What is Augmented Intelligence?
Augmented Intelligence is the use of artificial intelligence that focuses on the role AI plays in enhancing and improving human intelligence and decision making. The term is used to represent the combination of people and artificial intelligence working together to improve the way people do work, not replace it.
What Role Does Augmented Intelligence play in Today’s Modern Industrial Workforce?
The use of artificial intelligence to automate work in manufacturing has been a major focus for digital transformation efforts across a range of verticals and is a core technology for Industry 4.0. More recently, AI is increasingly being used alongside workers to augment and amplify their intelligence and improve safety, quality, and productivity.
According to Gartner, AI augmentation is already creating $2.9 trillion of business value and 6.2 billion hours of worker productivity globally. Furthermore, by 2030, decision support/augmentation will surpass all other types of AI initiatives.
Digital software tools that incorporate AI and connected worker technology to augment workers as they perform their jobs are a great example of augmented intelligence in practice. Connected worker platforms are used to create, assign, and manage the tasks being done. Through a combination of AI-powered digital work instructions and real-time collaboration tools, workers can independently complete tasks at peak performance using AI to enhance their knowledge and access to information.
4 Ways Augmented Intelligence is Empowering Manufacturing Workers
Connected worker solutions that are built on an AI foundation are also being used to support continuous improvement and lean initiatives in the workplace. With the foundational elements of digitized SOPs and remote expert guidance in place, manufacturing companies can not only help guide their workers with contextual information, aiding them in performing their jobs at peak efficiency and solving problems faster, but this also allows organizations to capture valuable data not just on the work that is performed, but also on how those workers are performing their jobs along with what activities or interactions are contributing to the success or performance of certain jobs.
Here are 4 ways augmented intelligence is being used today in manufacturing:
1. Personalized Instruction Based on Worker Proficiency
One example of how AI is being used is by providing personalized guidance where instructions are matched to the proficiency of each worker. This is helping to address skills gap challenges and help novice workers reach proficiency faster.
For example, Augmentir’s connected worker platform does this by providing digital, augmented work instructions that use AI to personalize the instructions based on worker proficiency, instant skilling using dynamic content with inline rich media for on-the-job-training, live access to remote experts, and AI-bots to automate knowledge sharing and improve decision support in the field.
For example, a worker that is new to an assembly job may need an escalation to a shop supervisor for sign-off, whereas a senior worker may not need that step. With AI matching instructions and support to each worker’s proficiency, each worker can perform at the highest levels of safety, quality, and productivity.
This allows companies to take a standard set of instructions and augment them with personalized assistance for individual workers, so they can perform their tasks at optimal safety, quality, and productivity.
2. Training at the Moment of Need
Another way that AI is helping to augment workers is through on-the-job targeted training – delivered at the moment of need.
Today’s industrial workforce is changing in real-time – who shows up, what their skills are, what jobs they need to do, is a constantly moving target. The traditional “one size fits all” approach to training, guidance, and performance support is fundamentally incapable of enabling today’s workers to function at their individual peak of safety, quality and productivity.
Traditionally, there was a clear separation between training and work execution, requiring onboarding training to encompass everything a worker could possibly do, extending training time and leading to inefficiencies. Today, with the ability to deliver training at the moment of need, onboarding can focus on everything a worker will probably do, significantly reducing onboarding time. From just-in-time training to digital one point lessons, companies are increasingly re-thinking how they train their workforce.
Connected worker software platforms that are based on a data-driven, AI-supported approach can help train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities.
3. AI Assistants
Industrial companies can drive further worker optimization through AI bots that provide autonomous, digital assistance.
Workers on the factory floor or service technicians out in the field that require additional support can benefit from AI bots that autonomously deliver answers to questions, provide digital content such as drawings, pictures, and videos, and rich sets of digital work instructions, to help workers resolve issues and complete the work independently. This allows a portion of worker support requests handled autonomously instead of over-reliance on subject matter experts (SMEs).
4. Intelligent Knowledge Sharing
The benefits that AI can bring to industrial companies are not limited to dynamic, proficiency-based work instructions, or moment-of-need training. Companies are also turning to AI to provide intelligence around the capture and cataloging of tribal knowledge that is being shared between workers and senior colleagues and subject matter experts.
Connected workers are increasingly relying on remote collaboration to leverage the expertise of senior colleagues and subject matter experts for on-the-job troubleshooting and problem-solving. AI-bots can capture tribal knowledge of these SMEs and convert it into a sharable corporate asset.