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

Generative AI in manufacturing refers to the application of generative models and artificial intelligence techniques to optimize and enhance various aspects of the manufacturing process. This involves using AI algorithms to generate new product designs, optimize production workflows, predict maintenance needs, and improve production efficiency within frontline operations.

generative ai in manufacturing

According to McKinsey, nearly 75% of generative AI’s major value lies in use cases across four areas: manufacturing, customer operations, marketing and sales, and supply chain management. Manufacturers are uniquely situated to benefit from generative AI and it is already a transformative force for some. A recent Deloitte study found that 79% of organizations expect generative AI to transform their operations within three years, and 56% of them are already using generative AI solutions to improve efficiency and productivity.

Manufacturing is rapidly evolving and by integrating cutting-edge technologies like Generative AI, manufacturers can better support, augment, and enhance their frontline workforces with improved decision-making, collaboration, and data insights.

Join us below as we dive into generative AI in manufacturing exploring how it works, the benefits and risks, and some of the top use cases that generative AI, specifically generative ai digital assistants, can provide for manufacturing operations:

What is Generative AI in Manufacturing

Generative AI refers to artificial intelligence systems designed to create new content, such as text, images, or music, by learning patterns from existing data. In manufacturing, this involves the use of Large Language Models (LLMs) and Natural Language Processing (NLP) to analyze vast amounts of data, simulate different scenarios, and generate innovative solutions that can impact a wide range of manufacturing processes.

Large Language Models

Large Language Models (LLMs) are a type of generative artificial intelligence model that have been trained on a large volume – sometimes referred to as a corpus – of text data. They are capable of understanding and generating human-like text and have been used in a wide range of applications, including natural language processing, machine translation, and text generation.

In manufacturing, generative AI solutions should leverage proprietary fit-for-purpose, pre-trained LLMs, coupled with robust security and permissions.  Industrial LLMs use operational data, training and workforce management data, connected worker and engineering data, as well as information from enterprise systems.

Natural Language Processing

Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and humans using natural language. It involves the development of algorithms and models that enable computers to understand, interpret, and respond to human language in a way that is both meaningful and useful.

For generative AI, NLP is a key technology that enables the assistants to understand and generate human-like text, providing seamless conversational user experiences and valuable assistance to frontline workers, engineers, and managers in manufacturing and industrial settings.

NLPs allow the AI to process and interpret natural language inputs, enabling it to engage in human-like interactions, understand user queries, and provide relevant and accurate responses. This is essential for common manufacturing tasks such as real-time assistance, documentation review, predictive maintenance, and quality control.

generative ai in manufacturing with LLMs and NLP

By combining large language models and natural language processing, generative AI can produce coherent and contextually relevant text for tasks like writing, summarization, translation, and conversation, mimicking human language proficiency.

Benefits of Leveraging Generative AI in the Manufacturing Industry

Generative AI and solutions that leverage them offer several benefits for manufacturing operations, including:

  • Operational/Production Optimization and Forecasting: GenAI technology offers a significant boost to manufacturing processes by monitoring and analyzing in real-time, spotting problems quickly, and providing predictive insights and personalized assistance to boost efficiency for manufacturing workers. Additionally, AI assistants empower manufacturers to explore multiple control strategies within their process, identifying potential bottlenecks and failure points.
  • Proactive Problem-Solving: Generative AI-powered tools provide real-time monitoring and risk analysis of manufacturing operations, enabling the quick identification and resolution of issues to optimize production and efficiency. They can spot events as they happen, providing valuable insights and recommendations to help operators and engineers rapidly identify and resolve problems before they escalate.
  • Reduce Unplanned Downtime: Generative AI solutions can analyze vast datasets to predict equipment maintenance needs before issues arise, allowing manufacturers to schedule maintenance proactively, minimizing unplanned disruptions. This not only improves downtime but also contributes to the overall operational resilience of mission-critical equipment.
  • Personalized Support and On-the-job Guidance: Generative AI tools can be tailored to diverse roles within the manufacturing plant, offering personalized assistance to operators, engineers, and managers. It can provide role-based, personalized assistance, and proactive insights to understand past events, current statuses, and potential future happenings, enabling workers to perform their tasks more effectively and make better, more informed decisions.

These benefits demonstrate the significant impact of generative AI on frontline manufacturing activities, improving overall operational efficiency, adjusting processes where needed, and driving operational excellence.

Pro Tip

Generative AI assistants can take these benefits one step further by incorporating skills and training data to measure training effectiveness, identify skills gaps, and suggest solutions to prevent any skilled labor issues. This guarantees that frontline workers have the essential skills to perform tasks safely and efficiently, while also establishing personalized career development paths for manufacturing employees that continuously enhance their knowledge and abilities.


Risks of Generative AI in Manufacturing

Generative AI in manufacturing presents several risks, including data security, intellectual property concerns, and potential bias in AI models. The reliance on vast amounts of data raises the risk of data breaches and cyberattacks, potentially exposing sensitive information. Intellectual property issues may arise if AI-generated designs or processes inadvertently infringe on existing patents or proprietary technologies. Additionally, biases in training data can lead to suboptimal or unfair outcomes, affecting the quality and equity of AI-driven decisions. There is also the risk of over-reliance on AI, which may reduce human oversight and lead to errors if the AI models make incorrect predictions or generate flawed designs. Ensuring proper validation, transparency, and human intervention is crucial to mitigating these risks.

Top Use Cases for Generative AI Manufacturing Assistants

Generative AI assistants and frontline copilots are AI-powered tools designed to provide valuable assistance and insights in industrial settings, particularly in manufacturing. These assistants are a type of generative AI that are used in manufacturing operations to enhance human-machine collaboration, streamline workflows, and offer proactive insights to optimize performance and productivity for frontline workers.

What makes frontline AI assistants unique among other generative AI copilots is the enhanced human-like interaction beyond standard data analytics and analysis to understand the context around a process or issue; including what happened and why, as well as anticipate future events.

Generative AI assistants work via specialized large language models (LLMs) and generative AI, providing contextual intelligence for superior operations, productivity, and uptime in industrial settings. Additionally, they typically involve natural language processing for understanding human language, pattern recognition to identify trends or behaviors, and decision-making algorithms to offer real-time assistance. This, combined with machine learning techniques, allows them to understand user inputs, provide informed suggestions, and automate tasks.

  1. Troubleshooting:Troubleshooting is such a critical use case in manufacturing. With today’s skilled labor shortage, frontline workers are often times in situations where they don’t have the decades of tribal knowledge required to quickly troubleshoot and resolve issues on the shop floor. AI assistants can help these workers make decisions faster and reduce production downtime by providing instant access to summarized facts relevant to a job or tasks, this could come from procedures, troubleshooting guides, captured tribal knowledge, or OEM manuals.
  2. Personalized Training & Support: With GenAI assistants, manufacturers can instantly close skills and experience gaps with information personalized, context-aware to the individual worker. This could include: on the job training materials, one point lessons (OPLs), or peer/user generated content such as comments and conversations.
  3. Leader Standard Work: With Generative AI assistants, operations leaders can assess and understand the effectiveness of standard work within their manufacturing environment, and identify where there are areas of risk or opportunities for improvement.
  4. Converting Tribal Knowledge: One of the more pressing priorities that many manufacturers face is the task of capturing and converting tribal knowledge into digital corporate assets that can be shared across the organization. With connected worker technology that utilizes Generative AI, manufacturing companies can now 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. Continuous Improvement: AI and GenAI assistants can help us identify areas for content improvement, and make those improvements, measure training effectiveness, and measure and improve workforce effectiveness.
  6. Operational Analysis: Generative AI assistants can also provide value when it comes to operational improvements. GenAI assistants can use employee attendance data to help shift managers or line leaders determine where the risks are, and potentially offset any resource issues before they become truly problematic. An organization’s skills matrix, presence data, and production schedules all can feed into a fit-for-purpose, pre-trained LLM – giving you information that manufacturing leaders need to keep their operations running.

Future-proofing Manufacturing Operations with Augie™

Generative AI and other AI-powered solutions are leveling up manufacturing operations, analyzing data to predict equipment maintenance needs before issues arise, allowing for proactive maintenance scheduling, and minimizing unplanned disruptions. With these tools manufacturers can empower frontline workers with improved collaboration and provide real-time assistance with contextual information, ensuring relevant and timely support during critical decision-making processes.

Overall, generative AI is transforming a wide array of manufacturing and industrial activities, connecting workers in ways that were previously thought impossible, and making frontline tasks and processes safer and more efficient for workers everywhere.

Augie, Augmentir’s new generative AI assistant for frontline work pulls in skill capabilities, workforce development information, and training data in addition to MES and ERP data. It offers contextual, proactive insights and automated workflows to optimize production and prevent bottlenecks, contributing to manufacturing efficiency, uptime, quality, and decision-making.

augie gen ai industrial assistant close skills gaps

Additionally, Augie ties together operational data, training and workforce management data, engineering data, and knowledge/information from various disparate enterprise systems to empower frontline workers, streamline workflows, and increase manufacturing performance.

Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.


See Augmentir in Action
Get in Touch for a Personalized Demo

Watch Augmentir’s presentation at Learning & HR Tech 2024 and see how Generative AI Copilots transform learning and development in manufacturing.

Generative AI in learning and development has started to shape the future of HR across the board including attracting, developing, engaging, and retaining talent.

AI has revolutionized how organizations approach:

  • Talent acquisition – for smarter recruiting
  • Talent development – for skills analysis and performance evaluations
  • Worker relations – capitalizing on its ability to personalize employee relations
  • Workforce planning – leveraging its ability to make sense of data to perform more accurate forecasting and capacity planning
  • People analytics – using AI to make sense of employee data from an engagement and skills optimization standpoint
  • Performance management – relying on it for benchmarking and progress evaluation
  • HR operations – leveraging AI’s ability to automate and support onboarding and offboarding processes
  • Learning and development – using AI in everything from content creation to delivering personalized and adaptive content

generative ai learning copilots

However, Generative AI in learning and development has yet to make a significant impact on employees where it matters the most – in the flow of work.

This is where Generative AI learning copilots and AI-powered connected worker solutions come in. Together these technologies are transforming learning for frontline workers, improving onboarding, enabling learning in the flow of work, and driving more efficient upskilling and reskilling.

Watch our full presentation from Learning and HR Tech 2024 “Generative AI Learning Copilots: Transforming Learning as We Know It”, on-demand below.

Key Highlights:

  • Generative AI in learning and development has started to shape the future of HR across the board including attracting, developing, engaging, and retaining talent.
  • Deskless workers make up 80% of all workers globally and are underserved from a learning and development perspective, with 78% feeling they don’t have the right amount of training to succeed.
  • Generative AI Learning Copilots can generate training content, translate languages, provide real-time feedback, give on-demand guidance and answers, and serve as a digital performance support tool.

Generative AI Learning Copilots for Deskless Workers

Deskless workers, often referred to as “frontline workers”, generally do not sit in front of a desk and make up about 80% of all workers globally, they are on the front lines – in factories, at retail counters, construction sites, hospitals, and more.

While frontline workers and activities have undergone dramatic changes over the past few years, they are still woefully underserved from a learning and development standpoint.

  • 78% of frontline workers feel they don’t have the right amount of training to succeed at work
  • 65% want information on-demand and “in the flow of work”
  • Only 12% of HR operations leaders are actually satisfied with their L&D processes in support of their frontline employees

The reality is that traditional onboarding and training practices have been proven to be ineffective, however, much like AI has historically been used to improve the efficiency and output of machines, we can do the same with our frontline workforce.

AI learning and development tools and GenAI assistants can help:

  • Identify areas for content improvement, and implement those improvements
  • Measure training effectiveness
  • Create personalized, job-relevant training and curriculums
  • Measure and improve workforce effectiveness

Managing Manufacturing Workforce Challenges with GenAI Learning Copilots

The workforce crisis in manufacturing is accelerating and at the forefront of the minds of operations and HR leaders.

In fact, even if every skilled worker in America were employed, there would still be 35% more unfilled job openings in the manufacturing sector than skilled workers capable of filling them. Deloitte predicts that the skilled labor crisis will cost manufacturers upwards of $1 trillion by 2030.

In 2019, the average tenure in manufacturing was 20 years, the average time in position was 7 years, and the average 90-day retention rate was 90%. As of 2023, however, the average tenure is 3 years, the average time in position is 9 months, and the average 90-day retention rate was 50%.

These are representative of drastically different manufacturing realities. The workforce of 2019 is not coming back, and neither will productivity, unless organizations make significant investments and strides in supporting frontline workers with the appropriate tools and training. Luckily, smart connected worker and generative AI technologies offer a path forward.

Generative AI helps manufacturers answer:

  • What is the skills inventory of the team that is in attendance today?
  • Who can/should perform this work?
  • Who would benefit the most from targeted training?
  • Where should they focus on for process improvement?
  • What type of training would give them the biggest return?
  • What training materials need Improvement?

Generative AI-powered copilots and digital assistants can take this further, allowing frontline manufacturing workers access to vast amounts of knowledge in the flow of work when they need it most, helping to predict and prevent skills gaps before they impact production, and to design efficient and personalized development curriculums to shorten the time it takes for workers to be effective and competent in their positions.

Interested in learning more?

If you’d like to learn more about Augmentir and see how our AI-powered connected worker platform improves onboarding, training, skills management, and other learning and development aspects across organizations, schedule a demo with one of our product experts.


See Augmentir in Action
Get in Touch for a Personalized Demo

Say hello to the newest addition to the Augmentir platform, Augie – the GenAI powered digital assistant for manufacturing.

Say hello to the future of work in manufacturing with the latest addition to Augmentir’s suite of connected worker tools, Augie™.

augie generative ai assistant for manufacturing

Augie is a digital assistant for frontline operations that utilizes Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) to enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. It leverages enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.

Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.

Continue reading below to learn more about how Augie works and how it can benefit your frontline workforce and manufacturing operations:

How our GenAI Powered Assistant Works

Generative AI-powered smart manufacturing assistants are designed to provide secure, role-based, personalized assistance to frontline workers, engineers, and managers in various industries, including manufacturing.

They work by leveraging artificial intelligence and integrations across different software systems, providing guidance and assistance in various tasks to enhance productivity and performance. This includes providing data insights, recommendations on actions to improve performance, and the ability to create analyses and dashboards with a natural language-based assistant.

A majority of smart manufacturing assistants only draw their information from manufacturing execution systems (MES), without tying in other important systems necessary for frontline manufacturing success.

Augie, however, is different. It leverages enterprise-wide data tying in information from a wide range of platforms including operational data, training and workforce management data, connected worker and engineering data, as well as information from enterprise systems.

gen ai industrial manufacturing

How Augie Benefits Your Frontline Workforce

Augie is unique among other smart manufacturing assistants. It leverages proprietary fit-for-purpose, pre-trained LLMs and generative AI, coupled with robust security and permissions, to help factory managers, operators, and engineers improve efficiency, resolve issues faster, and prevent downtime.

With information readily available via Augie, frontline workers can make decisions faster, reduce downtime, and improve troubleshooting with instant access to summarized facts relevant to a job or task. Additionally, Augie is multi-modal, meaning it can return actionable information in the form of work procedures, training videos, recorded collaborations, engineering documents and SOPs, as well as tribal knowledge.

Through Augie, manufacturers can instantly:

  • Close skills and experience gaps with personalized support
  • Gain insights into Leader Standard Work
  • Gain new insights into skills inventories
  • Convert Tribal Knowledge into Digital Corporate Assets
  • Identify opportunities for continuous improvement
  • Forecast potential operational issues

augie gen ai industrial assistant troubleshooting

With Augie by your side, you can streamline manufacturing operations, optimize performance, empower your frontline workforces, and stay ahead in today’s rapidly evolving and competitive landscape.


6 Ways Manufacturers Can Use GenAI Today



Improve Operational Efficiency with Augie and Augmentir

The digitization of frontline processes has become a must-have to keep up with the velocity of change – but not just digitization … smart digitization. Recently, Deloitte found that 86% of manufacturing executives believe smart factory solutions will be the primary drivers of competitiveness in the next five years. Leveraging smart, AI-driven connected worker solutions that allow industrial organizations to best support their frontline workforces and optimize processes to make them safer and more efficient is critical to overall enterprise success.

At Augmentir, we have been met with continued success in our efforts to transform manufacturing operations. Our patented Smart AI foundation helps manufacturing organizations close the loop between training and work execution, delivering the data and in-line insights necessary to continuously improve operational excellence day-over-day, year-over-year. Augmentir is the world’s leading connected worker solution, combining smart connected worker and GenAI technologies to drive continuous improvement and enhance performance management initiatives in manufacturing.

The addition of Augie to our platform is a game-changer for factory floor and other frontline workers, allowing for quick reference troubleshooting and useful, contextualized information to be delivered at the moment of need. Furthermore, with Augie, less experienced workers are provided with additional support and individualized guidance based on the job or task needs.

With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.


See Augmentir in Action
Get in Touch for a Personalized Demo