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Optimizing business management processes is never-ending and hectic. You always have room for more optimizations and improvements. What if Artificial Intelligence can help us to optimize business management? Of, course, it is gonna save a lot of man-hours for many organizations, but the real question is, how far can AI help in business management?
Let’s find out!
This is a fact – Artificial Intelligence technology mixed with Robotic Process Automation technology (This mix is called Hyperautomation) can automate a wide variety of tasks that consume much of employees’ work hours. And another fact is that machines can perform tasks way faster and accurately as compared to humans.
According to PwC, Artificial Intelligence will contribute $15.7 trillion to the global economy by 2030. A part of this will be contributed by the applications and use cases of AI in business management, which is expected to saves time & reap huge profits.
According to MIT Sloan Management Review’s 2017 Artificial Intelligence Global Executive Study and Research Project, 85% of executives believe that AI will help their businesses gain or sustain competitive advantage.
The stats indicate that organizations that leverage AI can benefit from the enhanced operational efficiency offered by the technology and outrun their competition. If you are not sure how AI can benefit your business, you can watch this short video blow to build a better understanding.
Now that you have a basic understanding of how AI can benefit your organization, (if not, please refer to the video above), let’s explore the possibilities of optimizing business management processes with Artificial intelligence. As you know, a business runs on many wheels. Each wheel is a department. The success of a business is defined by how well these different wheels work smoothly and how well they work in tandem.
So let’s dig into the detail, how AI can help different departments to help improve your business processes.
Managers in an organization spend most of their time on a variety of administrative, coordination, and control tasks. For instance, HR managers must constantly juggle shift schedules because of staff members’ illnesses, vacations, etc.
From employee on-boarding to performance analysis, AI can offer many benefits to HR management processes. Here is a detailed article explaining how AI can help human resource departments.
A few examples of AI use cases in the HR department are:
Job automation: Using Robotic Process Automation, time-consuming tasks such as resume analysis, salary processing, responding to employee inquiries, performance evaluation, scheduling meetings based on attendee availability, etc can be automated.
Job interviews: AI can simplify the interview process and takes up a considerable portion of the workload of the HR manager.
AI can help to-
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Responding to applications and queries: Reaching out to applicants as quickly as possible is essential otherwise, losing the candidate to competitors becomes a big possibility. Applicants who have queries about their candidature and other related information seek quick responses. AI chatbots can step in and expedite this task and reduce the burden on the HR department.
AI chatbots perform most noteworthy tasks such as –
Screening resumes: While the current applicant tracking systems (ATS) have played a major role in reducing the burden. The spontaneous flexibility acts as a competitive edge for AI when compared to criteria-based systems. AI can screen thousands of resumes across third-party candidate providers that the company uses. And could be even programmed to add only the best-suited candidate to their ATS.
Incorporating Artificial intelligence in business management can help marketers and sales people to provide highly personalized consumer experiences. In addition it costs less than traditional high-dollar campaigns. Future optimization primarily depends upon the interaction of the consumer with a product or service.
Here are a few innovative ways marketers can use AI in their campaigns:
Lead scoring: Propensity models generated by machine learning can be trained to score leads based on certain criteria. It helps the sales team to establish how ‘hot’ a given lead is and whether they are worth devoting time to. Contacting most relevant leads saves considerable amount of time. Moreover, they can concentrate their effort where it is most effective.
Optimize digital advertising campaigns: Machine learning algorithms analyses large amounts of historical data. In order to determine which ads perform best on which people and at what stage in the buying process. With the help of this data, they can serve them with the most effective content at the right time.
Predictive analytics: Propensity modeling can be used to predict the likelihood of a given customer to convert. It can even predict at what price a customer is likely to convert or which customer make more purchases. This will help the managers to come up with creative strategies to push less popular products.
Let’s take a look at how AI can improve the operational efficiency of Finance and Ops departments.
Fraud detection:
The traditional techniques for fraud detection use static rules-based systems, which has several disadvantages associated with it, which make it less effective.
Today, AI can analyze business transactions and evaluate their threat score. This score is then ranked against a pre-established threshold that will mark the transaction as fraudulent or not. The main idea behind this is that fraudulent transactions have very different characteristics from legitimate ones. This can help to;
Automated virtual financial assistants: AI can monitor events, stock and bond price trends. Portfolio and financial goals of the user serves as the prime metrics for AI. It can then give recommendations regarding bonds and stocks to buy or sell. These systems are commonly called “Robo-Advisors” and are getting more popular in established financial companies and fintech startups.
Risk management: For financial institutions, risk assessment while giving loans is a very complex and critical process. AI can simplify most processes by analyzing relevant data of the prospective borrower. AI plays a key role in analyzing data related to –
Nevertheless, it shows the potential risks involved in giving loan. In fact it makes risk management much easier for businesses.
Managing customer data: Efficient data management is key to business success. Technologies like NLP, Data mining and text analytics can help to retrieve information from business documents efficiently and accurately.
Uses of AI in managing customer data includes –
Business intelligence: Business Intelligence solutions can help businesses to identify new opportunities and implement effective strategies based on key insights. Here is a detailed article explaining the possibilities of business intelligence
Applications of AI in the manufacturing sector opens up a wide range of opportunities for optimizing the manufacturing processes. Technology has drastically changed how organizations go about their manufacturing operations.
It is not a stretch to say that Artificial Intelligence in business management helps in every aspect of a business. Whether it be for simple tasks such as suggesting products or providing customers with basic customer service. Even in complicated measures such as conducting software tests and completing extensive problem-solving procedures. For this reason, it is important to say that Artificial Intelligence had become an unavoidable factor in our world.
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