As soon as we hear the words “artificial intelligence,” we picture robots and machines taking over like in Terminator or a hallucinogenic super-software controlling our world like in The Matrix. However, the current truth is far from the fictional accounts. AI is already all-pervasive and influencing our decisions and destinies, whether while shopping online or while deciding what meal to order from an app. AI is certainly here to stay and will forever change the way the world works. Manufacturing will particularly see the immense impact of machine learning, process automation, and robotics.
In reality, AI is far from the doom and gloom associated with sci-fi action movies. It has the ability to improve work in all industries and help companies become smarter, faster, and better at serving their customers. The intelligence gained through insights from complex self-learning and self-improving algorithms can help workers and staff make faster decisions, prevent losses and quality events, and improve plant uptime.
Top leaders in manufacturing organizations need to make the effort to understand AI and how it impacts work in the present, how it will affect work in the future, and how it can be used to optimize both workflows and workforces across the entire manufacturing value chain.
In a post, Forbes explains what AI is and how it can potentially impact the way work is done. AI is defined in the simplest terms by Britannica: “The ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” The intelligence associated with AI comes from learning, and this learning is a direct result of self-improving and self-optimizing algorithms. The algorithms that enable AI are able to modify themselves based on input data and can produce increasingly better results based on area of application.
In a research paper, MIT highlights that AI would not necessarily eliminate a human workforce. Rather, it would augment and complement humans such that there would be more job creation than loss. In order to understand why AI isn’t yet a threat to human intelligence, it is important to understand that it possesses what is called specialized intelligence, which focuses on solving one type of problem and performing one type of job. Human beings, on the other hand, possess what is referred to as a generalized intelligence, which is a combination of abstract thinking, problem solving, and critical judgment. Basically, when compared to human intelligence, AI is rigid and may fail to deliver value beyond what it is programmed to do.
AI has some common limitations that make it difficult for any artificial application to replace a human being:
- AI needs massive amounts of data to become more accurate. This data needs to be in the right format and context and made available continually for AI to deliver optimal results.
- AI might have programming or data bias, which might lead to less than accurate and biased results.
- AI needs copious amounts of computing power to succeed, which translates to high power and energy costs, making it unviable for the large-scale replacement of human intelligence.
The Forbes article clearly establishes that AI should be viewed as a technology that will augment and improve worker output and workflow performance. The main thought in leaders’ minds should be humans with computers rather than humans or computers.
The Impact of AI on Work:
McKinsey explains the impact of AI on work by stating that about half the activities performed by workers today can be automated in the future through the application of AI and automation. However, this does not translate to the elimination of jobs. Only about 5% of all occupations can be fully automated, with about 30% of the activities of 60% of overall occupations automatable by 2030.
McKinsey predicts that the proliferation and widespread adoption of AI will require workers to learn and utilize different sets of skills, which will translate to a large-scale and irreversible change in the way work will be performed in manufacturing and other sectors. While physical and manual skills will still be in high demand come 2030, jobs that require repetitive task execution and the application of basic cognitive skills will see a significant dip.
Jobs that require higher cognitive, emotional, social, and technological skills will see a significant increase. The article predicts that the jobs eliminated by AI will be largely offset by the jobs it creates, a figure that lands somewhere between 500 to 900 million new types of jobs.
AI will certainly change the workflows of each and every business and thereby forever impact the way workforces are recruited, managed, and trained. The McKinsey research makes it clear that AI and automation are both necessary and inevitable and that workers will need to adapt to these technologies and embrace the improvements they bring while acquiring the skills required to better use them.
For manufacturers, AI, automation, and robotics directly translate to better decisions, faster actions, and higher efficiency. All of this means lower costs and better business margins. The ability to act faster and in a more data-driven manner also makes the entire value chain more agile and resilient, which is extremely important given today’s uncertain market and geopolitical environments.
Webalo experts believe that the frontline workforce has been a blind spot for manufacturing leadership. AI and ML can have an impact on the data manufacturers handle, their operations, their workforces, and workflow optimization. Manufacturers lead the way in the adoption of process automation and robotics, but that does not necessarily translate to the level of improvement that AI or connected, integrated, and contextualized ML-based actions can bring to a shop floor or global manufacturing network.
AI-based learning and intelligence works best when an entire manufacturing process is connected and there is an operational flow from raw material to finished goods. This means that each and every transaction that happens from the store to the shop floor to the finished goods warehouse must be captured, structured, contextualized, and used for effective decision-making.
This can only happen when there is a platform in use that allows the frontline workforce to not only automate and digitize workflows but also capture data through IoT or enter it through their mobile devices. Aside from providing functional coverage, the platform should integrate with enterprise applications from the ERP to the MES and everything in between. Webalo does exactly this by providing full functional coverage and not allowing any data to slip out and become dark data.
Manufacturing leaders should remember that data is the foundation of AI, and a powerful platform like Webalo can help capture data and implement ML in the most neglected and often overlooked area of industrial manufacturing: the frontline. AI will be transformational for the enterprises that apply it. It will augment decision-making by providing actionable intel, expedite actions through predictive indications, and optimize workflows by allowing process stakeholders to take a deep dive and learn from events captured on and beyond the shop floor. Webalo enables complete data capture, applies ML to the data, and provides stakeholders with the ability to use this data and create a Workforce Intelligence Center that will optimize each and every activity performed manually or through partial/full automation.
If implemented correctly, AI has the potential to go beyond optimization and lead to innovation. But this will only happen if you get the basics right and choose a platform that provides mobility and configurability for faster adoption and the SaaS and cloud-based setup that forms the very foundation of AI. It is clear that frontline roles will transform and that workers will need to acquire new digital skills. AI, and the platform you choose to implement it, might just be the difference between unprecedented success or abject failure, so choose wisely!