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SmartData Collective > Business Intelligence > Artificial Intelligence > Key Reasons Businesses Are Embracing AI
Artificial IntelligenceExclusive

Key Reasons Businesses Are Embracing AI

AI technology offers tremendous benefits for businesses of all sizes so they should invest more resources in it.

Alexey Utkin
Alexey Utkin
6 Min Read
businesses using AI
Shutterstock Licensed Photo - 1831742065
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Businesses are evolving and searching for newer ways to accomplish their goals, hence the need for artificial intelligence (AI). AI involves building smart machines to carry out tasks that typically need human intelligence, and AI simulates human intelligence using computer systems. The two major AI types used in businesses today are reactive machines and limited memory.

Contents
1.      Improved Customer Experience1.      Optimizing Business Management2.      Cybersecurity Solutions3.      Improved Marketing

Reactive AI machines are programmed with predictable outputs based on the input they receive. So, they use their intelligence to perceive the world and respond to identical situations similarly. Reactive AI does not store memory; therefore, it cannot rely on past experiences to inform real-time decision-making.

On the other hand, limited memory AI consists of machine learning models that can extract knowledge from previously learned facts, information, events, or stored data. They are more complex than reactive AI because they can analyze and use stored data to make better predictions, presenting users with greater possibilities. AI has tremendously changed the way businesses operate for the better by mixing human creativity with machine accuracy. Keep reading to discover some of the primary reasons companies adopt AI into their operations.

1.      Improved Customer Experience

Business success no longer relies solely on product or pricing; a satisfying customer experience is now necessary. Various knowledge management software use AI to create a knowledge-sharing culture that delivers a better customer experience. Through the combination of AI and machine learning that gathers and analyzes behavioral, historical, and social data, brands can now better understand their customers.

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Unlike traditional data management, AI continuously learns and improves using the data it analyzes to anticipate customer behavior. As a result, brands can improve the customer journey and provide highly relevant content, thereby increasing sales opportunities. For instance, AI chatbots implemented at strategic customer touchpoints help businesses uncover common customer issues and gain insight into what’s causing problems for users. Therefore, brands can create personalized solutions to such issues.

Furthermore, AI-powered chatbots can use programmed questions to generate and validate leads before moving them to sales agents. Chatbots can also initiate conversations with prospective customers based on their browsing history to help the sale or upsell post-purchase. Ultimately, AI creates improved, memorable customer experiences for businesses.        

1.      Optimizing Business Management

For businesses to grow, they must look for ways to optimize and improve their management processes. AI helps automate various tasks that consume employees’ work hours and perform such tasks faster and sometimes more accurately than humans. For example, many HR personnel in organizations spend their time on coordination, administrative, and control tasks such as adjusting schedules due to staff members’ vacations or illnesses. This can be performed automatically using AI-powered business management applications.

Also, AI can simplify job interview processes and lessen the workload of HR managers, freeing them up for duties that actually require their intervention. AI can easily shortlist resumes from large databases, automate the initial rounds of employee interviews, and monitor candidates’ facial expressions when answering questions to calculate their confidence levels. Furthermore, AI makes it easier to respond to applications and queries. When brands reach out to applicants quickly, they reduce the chances of losing qualified candidates to their competitors.          

2.      Cybersecurity Solutions

Cyberattacks have grown in complexity and volume, and they can cause substantial financial losses and reputational damage to businesses. AI helps security operations analysts stay ahead of threats by curating threat intelligence from several news stories, research papers, and blogs. AI technologies provide quick insights into possible cyber threats and reduce response times.

Cybersecurity professionals can now reinforce best practices for cybersecurity and narrow the attack surface instead of being continuously on the lookout for malicious activity. For instance, AI can efficiently and accurately analyze large amounts of business data and identify likely threats hiding in a company’s system. Businesses can segment risks from routine network activity and pinpoint threats more efficiently. Therefore, they can enhance their security measures by increasing the monitoring around commonly attacked areas of their network.    

3.      Improved Marketing

Marketing is an essential part of every business. However, people don’t like having random ads pop up when they’re online. Most times, such ads don’t help companies to achieve their marketing goals since they are irrelevant to the viewers.

Nowadays, brands use AI to improve the marketing experience and reduce waste time and resources on unproductive ad campaigns. AI machine learning prevents customers from receiving random ad suggestions and allows ads to appear based on customer profiling, audience segmentation, and people’s online behaviors.

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ByAlexey Utkin
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Alexey Utkin joined DataArt as Systems Architect and Team Leader in 2004, and has been in charge of leading major finance enterprise accounts since. With over 14 years in the IT industry, eight of them in the financial services sector, Alexey brings a wealth of industry expertise to DataArt and has become a core member of its Finance Practice. With a dedicated focus on solution, technology, regulation and process consulting, he now leads DataArt’s most seasoned industry practice from its London’s office.

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