5 AI Applications That are Redefining the Traditional Norms of Business Operations
Did you know that it is estimated that the evolution of artificial intelligence will eliminate 85 million jobs and will create 97 million new ones by the year 2025? Presently 37% of businesses all across the globe employ innovative artificial intelligence algorithms.
But that’s not all, folks!
The international market of artificial intelligence is anticipated to reach $257 billion by the year 2027. The total contribution of artificial intelligence and cognitive technology is expected to surpass the figure of $15.7 trillion by the year 2030. These ginormous figures depict that the progressive acquisition of artificial intelligence is unstoppable and will be brought from hype to mainstream in the near future. There would be no wrong in saying that artificial intelligence universally conjures up visions of accommodating personal assistants, self-driving vehicles, and intelligent robots.
Significant progression of artificial intelligence has been observed especially in the past decade. The best part about emerging innovative algorithms of artificial intelligence is they play a promising role in the enhancement of business operations. Enterprises of all sizes deal with different sorts of data each day, which leads us to the fact that it’s high time for them to acquire such measures to enhance data analysis and other business operations.
Let’s check out on some promising applications of artificial intelligence and cognitive technology that are redefining traditional norms of business operations.
#1 Digital Inquisitiveness:
The artificial intelligence algorithms in enterprise cognitive computing applications do provide definitive answers, but provide predictions based on probabilities such as whether the customer will buy this product or not, or will the loan be repaid or not, or the patient is suffering from certain diseases or not, etc. These predictive analyses help in decision making and assist them in deciding which areas to target for the promotion of the product, or which loans must be approved, or which treatment must be provided to the patient. Businesses need to integrate themselves with digital inquisitiveness to do predictive analysis efficiently and effectively. Digital inquisitiveness is a habitual inclination to circulating questions and data evaluation. This skill must be utilized for a better understanding of options provided by cognitive computing applications of enterprise and enhance outcomes. Broad-based application is required for the development of this capability.
#2 Operational Information Technology (IT) Backbone:
The operation information technology backbone, data foundation, and existing technology of the organization and people who respond to it encourage the utilization of cognitive computing applications. This provides the IT capabilities which are required for storing and accessing critical data. Integration of cognitive computing applications with other applications of enterprise provides reliable operations and enhances the cybersecurity protocols of an enterprise. Artificial intelligence algorithms learn from data available in the data inventory of organizations. An enterprise must make available an enormous amount of high-quality data that is tagged as well as clean. The least anticipated and most potentially difficult algorithm challenge in the development of artificial intelligence algorithms is the lack of high-quality data. Hence the integration of cognitive computing application is mandatory for structuring data properly and for the enhancement of business operations
#3 Data science competence:
Data science competence employs a wide range of skills which are significant for the technology of cognitive application of enterprise. It involves the assurance of the availability as well as the usefulness of tremendous amounts of data such as collecting, cleaning, tagging, curating, and the analysis of internal and external sources from numerous sources. Daa science competence also entails the identification, explaining the relationship among data, and the development of artificial intelligence algorithms that learn to identify probabilities and patterns from data. Incorporation of data science competence is expensive for such organizations that cannot develop talent internally and can require numerous hires from, such as technology consulting companies, software development companies, AI startups, and university programs in relevant fields.
#4 Recruiting and Hiring:
Organizations of all sizes are only as good as their employees. Innovative artificial intelligence algorithms assist in the implementation of the best hiring and recruitment practices. Machine learning and artificial intelligence can make the recruitment process more efficient, cost-effective, and agile just like numerous other areas of business operations. However, great organizations still rely on seasoned professionals’ final judgments.
Here are some of the methods of how applications of artificial intelligence are being utilized in the recruitment process:
- Filtering of resumes
- Analysis of demographics of the applicant pool
- Arranging applications to different hiring managers
- Automation of communication with candidates
AI-powered applications could effectively screen out applicants that do not have appropriate qualifications for the job. Those applications can send automated messages to candidates and inform them on the current stage of their application process. Not only this, artificial intelligence algorithms help in the elimination of repetitive and time-intensive tasks that are the basic requirement of every organization which is seeking to bring in new talent.
#5 Business Architecture Expertise:
The incorporation of enterprise systems has a history of disappointed leaders who underestimated the changes in organizations that were required to capture their value. Numerous leaders are re-experiencing this disappointment with enterprise cognitive computing (ECC) applications. ECC applications do not provide values unambiguously by data processing and providing outputs. They deliver values with the behavioral change of the organization, i.e. when the enterprise alters its practices, policies, and processes to attain and implement the insights from those outputs. Implementation of ECC applications assists enterprises in the enhancement of their architecture and creates business value. This also helps in the management of the transformation of the organization from old to new ones.
All in All
Consequently, the acquisition of artificial intelligence and cognitive technology is indispensable in this modern era of technological advancements. Enterprises at the bleeding edge of machine learning and artificial intelligence will be the ones reaping all the financial rewards and dominating the competition in the near future. Also, the misconception that robots will replace humans in the near future is just a myth. The real capabilities of machine learning and artificial intelligence are not going to replace humans. Instead, such innovative technology will play a promising role in enhancing their jobs and provide faster access to the relevant data to come up with better decisions.
