Managing the industry transition to Industry 4.0 (AI) seamlessly ..

Globally organisations are on the transition from Industry 3.0 to 4.0. At this stage it will be interesting for the Indian readers to understand the opposition during the stages of computerisation in the country.

Way back around the 80s and 90s when Indian industry was on a computerisation spree, the left trade unions went on a rampage across India and raised lot of hue and cry. Even with all the opposition, the country under the dynamic leadership of former PMs Indira Gandhi and Rajeev Gandhi went ahead. The country is reaping the rewards of that move now. We are one of the accepted soft powers of the world.

A similar situation is staring at us now when the world is on the threshold of transition to Industry 4.0.

Industry 3.0 (digital world) took out the boredom from routine, repetitive work while Industry 4.0 will take out the strain and exertion from cognitive work

Are we really prepared to switch to this technology yet ? Even though the technology may have developed in the labs and specifically with hundreds of focused startups across the world offering interesting AI apps or public consumption, for eg. Voila and Prisma are interesting AI image processing apps,  we are yet to fullly understand what are the societal and managerial challenges this adoption is likely to bring. Marking the course and pace of adoption is part of effective management of the process.

While going through the HBR article "Finding the right pace for your AI rollout", click here, I was reminded of the issues Indians had to face to ensure the tough roll out of computers. Now with AI, the situation is going to get grim and critical.

More than being of great help to the existing digital worker what the present trade union and workers union leaders tend to not realise or fail to understand is how the AI revolution can make things easier for the whole humanity. We are giving more of our cognitive decision making to the AI machines and taking only a few critical decision for the betterment of humanity, ensuring porsperity and abundance of resources.  

Understanding the task and role level impact is the basis for a successful implementation of AI in the organisation. We find that some of the tasks are only moderately impacted by AI and some more. We can also find through an innovative mapping mechanism provided by the HBR author of the above article, Rebecca Karp, faculty at HBS and Aticus Petersen a PhD student at HBS, the impact AI has on a task and on each role. 

Often we find employees are sceptical at implementing new technologies fast and quick as they are unaware of the complete impact of the technology on their life and work. The above HBR article also has come up with an excellent theoretical framework to assess the relationship between the implementation of the AI technology and its impact. 

When the willingness to adopt the new technology is high but the ability is low, the adoption of the technology should be stagewise at a moderate pace, getting the employees aware, providing them training and then implementing the technology slowly.

The Gartner hype cycle for AI adoption released in 2021 paints a similar picture. While AI General Intelligence is at the Innovation trigger stage, we find chat bots, Autonomous vehicles and computer vision is at the trough of disillusionment and on the slope of enlightenment. Edge AI and AI cloud applications are at the peak of inflated expectations.

Summing up all these interesting literature, we can safely assume that AI is on the firm path to adoption in our society. The second and third decades of the twenty second century will be very eventful and tumultuous in human history.

George.