Artificial intelligence has long been confined to the confines of science fiction films and academic papers. However, due to its widespread use in our daily lives, this characterization is gradually fading. AI has now become a household name. You’ve likely used it to check your social media feeds, search the web, or on your daily commute to and from work. You might not be aware of it, but AI has a significant impact on your everyday life. The application of Artificial Intelligence in business, however, is still in the early adoption stages. Many of the technological business solutions we see today are considered ‘weak AI,’ and organizations are yet to realize their full potential.
Artificial intelligence will have created 58 million new jobs by 2022, disapproving the misconception that the adoption of AI will render many people jobless. So how exactly can you leverage the benefits of Artificial Intelligence to improve your business operations?
In this article, we are going to take you through the benefits of Artificial Intelligence in the business area. But first, let’s begin by defining what artificial intelligence means.
What is Artificial Intelligence?
Artificial intelligence is a broad term that refers to the use of big data sets to develop computer systems that perform intelligent tasks. In simple terms, it’s the imitation of human intelligence by computer systems and machines to perform problem-solving and decision-making tasks. This technology is gaining more relevance because it doesn’t need human intervention to develop a particular solution. Once the software programs have been fed with the necessary information, then that’s it.
AI came into life in the early 1950s after it was demonstrated that computers could learn checkers’ strategies and speak English. And since then, the field has made tremendous progress, especially with the development of more powerful computers.
What is AI in business?
Organizations can no longer rely on the traditional brick-and-mortar methods of operation to drive business growth. The limitless amount of data available today has opened a new realm of possibilities, and Artificial Intelligence plays a pivotal role in this revolution.
Artificial intelligence in business involves the use of data to derive valuable and actionable insights that can be used to boost revenue, increase productivity, and improve customer experience. However, this is an uphill task without the use of other supporting technologies such as machine learning, data science, and predictive analysis.
Business needs that AI can support
Organizations shouldn’t look at AI through the lenses of technologies but rather business capabilities. There are three primary business needs that AI can support: Process automation, cognitive insight, and cognitive engagement. Let’s go through them in detail.
Cognitive engagement
Artificial intelligence plays a huge role in a cognitive engagement strategy. Many companies tend to use cognitive engagement to interact more with employees than their customers. It involves the use of chat bots or intelligent agents that employ natural language processing to perform tasks such as product recommendation, answering team member questions, and delivering website content based on customer history.
Process automation
Right from its beginning days, the main goal of IT has always been to automate the manual processes of a business. We have come a long way from mainframes to business process management (BPM) based workflows to client-server application developments.
Today, robotic process automation (RPA) has become a viable solution for businesses looking for intelligent automation. It mimics human behavior to automate manual tasks for efficiency and speed. Some examples include processing insurance claims, handling customer communications, and scanning documents to obtain important information using natural language processing.
Cognitive insight
Cognitive insight uses algorithms to detect data patterns. With large volumes of data, it’s pretty difficult for humans to detect minute changes in patterns where anomalies exist. AI not only detects the changes but also tracks results to see how it affects future behavior. Some examples include identifying security threats to computer networks, predicting consumer behavior, and nurturing customers at different stages of the purchasing journey.
Business functions that use artificial intelligence
Sales
Artificial intelligence helps predict customer needs, forecast sales, and improve communication within an organization. All this is possible because the technology can automate and augment the sales process.
And as a result, salespersons can now manage their time well and focus their efforts on the things that matter.
While there’s a side of product marketing that humans uniquely perform, AI can provide salespersons with insights that help improve the sales function.
the adoption of AI in optimizing sales is expected to grow more than any other technology. The report also found out that successful businesses are 3.1 times more likely to be using Artificial intelligence than their unsuccessful counterparts. And yet, AI cannot fully replace salespersons.
Marketing
Businesses are looking for new ways to reach and attract their target audience. The rapidly evolving business landscape has rendered traditional marketing efforts ineffective in reaching people and achieving results. If your business isn’t already using AI in marketing, it’s lagging behind.
Marketing teams use AI technologies to develop and execute marketing strategies based on data collection, data analysis, and economic trends that impact marketing efforts. AI tools leverage data to create customer profiles that help in understanding customer demographics and interests. Then, they help you make targeted ads based on browsing history, giving customers suggestions of precisely what they are looking for.
Customer experience
Online retail has become more competitive than ever, especially at the height of the covid-19 pandemic. As a result, businesses are turning to Artificial intelligence to enhance their online shopping experience. Amazon was one of the first brands to use AI to customize purchase recommendations and adjust its pricing to stay competitive. Currently, more and more companies are turning to AI to improve their customer experience.
Chat bots and voice assistants are some of the most used AI tools in customer service. Customers prefer to communicate with a business in real-time when making a purchase, just like how they interact with a salesperson at a brick-and-mortar store. And therefore, adding a chat functionality to your website can help improve your customers’ shopping experience by answering their questions when making an order.
Human resources
AI integration into human resources has revolutionized practices such as recruitment and talent management. AI tools can make real-time decisions based on algorithms and computing technologies, making it easier to screen candidates, schedule interviews, and maintain databases. And as a result, the hiring time has been significantly reduced.
An AI-based chatbot, for example, can match the profiles of potential candidates against the position requirements and narrows down the list to candidates that match the job description. It then goes ahead to schedule interviews and can even hire qualified applicants. This saves the hiring team’s effort and time, making them free to focus on other tasks.
Manufacturing
AI robots are gaining popularity, specifically in industrial manufacturing, where they are used to revolutionize mass production. Robots can perform recurring activities that would typically require manpower. While humans work in three shifts to ensure continuous production, robots are capable of working 24/7. And as a result, they boost production and eradicate human error.
AI robots also help condense operation costs. Although it’s pretty costly to bring the technology onboard, the ROI is worth the investment. Operating cost is reduced by a significant margin when machines take care of daily tasks.
Another application of AI in the manufacturing sector is the use of predictive intelligence to predict demand. Demand prediction allows businesses to ramp up productions when the demand is high and vice versa. AI also tracks the production process and flags areas of concern before they erupt into costly issues.
Heineken is an excellent example of a company that uses AI in manufacturing. It uses data analytics in every step of the manufacturing process, right from the supply chain, to keep tabs on inventory on the shelves.
Accounting and finance
One of the main reasons why AI is appealing to many organizations is the promise of cost reductions and efficient operations. Robotic process automation, in particular, produces impressive results in the accounting and finance departments. It completes repetitive tasks such as data recording, sorting transactions, and tracking price changes from vendors. And as a result, finance professionals are freed up to focus on higher-level activities.
It’s a significant upgrade from brick-and-mortar accounting and bookkeeping that uses manual data entry, which is usually slow and inaccurate due to human mistakes. With AI, computers can now complete tasks with higher speed and accuracy than humans.
AI technologies such as deep learning, natural language processing, and machine learning give valuable insights into an organization’s financial data. Access to real-time financial understanding unlocks new levels of business success. It impacts a business’s vendor partnerships, hiring decisions, sales negotiations, and much more.
IT operations
Artificial intelligence for IT operations(AIOps) is an essential aspect of digital transformation in organizations. It’s often the first encounter businesses have with materializing Artificial intelligence internally. You’ve most likely heard or read about it having a massive impact on administration and system operations. But what exactly is AIOps, and why should you pay attention to it?
AIOps is a term used to refer to the use of advanced analytics to automate business operations. It integrates deep learning and machine learning to create predictive outcomes that provide actionable and intelligent insight to facilitate business growth.
There are multiple layers of technology that make up a business’s IT infrastructure. This is why you need AIOps to build context-rich data lakes that cut across all the layers to collect, consolidate and contextualize data. It also helps identify issues within the system so that IT personnel can proactively fix them before the system breaks down.
Contact centers
The application of artificial intelligence in contact centers is still new and evolving. Organizations that have adopted it use it to enhance rather than replace human power. It reduces operational costs, increases agent efficiency, and provides unmatched customer experiences. Some of the most common AI applications in contact centers include:
•Chatbots: When customers visit your website, chatbots greet them, collect their background information, and solve their issues. AI chatbots, however, cannot solve complex customer issues. Those ones need an agent’s touch.
•Intelligent Routing: Contact centers use AI to route inquiries based on customer personalities and information derived from previous contacts. Linking up customers with the right agent at the right time can significantly improve the customer experience.
•Analyzing large data sets: Analyzing colossal data sets is quite overwhelming to humans. Let’s say you offer online courses, and you’re trying to find a way around your workforce scheduling for the year. It’s probably hard to find a middle ground since you constantly find yourself over or understaffed. However, you can use AI to monitor data sets of previous calls and bookings to develop an accurate trend map that will allow you to schedule your team effectively.
Facility maintenance
Businesses lose billions annually to machine downtime caused by increased usage, aging, changing seasons, among other factors. AI-enabled FM software can predict faults and schedule preventive maintenance by analyzing historical data on past failures. An excellent example of AI-enabled software is the Decision Engine. It uses predictive analytics to make data-driven decisions when reviewing proposals, selecting contractors, and scheduling maintenance.
AI also helps facilities to reduce energy expenditure. Typically, businesses spend big money on energy resources such as heating, cooling, electricity, water, and ventilation.A typical business facility in the US uses 19% of its total expenditure on energy-related costs.
Clearly, this sector needs management attention. AI provides solutions for dealing with main energy drains such as electricity, HVAC, and refrigeration. For example, it can turn down the heat when it’s least needed, based on historical data patterns.
Research and development
Artificial intelligence and Machine learning play a pivotal role in research. They increase productivity and optimize the costs of complex projects. In the modern business landscape, innovation is the main driving force behind success. It is characterized by the upgrade of facilities and improvement of products and services sold in the market.
AI helps solve issues and boost innovation. It has resolved the issue of data analysis, making it easier for researchers to find the relevant information necessary to perform research. And as a result, R&D activities are now more strategic and practical.
Challenges of artificial intelligence in business
AI’s ability to revolutionize the business space has made it grow and gain popularity at an excellent rate. And as a result, several organizations are now investing in the research and development of AI applications such as robots and automated cars. However, it’s also important to note that the technology is still facing a couple of challenges.
Here are some of the setbacks that companies face when trying to implement AI:
Data security and storage
AI applications use data to make intelligent decisions. The disadvantage of using large volumes of data is that it may overpower the business’s storage capacity or result in data security issues. This is why a business must adopt the right data management system if they want to implement Artificial Intelligence.
An excellent data management system will not only offer security to sensitive data but will also make it easier for companies to retrieve siloed data for Machine Learning and Artificial Intelligence projects.
Infrastructure
AI-based systems use high levels of computational speed, which is why businesses planning to adopt this technology need substantial infrastructure and high-end processors. For many organizations, replacing traditional legacy systems with new cutting-edge systems is still a major challenge that derails the implementation of AI.
Determining the right data set
AI implementation starts with the use of the correct data set. With different types of data flowing across organizations, it can be challenging to determine which one to use.
And therefore, if you want to improve the learning and decision-making process of AI implementation in your company, you have to get in touch with experts in the field. They will guide you through the correct approach to achieve your desired results.
Final thoughts on artificial intelligence in business
The buzz around AI continues to grow each year. Its use in business applications such as natural language processing and data analytics is unmatched. However, the discussion around this technology elicits mixed feelings.
Some people feel like the revolution has come to reap them from their jobs, while others are excited about the overblown prospects of what they can realize with machine augmentation. But the fact remains that AI is a guiding light to the revolutionary future of business.
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