on quality and on schedule. AI can also be used to continuously measure and assess how the workers are doing. This is where organizations can start seeing growth within their workforce.

Looking Ahead

We had a blast at this year’s AI Manufacturing conference and are already looking forward to another successful event next year! If you’re interested in learning more about why AI is an essential tool in digital transformation, from reducing costs and downtime to improving over quality and productivity, we’d highly suggest considering attending next year. In the meantime, if you’re looking for information surrounding AI, digital transformation, and building a connected workforce, check out our eBook: “Building a Modern, Connected Workforce with AI”.

Modernizing Manufacturing Training with Continuous and Workflow Learning

Learn how continuous and workflow learning can help modernize employee training in the manufacturing industry.

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Staying ahead of the curve in today’s manufacturing marketplace means that businesses need to innovate and adapt. To accomplish this, organizations must have a skilled workforce and ongoing training and workforce management processes to support continuous learning and development.

Modernizing training cultivates employee skillsets by implementing continuous learning in the flow of work.

modernize manufacturing training with continuous learning

Continuous learning is the process of attaining new skills on a constant basis. Workflow learning involves educating yourself on the job using resources and self-directed learning materials. Done together, this modern training approach can help streamline productivity.

If you want to learn how to improve manufacturing training with continuous learning and workflow learning, explore this article that answers the following:

What is continuous learning?

Continuous learning in manufacturing involves enabling workers to learn new skills regularly. It’s a great way to improve employee performance and innovation. According to Forbes, embracing a culture of continuous learning can help organizations adapt to market demands, foster innovation, as well as attract and retain top talent.

Learning can come in different forms, from formal course training to hands-on experience. Employees are encouraged to be self-starters who want to evolve their skills on an on-going basis. A good example of a continuous learning model is everboarding; everboarding is a modern approach toward employee onboarding and training that shifts away from the traditional “one-and-done” onboarding model and recognizes learning as an ongoing process.

How can continuous learning be used in manufacturing?

When businesses don’t support continuous learning, manufacturing processes stagnate. This contributes to a lack of innovation and hinders potential opportunities for success that a company may experience.

In a nutshell, the more workers know and the more they can accomplish, the more they can contribute to business growth. This may consist of employees taking an online course or learning a new technique hands-on, no matter what department they’re in.

For example, assembly line workers may learn new manufacturing processes to ensure everything is functioning properly. Meanwhile, operators may study the latest machinery to learn new tricks of the trade.

What is workflow learning?

Workflow training in manufacturing involves learning while doing. This means that workers pick up new skills while on the job through hands-on experience.

The key to workflow learning is that it happens while employees perform their everyday tasks.

Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions. With workflow learning, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially bridging the gap between knowing and doing. This “active learning” aligns with the Pyramid of Learning visual model that illustrates the different stages of learning and their relative effectiveness.

pyramid of learning

Active learning involves the learner actively engaging with the material, often through problem-solving, discussion, or application of the knowledge while they are on the job.

In general, active learning is considered more effective than passive learning in promoting deep understanding and retention of information. Therefore, learning leaders often strive to design learning experiences that involve higher levels of active learning, moving beyond the lower levels of the pyramid and promoting critical thinking, creativity, and problem-solving skills.

How can workflow learning be used in manufacturing?

Workflow learning consists of using resources at your disposal to complete tasks. This strategy is sometimes referred to as performance support.

For example, workers can look up answers to questions, steps of a process, or new services while performing their jobs instead of interrupting their workflow to go to a class or training session.

Pro Tip

Active, or workflow learning can be implemented with mobile learning solutions that leverage connected worker technology and AI to provide workers with bite-sized, on-demand training modules that they can access on smartphones or tablets. These modules can be developed with customized learning paths that are focused on the type of tasks and work employees are doing on the factory floor.

A

How can technology improve manufacturing training?

The nature of manufacturing training is changing in the age of artificial intelligence. Today, many training processes can be streamlined and optimized using digital and smart, connected worker technologies.

For instance, data collected from everyday manufacturing processes can polish training programs online. Experienced workers can share best practices on customized dashboards for other employees to access. These can be updated in real-time and show changes highlighted to better optimize manufacturing processes.

Digital training tools can also help improve learning speed and retention. For example, workers who need visuals or real-world scenarios can assess them using AI-powered software to maximize their training.

 

Augmentir is the world’s leading AI-powered connected worker solution that helps industrial companies optimize the safety, quality, and productivity of the industrial frontline workforce. Contact us for a live demo, and learn why leading manufacturers are choosing us to elevate their manufacturing operations to the next level.

 

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How to Combat the Manufacturing Skills Gap with an Augmented Connected Workforce (ACWF)

Learn how manufacturers combat the manufacturing skilled labor shortage and close skills gaps with an Augmented Connected Workforce (ACWF).

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An Augmented Connected Workforce (ACWF) offers manufacturing and other industrial organizations a powerful solution to combat the ever-worsening skilled labor shortage and skills gap. According to a report by Deloitte and the Manufacturing Institute, an estimated 2.1 million manufacturing jobs could go unfilled by 2030 and the cost of those missing jobs could potentially total $1 trillion in 2030 alone.

augmented connected workforce acwf manufacturing

By integrating advanced technologies like artificial intelligence (AI), connected worker platforms, and other emerging solutions manufacturers can enhance the capabilities of their existing workforce and bridge skill gaps. Connected worker tools offer real-time monitoring of your frontline workforce, ensuring seamless operations. Moreover, connectivity enables remote collaboration, allowing experts to assist frontline workers from anywhere in the world. This interconnected ecosystem empowers workers with the tools they need to succeed and attracts new talent by showcasing a commitment to innovation and technology-driven growth.

Through an ACWF, manufacturers can effectively combat the manufacturing skilled labor shortage and close the skills gap while driving productivity, innovation, and remaining competitive. Read more about ACWF in manufacturing below:

Implementing an ACWF in Manufacturing

A critical element of transitioning from a traditional workforce to an Augmented Connected Workforce (ACWF) is implementing and adopting new technologies and processes. Here are a few steps that can help with the adoption of ACWF technologies and smooth transitions in industrial settings:

  • Step 1: Assess Current Processes – Organizations must understand existing workflows and identify areas where AI, connected worker platforms, and other ACWF technology can replace paper-based and manual processes to enhance efficiency and productivity.
  • Step 2: Invest in Technology – Procure  AI-driven analytics platforms, mobile technology, and wearable technology to enable real-time data collection and remote collaboration.
  • Step 3: Training and Onboarding – Provide comprehensive training programs to familiarize workers with new technologies and workflows. Emphasize the importance of safety protocols and data privacy.
  • Step 4: Pilot Programs – Start with small-scale pilot programs to test the effectiveness of the implemented technologies in real-world manufacturing environments. Target high-value use cases that can benefit from a transition from paper to digital.
  • Step 5: Continuous Improvement – Gather feedback from workers and supervisors during pilot programs and adapt implementation initiatives based on their input. Continuously optimize processes and technologies for maximum effectiveness.

By following these steps, manufacturers can smooth the transition from a traditional manufacturing workforce to an ACWF, empowering their frontline workers with improved capabilities, skills, and overall operational excellence.

Supporting Learning in the Flow of Work

Augmented Connected Workforce (ACWF) technologies allow for increased frontline support and for new processes around learning and training to strategically upskill and reskill, reduce time to competency for new workers, and to combat the skilled labor shortage in manufacturing and more. Connected worker tools, such as wearable devices and IoT sensors, enable real-time monitoring of worker performance and environmental conditions, ensuring safety and efficiency on the factory floor.

pyramid of learning

An ACWF also allows for improved workflow learning capabilities giving frontline workers access to expert guidance, remote assistance and collaboration, microlearning, and other learning in the flow of work options regardless of the worker’s location.

ACWF tools further enhance frontline activities through:

  • Digital work instructions and guidance: Smart, connected worker platforms provide digital work instructions, procedures, and visual guidance easily accessible to workers on mobile devices.
  • Digital mentors and training: Some ACWFs incorporate “digital mentors” – GenAI-powered industrial assistants that can provide step-by-step guidance to workers, especially new hires.
  • Knowledge capture and sharing: Connected frontline worker applications serve as knowledge sharing platforms, capturing data and insights from frontline workers, which can then be analyzed by AI software and used to improve processes, update work instructions, and share knowledge across the organization
  • Performance monitoring and feedback: ACWF solutions provide visibility into worker performance, allowing managers to identify areas where additional training or support is needed.

augmented connected workforce in manufacturing

In summary, ACWF initiatives empower frontline workers with the digital tools, knowledge, and support they need to learn and improve their skills directly within their daily workflows, rather than relying solely on formal training programs. This helps close skills gaps and drive continuous improvement.

Future-proofing Manufacturing Operations with an ACWF

Adopting an Augmented Connected Workforce (ACWF) approach centered around augmenting frontline workers with mobile technology, immersive training, collaborative decision-making, and continuous improvement, allows manufacturers to future-proof their operations and gain a sustainable competitive advantage. This concept empowers employees with powerful tools that augment and enhance their capabilities, productivity, and overall business processes by accessing critical information and fostering collaboration

AI-powered software can analyze vast amounts of data to optimize production processes and predict workforce development needs. At the same time, connected frontline worker solutions enable the integration of mobile and wearable technologies and provide real-time data insights, aiding in optimizing factory operations and adapting to evolving industry trends.

For an Augmented Connected Workforce, integrating AI and connected worker technologies serves as a vital strategy for manufacturers navigating the skilled labor crisis. Augmentir encourages organizations to embrace ACWF transformations and expedites adoption through a comprehensive connected worker platform leveraging the combined benefits of connected worker and AI technologies.

With Augmentir, frontline workers can access critical information, real-time data and insights, and expert advice and guidance all in the flow of work preventing lost time and improving both efficiency and productivity. Schedule a live demo to learn more about how an Augmented Connected Workforce future-proofs manufacturing operations and enhances frontline activities.

 

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How AI is Revolutionizing Manufacturing Training

Explore how Augmentir uses AI to personalize manufacturing training, boost performance, and deliver real-time support and content creation.

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In today’s fast-paced manufacturing environment, staying competitive means more than just upgrading equipment—it requires investing in people. But traditional workforce training methods haven’t kept up. Static instruction manuals, one-size-fits-all onboarding programs, and outdated SOPs often fall short of preparing workers for the dynamic challenges of the modern factory floor.

ai in manufacturing training

Enter artificial intelligence (AI). From analyzing worker performance to delivering personalized training and real-time support, AI is transforming how manufacturers develop and empower their frontline workforce. Solutions like Augmentir are at the forefront of this shift, using advanced analytics, machine learning, and generative AI to create more effective, agile, and personalized training ecosystems.

Here’s how AI is reshaping manufacturing training across four critical areas.

1. Smarter Upskilling and Reskilling Through Performance Analytics

One of AI’s most valuable contributions to manufacturing training is its ability to turn raw performance data into actionable insight. Every worker interaction—how long a task takes, whether they need help, how often they make mistakes—tells a story. Traditionally, these insights were anecdotal at best. With AI, they’re measurable and immediately useful.

Platforms like Augmentir use AI to analyze real-time worker performance data and automatically surface trends and gaps. Suppose a maintenance technician consistently struggles with certain procedures. The system flags this, allowing supervisors to deliver targeted retraining or create a learning path that addresses the weak areas. Likewise, workers who consistently perform well might be fast-tracked for cross-training or more advanced roles.

the difference between skills development and training in manufacturing

This approach enables continuous learning and ongoing upskilling and reskilling, not just during onboarding or annual reviews, but every day. By matching training efforts with actual needs—based on data, not guesswork—companies can build more agile, responsive workforces that are always learning and improving.

2. Personalized Work Instructions for Every Skill Level

Manufacturing is not a one-size-fits-all environment—so why should training be?

AI can help tailor work instructions and learning experiences to the individual. With Augmentir, for example, AI dynamically adjusts work instructions and guidance based on a worker’s experience, proficiency, and even recent performance. This personalization helps new employees ramp up faster and allows seasoned workers to bypass unnecessary detail and focus on what matters most.

For a novice, instructions might include step-by-step visual aids, safety warnings, and prompts for supervisor sign-off. A veteran might receive a streamlined checklist with optional references. The experience becomes smoother and more relevant for each person, improving accuracy and reducing the time it takes to perform tasks.

using ai to improve manufacturing trainingThis kind of adaptive guidance is especially valuable in high-mix, low-volume environments or where production processes change frequently. Workers stay productive while learning in the flow of work—a win for both efficiency and engagement.

3. On-the-Job Support with Generative AI Factory Assistants

Even the best training can’t prepare workers for every situation they’ll encounter. That’s where generative AI assistants—often called copilots—come in.

Imagine a frontline operator faced with an unfamiliar error code on a CNC machine. Instead of stopping work, digging through documentation, or calling a supervisor, they can ask an AI assistant integrated into their work app or wearable device. The assistant quickly provides context-aware help: maybe it’s a diagnostic procedure, a video walkthrough, or a simple checklist.

This is not science fiction—it’s happening now. With tools like Augmentir’s Augie, workers get real-time guidance, support, and training while they work, tailored to the exact task and situation. These industrial generative AI assistants learn and improve with each interaction, so the more they’re used, the better they get at helping.

augie generative ai assistant for manufacturing standard work

This not only boosts productivity but also reduces downtime, prevents errors, and improves worker confidence. AI copilots act like a mentor in your pocket—one that’s always available, always up to date, and always ready to help.

4. Rapid Content Creation with Generative AI Tools Like Augie

A major pain point in manufacturing training has always been content creation. Writing SOPs, training manuals, and onboarding documents is time-consuming, and keeping them current is a constant challenge—especially when processes, tools, or equipment change.

That’s where generative AI tools like Augmentir’s Augie come in.

Augie helps training teams and subject matter experts create up-to-date, accurate, and engaging content in a fraction of the time it used to take. You can input a few notes, a video walkthrough, or an old manual, and Augie will generate structured work instructions, training modules, or even interactive checklists. This democratizes content creation—now anyone from a line lead to a maintenance engineer can contribute training content without needing to be a technical writer.

augie industrial copilot generative ai assistant for training and quiz creation

More importantly, because Augie is part of the same ecosystem, the training content it generates can be immediately pushed into the hands of workers—embedded in digital workflows, accessible via AI assistants, or served up dynamically based on user behavior.

This means your training stays fresh, relevant, and aligned with the reality on the ground. No more outdated manuals. No more lag between process changes and training updates.

The Big Picture: AI as a Training Multiplier

What ties all these innovations together is a shift from static, one-time training to ongoing, personalized support—enabled by AI.

  • AI makes training smarter by identifying who needs help and where.
  • It makes training faster by delivering content that matches each worker’s needs.
  • It makes training more effective by embedding it directly into the flow of work.
  • And it makes training more scalable by automating content creation and support delivery.

In short, AI becomes a force multiplier for training. It empowers workers to get better faster, managers to lead more effectively, and companies to stay agile in a constantly changing world.

Looking Ahead

The manufacturing skills gap isn’t going away anytime soon. In fact, it’s projected that millions of manufacturing jobs could go unfilled over the next decade due to a shortage of trained workers. Traditional training methods simply can’t scale to meet this challenge.

But AI can.

By weaving intelligence into every layer of the training experience—from data analytics to real-time support—platforms like Augmentir offer a new blueprint for workforce development. It’s faster, smarter, more engaging, and ultimately, more human.

Because at the end of the day, it’s not about replacing people with AI—it’s about helping people thrive alongside it.

 

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