Acceleration of AI in the Post Pandemic Production

How AI is accelerating output in the post pandemic production



According to the recent research made in the post-pandemic, AI is accelerating to the highest extent.  It is expected that AI will make processes more optimistic and help to design new products, services, and business models. 

With AI-based management solutions, supply chains across all the industry sectors are becoming progressively diverse and digitally driven. AI helps in providing end-to-end visibility that allows organizations to make use of opportunities. For instance, Alaska Airlines is using an AI-driven flight management system that can assemble and analyze datasets more swiftly than human operators. The airline is using this information to abridge flight times, reduce delays and minimize costs. The AI system supports human dispatchers in their work and does not replace them.


AI-Enabled Productivity 

Google mentioned its development of reinforcement learning deep neural network that creates computer chips faster than humans. This is the result of Artificial Intelligence accelerating in the technology market. Google is using AI to create chips that can be used to design much more advanced AI systems, also speeding up the already existing performance through an elevated cycle of innovation.

However, It is not only Google that is initiating semiconductor chip design using AI. Chip development company Synopsys recently illustrated how a problem that had previously taken months of work by an entire design team could be achieved with high-end results in just a few weeks by a single engineer. These are just a few instances highlighting the potentiality of Artificial Intelligence. All of the major chip designers and semiconductor tool companies are deploying some aspect of Artificial Intelligence.

One of the new generation software development tools is Copilot, an AI-powered programming tool jointly built by OpenAI and GitHub that is positioned as an augmentation for human programmers. The tool uses Codex, which is based on GPT-3 but fine-tuned for programming tasks. 

AI-enabled automation is starting to have an impact. In a panel discussion, Sanjeev Vohra, Accenture global lead for applied intelligence, explained that he had observed a “gigantic shift” in companies toward using technologies like AI, analytics, and machine learning, which is uplifting revenue and efficiencies. This shift will head towards a productivity boom. Artificial Intelligence is already better than humans at certain applications and businesses using AI tools will soon see an acceleration in their productivity.

Given the combination of wage growth and labor shortage because of the hit of Covid-19, the demand for automation is rising. Till now there is not any large impact of Artificial Intelligence on employment that can be seen. But yes this can change in the future or is already starting to change. 

PWC talks about the cycles of automation that will extend to the 2030s, and each will have its own level of job impact. These cycles include the algorithm wave, the augmentation wave, and the autonomy wave. According to PwC’s report, only around 3% of jobs are at high risk for automation from the algorithm wave in the early 2020s, but this can rise to almost 20% by the late 2020s from the augmentation wave, and around 30% by the middle of 2030s.

It is daunting that AI-powered automation might have an impact on jobs. But with competitive pressures faced by the industries and enterprises, it is not possible to resist technology advances rather it will lead to further automation. A recent survey shows that 68% of office workers are actually demanding more Artificial Intelligence to help them in their daily work. 


Accelerating Output of AI

With the hit of Covid-19, companies are digitizing to an extended level. With the emergence of digital transformation, all businesses and companies are demanding automation that can assist the workers to better serve their customers. The pandemic has created an exceptional need for speed and scale in addressing customer queries. For instance, AI chatbots, by learning from samples over time, chatbots are only getting better and faster at solving problems, but can also provide awareness that helps enhance products. 

AI has the potential to traverse the current organizational process among the business units. Tools like Artificial Intelligence and RPA can create connections across organizations, allowing a characterized view of the customer that allows delivering personalized value in real-time. New opportunities will also appear for humans to work in production with machines to intensify the overall impact. Despite just using Artificial Intelligence to do the same things better, the cooperation between humans and smart tools can create new possibilities for delivering real-time value and developing a new kind of workforce.