Introduction to Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) is a cutting-edge technology that aims at imbibing human intelligence into machines. Machine Learning (ML), an important sub-branch of AI, trains the machines to learn, adapt and conclude based on the experience rather than a pre-defined set of rules. This enables them to develop analytical/statistical models from which they become capable of mimicking human actions. 

How does investing in AI & ML resources help the companies?

The field of artificial intelligence and machine learning has experienced numerous ground-breaking advancements during recent decades. This has empowered AI machine learning techniques the ability to exhibit promising results in many areas, including that of industries. Here is a gist of how organizations are making AI and ML work for them in their business processes and reaping the benefits.

  • Reduction in employee work pressure

Artificial intelligence technology can easily be deployed to handle repetitive tasks like addressing most frequently asked questions and/or monitoring routine transactions. With this, AI-equipped systems can successfully function as chatbots or customer support agents, considerably lowering the work pressure of employees. As a result, human workers can concentrate on other tasks that demand for creativity and absolute human presence.  

  • Maintenance of inventory

Inventory maintenance can be tedious and time-consuming, especially for a large enterprise. Nevertheless, this relatively simple task can be automized with minimal effort, making AI the best fit for the category. Even simple artificial intelligence and machine learning systems programmed using less complicated machine learning languages can effectively handle this business process, mostly with minimal or almost no human intervention.

  • Easy analysis of a huge dataset

Present world thrives with an enormous amount of data. This statement is true even with respect to companies, as they handle hundreds and thousands of transactions within a single day. AI aided machines can subject this huge voluminous data to critical analysis and can be trained to extract implicit patterns prevailing from-within. This ability of machines is seen to be undoubtedly superior in comparison to that of humans both in terms of time as well as efficiency.

  • Facilitate decision making

Not just analysis, instead, a well-trained, AI aided system can even draw inferences from the results derived. The insights gained from AI are often innovative leading to a noticeable transformation in the decision making process. For example, AI can be used to predict the most likely products that will be bought by a particular customer from a specific store. 

  • Help in market analysis

AI can be used to display the information or advertisement concerned with only a selected range of products. Trained artificial intelligence systems can effectively monitor the price variation in real-time, facilitating revision of commodity cost in accordance with the demand. With this, the sale process of existing goods can be automated while the business market can be expanded by discovering new, more-appealing products.

  • Ensure security maintenance

AI systems can be effectively trained to discover malpractices and fraudulent transactions. This ensures safe and hassle-free proceedings leading to increased customer reliability. This aspect might be of particular interest for the companies that develop fully automatic systems or those which deal with high-security information.

The benefits mentioned above cover just a small part of huge number of merits that can be leveraged from the use of AI in the industrial sector. 

Features facilitating Implementation of AI and ML

It is to be noted that the implementation of AI-oriented systems is not a cake-walk. This is because, although evolving at a rapid rate, it imbibes many unknown threads well within its architecture. For now, AI arena is considered to be an art of expertise and thus demands a dedicated team of AI specialists. Moreover, the implementation of machine learning techniques calls-for huge computational power and sophisticated resource requirement.

In either case, there are two possible solutions: 

(i) Allocation of dedicated resources 

If the employees within the firm are research-oriented and show interest in developing novel skill-set, then probably building a dedicated team to work on AI deployment would be suitable. Numerous courses/workshops and extensive literature can be used to consistently sharpen their knacks and know-hows. Similar is the case with hardware/software too. If potentially feasible, dedicated computing resources can be allotted to administer AI.

(ii) Availing third-party services

If, in any case, providing specific resources is not possible, then companies can always look-for third-party solutions. There are ample of top AI companies which offer help to implement AI in the form of expert team personnel. Likewise, there are even open-source software as well as cloud services provided to facilitate easy AI enforcement. This extended support particularly suits the best for the small enterprises, equipped with just-enough resources.

Although their aspects make AI deployment relatively easier, there are certain aspects specific to a particular company to be taken care-of while imbibing artificial intelligence. In fact, there might arise a need to redesign the entire business process while clearly marking the line where AI gains priority over humans. This is necessary as machine learning techniques are expected to work in harmony with the prevailing system so as to improve its efficiency while not disturbing the basic process. In order to accomplish this objective, the technology which best suits the application-in-hand has to be chosen amongst the numerous ones existing, again the task apt just for AI expert.

Conclusion

Rapidly advancing AI machine learning technology has shown promising results in various domains. In the industrial sector, deployment of AI improves efficiency, ensures security, increases customer relationship and trust, hikes customer retention rate, increases productivity, enhances job satisfaction, expands data processing capabilities, provides a competitive edge, improves management and increases reliability. In an overall sense, investing in AI and ML resources is seen to be critical to ensure sustained industrial growth.