The role of AI in Automation

As technology continues to evolve, Automation and artificial intelligence (AI) are becoming a constant that are transforming businesses and will bring productivity and contribute to economic growth. The use of AI in automation will also help the development of various sectors from health to agriculture.

Besides, using bother AI and automation will, in time, transform the nature of work and the workplace itself. Indeed, machines will be able to carry out many of the tasks usually done by humans, as well as complement manual work and perform some tasks that a human being wouldn’t be able to do. Hence, AI and automation have a lot to bring to businesses and industries across the world.

In order to shed light on this topic, we asked experts in the industry to tell us about the future of AI within automation.


AI vs Automation

Sankaran Lakshmi, Research Assistant at Christ University, defines AI as the way to induce programs to get more powers so as to achieve new solutions is not a typical way.

Hamza Mujeeb Khan, Project Manager at Azur Tech adds that AI is the technology that deals with the machine’s ability to learn things. It is really close to the functioning of the human brain. For instance, he continues, if we show an AI model 100 photos of cat and 100 photos of the dog and tell the machine to learn the difference between the dog and a cat, it should be able to determine if any other picture is one of a dog or a cat.

Moreover, for Pawan Kumar Reddy, Associate System Consultant at Columbus Global, AI is defined as the intelligence exhibited by machines to inculcate the ability to think, to build perceptions, to plan, and to respond like humans. The final aim of AI is to develop problem-solving skills so that it can assist humans with their daily chores efficiently.

Meanwhile, Sankaran defines automation as running something monotonous but without any interference.

Pawan adds that automation is a technique that helps make a repetitive task system operate without human touch. Hamza also highlights that fact by saying that automation deals with making things automatic. There is no learning part involved in automation. For instance, if you know that 10 steps are to be followed in making a cup of coffee, in order to do this task, you only have to build a machine and input those 10 steps and tell it to do it until you tell it to stop.

Here the machine will do the same thing over and over again hence producing the same cup of quality. In automation, he highlights, the quality of coffee won’t improve just because the machine has been repeating those steps for a while. Automation doesn’t have a learning aspect.


How can AI be used in automation?

AI is rapidly starting to take over many forms of technology and industries. Hence, it is not a surprise that it could be used to improve and speed up automation.

For instance, Hamza points out that with AI,  automation gets a new learning factor. Indeed, to come back to the previous example, with AI, the coffee will now be able to improve based on the number of times the automation runs as other parameters will come into play, such as comparing the output coffee with a better handmade coffee and telling the machine to figure out why the difference happened.

Pawan adds that AI makes automation smarter and more efficient within industries. For instance, it can help develop the algorithm to solve the issues quicker and without needing human presence. AI in automation can then be a huge benefit in sectors such as healthcare, manufacturing, banking, etc.

Sankaran also emphasized the fact that AI algorithms can help build automation cycles or pipelines.


How can AI improve automation and create opportunities for businesses?

Regarding business automation,  Sankaran tells us that AI can bring more intelligence into a manually regularly running business process or workflows. This then leads to more merits to automate them for quick decisions in workflows.

Pawan also adds that, by providing high efficiency and precision, AI can help or overtake the value of human presence in most the jobs. Indeed,  in the near future, it is expected that automation will replace at least 5-7% of jobs worldwide, and when combined with AI it would be able to reach a whole new level. With increase in productivity, the revenue stream will get bigger for companies as data will be the fuel. Thus, revenue stream would be used for further expansion of either businesses or pour into further R&D which in turn gives huge opportunities for other businesses as well.

For Hamza, AI can improve automation, but it also comes with challenges. Indeed, according to him, there is a chance it may negatively affect the quality of the product.

He continues by explaining that when AI is implemented into the machine to work things out, the machine might try to experiment with a new method or path that hasn’t been input by us. Hence, the machine just tries to take that approach to see whether it can improve the quality of the output. For instance, it’s like when a baseball player experimentally tries to hit the ball differently just to get a better shot. The shot can get better or even worse. The same thing happens with AI.

Therefore, to create opportunities in businesses the AI associated with that particular automation should be trained well before we put it into action.

Only then will it create opportunities for people who have good knowledge of AI and automation. In terms of business revenue, it will keep growing as the quality will be better and more consistent.


What can AI bring to automation?

AI can bring many benefits to automation. Sankaran defines three key ones:

  • Cost optimization
  • Quality assurance
  • Time optimization

For Pawan, the main benefits of having AI within automation are higher efficiency, productivity, and precision.

Moreover, Hamza points out that in automation,  a lot of data is generated from the already functioning system that is setup. Indeed, AI will add value to automation by using that data. Hence, the most valuable thing in AI is data.

In Automation, he continues, the quality of the output product is already known. The main aim of automation is to have consistency in producing that quality as well as to increase the production of the output which, otherwise, would have not been possible to this extent when humans do the tasks. Therefore, the impact of AI will help to improve the quality of the product and figure out ways to do things better.

For instance, twenty steps are involved in an Automation sequence, which at the end produces a product. The machine repeats these steps, and the products keep on coming out of the machine. The AI will help make this machine run for months and check every output and compare it with a better output product which will be provided by Data Scientists to the AI. This product, which will be provided to the AI, will be a handmade product with superior quality.

Thus, AI after comparison will be able to work out the way the steps are executed and will re-run the test until the quality is achieved.


But what are the risks?

Pawan points out four main challenges:

  1. Cost of implementation.
  2. Need of qualified human resources to implement or perform R&D
  3. Acquiring the necessary computation infrastructure and its maintenance
  4. Increase unemployment, creativity

All of this should come into play when thinking about adding AI to the equation.

For Sankaran, however, there are not many risks to using AI in automation. Indeed, as she tells me, humans need the automated machines to support to tackle the challenges in business as well as in life. Hence, an AI system can only be beneficial in the long run.

The only risk she highlights is that humans will be replaced by devices. However, the brain can never be automated, and thus, machines still can’t think for themselves.

On the other hand, Hamza wonders if we can afford to take the risk and challenges that comes in blending AI into Automation.

Indeed, when talking about AI, this itself has its own risk and challenges that are taken. The first challenge is that to know if we enough data. If not, then how to get that data. The second most important challenge is time: do we have enough time, or can businesses afford to invest that much time in blending the AI in their automation, and was it all worth the benefit?

Moreover, as Hamza points out, there will be times in automation where a lot of physical movements won’t be feasible with AI, especially when related to hardware. Indeed, in AI, the automation sequence may have to run 100,000’s of time. In software, it’s feasible as we have powerful machines that can do these tasks quickly but when it comes to sequences where physical movements are involved it won’t be a wise option unless the benefits are worth it.

Hence, these kinds of challenges need to be taken into account and thought about carefully before starting to use AI in automation.


The future of AI in automation

But then, what is the future of AI in automation?

Sankaran believes that more human tasks will be automated such as daily and repetitive tasks until we attain 50% automation of artificial intelligence.

Hamza thinks that AI in automation will be coming sooner than later. This could however be halted depending on the resources available for automation.

For Pawan, the future of AI in automation looks promising. However, it should go hand in hand with humans by not creating an adverse effect on human employment. We need to keep AI in check so that it doesn`t evolve beyond human understanding.

Therefore, it seems that, in time, companies and governments will be harnessing AI in automation in order to benefit from enhanced performance and productivity as well as all the societal benefits that come with it. The future with AI in automation comes with many challenges, but it will bring so many positive outcomes if technologies are used correctly, and the negative effects are mitigated.


Special thanks to Sankaran Lakshmi, Hamza Mujeeb Khan, and Pawan Kumar Reddy for their insights!

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