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9 Impactful AI in Business Examples


Trinh Nguyen

Jan 26, 2024

Many organizations have been incorporating artificial intelligence into their business operations, either as a standalone technology or by integrating it into existing enterprise software systems. In April 2023, a pulse poll conducted by EY revealed that 90% of technology leaders are currently exploring AI platforms like ChatGPT and Bing Chat, and 80% have plans to increase their investments in artificial intelligence in the coming year.

Given the rapid advancement of AI, the potential for its business applications is bound to expand constantly. But for now, in this article, we’ll look into 9 AI in business examples across three different domains, which have gained traction as of late, i.e. marketing, customer service, and cybersecurity.

Just a quick note before we get started: while many examples here come from multinational companies, there are also affordable and versatile solutions that small businesses can apply.

So, without further ado, let’s dive right in!

Common Uses of Artificial Intelligence Across Sectors

AI in Marketing

Among the departments in a company, marketing probably benefits the most from artificial intelligence. Understanding what customers want, finding products and services that meet their needs, and convincing them to purchase – all tasks AI tools can significantly enhance.

Below are a few notable use cases of artificial intelligence that can help organizations reach ambitious marketing goals.

  • Content generation

Since the launch of OpenAI’s generative AI platform ChatGPT in November 2022, many new applications of AI have emerged. Particularly, AI used for content generation can save loads of time and money for sales and marketing teams by producing blogs, marketing messages, copywriting materials, emails, chat replies, and much more user-centric content in just a short amount of time.

  • Audience segmentation

Thanks to AI tools for businesses, you can more effectively segment customers based on various personality traits, interests, and behaviors. This allows for better targeting, boosting customer engagement, lowering cost per acquisition (CPA), and increasing return on investment (ROI).

  • Programmatic advertising

Programmatic advertising means automatically acquiring and displaying advertisements on websites and applications. The marketing team can apply AI in programmatic advertising by leveraging customer history, preferences, and content. This process will result in a greater organization’s ability to offer more relevant ads with higher conversion rates.

  • Search engine optimization (SEO)

Incorporating artificial intelligence to enhance SEO enables marketers to create more effective tactics and rank pages better. Marketing professionals can also generate and optimize content with AI’s assistance, like SurferSEO, to meet the latest standards.

AI in Customer Services

AI in Customer Services

Artificial intelligence has a lot to offer when it comes to customer service. It can help automate basic questions, give round-the-clock assistance, and free up time for more complex and personalized interactions.

Some notable instances of AI applications in customer service are as follows:

  • Content Generation

Generative AI can analyze customer conversations, extract relevant data, and produce human-like responses to customer inquiries. It will help speed up response times and increase customer satisfaction. This is particularly true when the AI utilizes data collected from customer relationship management (CRM) systems.

  • Chatbots

AI-powered chatbots can aid with order tracking, product recommendations, troubleshooting, and responding to simple questions from customers instantly. Most importantly, they are accessible around the clock, strengthening customer service availability and boosting customer relations.

  • Sentiment Analysis

AI technologies do a great job of evaluating customers’ emotional sentiments. These tools track and analyze reviews, social media interactions, and customer feedback for multiple purposes. They can help businesses identify areas in need of improvement, address client complaints, and offer tailored experiences based on their preferences.

  • Recommendation Systems

AI recommendation systems examine customer behavior, past purchases, and preferences to provide custom content or product recommendations. In addition, companies can also boost cross-selling and upselling opportunities by utilizing the personal preferences of each consumer.

  • Predictive Analytics

AI-based predictive analytics makes use of customer data to forecast their needs, behavior patterns, as well as potential issues. This way, organizations can proactively handle customer concerns, optimize resource allocation, and personalize customer touchpoints.

  • Self-Service Solution

Knowledge bases and FAQs are two key examples of AI-powered self-service platforms that use NLP to decode customer queries and deliver relevant knowledge or troubleshooting instructions. As a result, customers can quickly find answers without requiring help from human employees.

AI in Cybersecurity

AI in Cybersecurity

Over the past years, there has been a growing interest in the use of artificial intelligence in cybersecurity. Investments have been made constantly to develop and improve AI-powered cybersecurity solutions to mitigate cybersecurity risks before they occur.

  • Threat Detection and Prevention

AI technology is particularly skilled at detecting threats. It can process massive amounts of data from various sources and identify abnormal patterns in users’ behavior, potentially indicating a cyber-attack. For instance, when an employee unintentionally clicks on a phishing email, AI systems can swiftly notice abnormality and notify us of a potential security breach.

Plus, by automating incident response actions, such as isolating affected systems or blocking malicious activities, AI reduces the likelihood of attackers and lessens the possible effect of security breaches.

  • Security Operations and Automation

Time is of the essence when it comes to addressing cyber threats. With a manual threat detection and mitigation process, hackers have enough time to encrypt or steal data, conceal their actions, and establish hidden access points within your system. But, with AI, businesses can automate repetitive tasks in threat detection and promptly respond with necessary actions. IBM has found that AI implementation shortened the time required to identify and act against cyber threats by up to 14 weeks.

AI can also autonomously scan systems and networks to detect potential entry points for attackers. Besides, since AI solutions excel at recommending and prioritizing security updates, they help accelerate process automation and reduce vulnerability exposure. As an illustration, IBM’s managed security services team leveraged these AI capabilities to automate 70% of alert closures and significantly accelerate their threat management timeline by over 50% in the first year of implementation.

Examples of AI in Business

#1 AI-driven Programmatic Advertising

I-driven Programmatic Advertising

As the name suggests, programmatic advertising uses artificial intelligence (AI) technologies to automate the buying and selling of advertising space in real-time. This advanced approach aims to improve the efficiency, effectiveness, and personalization of ads.

The Economist, a famous British magazine, has done a great job of implementing AI in their advertising strategy.

The story started in 2017 when the magazine experienced a decreased readership despite being a highly regarded digital publication.

The publication then took advantage of AI-driven programmatic advertising to buy and sell targeted ads autonomously. By gathering and closely examining customer data, The Economist was able to pinpoint a particular audience segment that was believed to be reluctant readers.

Through independent web and app usage analysis, it could then delve deeper into user behavior and even their reading interests, thereby coming up with more effective outreach strategies online. Additionally, the publication has seen a rise in readership as a result of its focus on matching cookies, subscribers, and other data sets to uncover new customer segments and build lookalike audiences.

In the end, this innovative strategy increased the number of readers by 3.6 million and yielded a 10:1 return on investment, which is no small accomplishment given today’s highly competitive digital world. Since then, this new data-driven, AI-focused business model has firmly solidified The Economist’s subscriber growth, with an astounding 9% increase (90,000 new loyal customers) in 2020/2021 alone – an incredible achievement in these trying times.

#2 User-generated Content

Another application of AI in the marketing sector means letting users of an online platform create content of any form, including images, videos, text, reviews, etc. Often, this content is publicly available and can be spread across social media channels.

In 2023, the iconic brand Coca-Cola elevated its AI marketing by collaborating with OpenAI and Bain & Company to launch its own consumer-facing AI-powered creative platform, Create Real Magic. With this product, the company aimed to involve the global audience in its creative process. Essentially, fans are encouraged to engage with the brand on an ultra-personalized level by using Create Real Magic to produce their AI-powered creative artwork that might get featured in official Coca-Cola advertising campaigns.

This highly immersive AI application is the perfect combination of skillfully adopting the user-generated content (UGC) strategy and autonomous technology – a true illustration of the brand’s continuous innovation.

#3 Tailored Content

Different from user-generated content, tailored content is produced by brands or companies to specifically meet the needs, preferences, or interests of a particular audience segment. Businesses can consider various factors about the target audience, such as demographics, behavior, geographic location, personal interests, and past interactions.

To strengthen its content marketing efforts and build personalized communications for the audience, global food and beverage giant Nestle employed natural language processing (NLP) technology to develop tailored content for its many different audience segments.

With this content-centric innovation, Nestle consistently turns valuable insights into action by utilizing AI-driven big data processing platforms to see through its customers. This approach has led to new technology adoptions like chatbots and virtual assistants like Cookie Coach called Ruth.

#4 AI-driven Digital Marketing Strategy

Artificial intelligence is performing really well in planning, executing, and refining a business’s digital marketing efforts. It analyzes vast amounts of data faster and more accurately than humans, enhancing efficiency, personalization, and effectiveness in a marketing campaign.

HubSpot, a reputable force in digital marketing, consistently remains at the forefront of new trends and technologies, artificial intelligence included.

The brand employs artificial intelligence in various key pillars of its digital marketing strategy, such as:

  • Finding relevant topics quickly and efficiently with generative AI.
  • Generating engaging article or blog post outlines utilizing ChatGPT and similar AI technologies.
  • Speeding up the brainstorming process for content marketing with targeted ideas and subject matter.
  • Experimenting with video content and working alongside its in-house human marketing specialists to create email summaries, rich snippets, and meta descriptions.

#5 Trip Planning Bot

Trip Planning Bot

Talking about trip planning bots, we think of AI-powered software that assists users in planning their travels. It provides a wealth of information and services, from booking flights and accommodation to suggesting itineraries, handling changes in plans, providing local information, and even making recommendations based on personal preferences.

If you travel often, chances are you’ve used or at least heard of Expedia before. It offers a wide range of travel services, such as flight and hotel bookings, package deals, and destination guides. To enhance the trip planning experience for users, the brand has managed to incorporate ChatGPT into its mobile app seamlessly.

With the new trip planning feature, travelers can engage in a natural conversation with an AI bot. They’re able to quickly get recommendations, explore activities, and receive travel assistance without any delays or waiting for an agent.

#6 Support Chatbots

It would be a huge missing out without mentioning virtual intelligent chatbots. Companies often implement them on websites or e-commerce stores to provide immediate responses to customer inquiries, essentially offering customer service support.

Global retail giant H&M has increasingly utilized generative AI to enhance customers’ online shopping experience by helping them easily and quickly find desired clothing and accessories.

On their website, the AI chatbot has significantly reduced response times, resulting in a more satisfying customer experience. Besides, new updates on the mobile app enable shoppers to effortlessly find desired products by simply using voice via an advanced AI voice assistant.

Not only can the chatbot assist shoppers in locating specific products, but it can also provide answers to frequently asked questions and offer support with placing orders. This way, H&M has been able to provide customers with a more convenient and enjoyable experience while also relieving the burden on its customer service team.

#7 Facial Recognition Systems

AI in Business Examples - Facial Recognition Systems

A facial recognition system identifies or verifies a person by comparing and analyzing patterns based on the person’s facial contours. It’s a biometric technology that works by mapping facial features from a photo or video and comparing this information with a stored facial database to find a match.

KFC is a prime illustration of a brand that leverages artificial intelligence to provide a tailored shopping experience. Back in 2017, they worked together with Baidu, a Chinese internet giant, to create a facial recognition system that can anticipate a customer’s order.

The system provides different menu suggestions that carefully consider each individual’s estimated age and current mood. For example, a 20-year-old guy might be offered a meal consisting of a crispy chicken sandwich, roasted chicken wings, and a Coke. For breakfast, it recommends a 50-year-old woman a nourishing bowl of porridge and a glass of soybean milk.

This expedites the ordering process and delivers a personalized experience that many customers find enjoyable and refreshing.

#8 Automatic Suspicious Transactions Detection

Automatic suspicious transaction detection systems mainly serve banking and financial industries to identify potentially fraudulent or unusual activities. These platforms typically employ artificial intelligence (AI), machine learning (ML), and complex algorithms to detect and flag transactions that deviate from regular patterns or comply with typical fraud indicators.

The first case study is the renowned online payment PayPal, which incorporates an AI system to address money laundering and catch suspicious transactions.

Transaction analysis – a crucial element of PayPal’s cybersecurity strategy – also happens to be where AI plays a significant role. Given the large number of daily transactions on the platform, manual fraud detection would be an incredibly challenging endeavor. AI’s rapid processing capacities shine through as it efficiently examines each transaction for potential red flags.

Furthermore, PayPal is committed to identifying and blocking malicious websites as part of its ongoing efforts to ensure security. The system also works tirelessly to scan websites and detect any malicious content or potential cyber threats, as cybercriminals are always coming up with new tactics to deceive users via phishing and scam websites.

#9 Cybersecurity Detection Systems

Like PayPal, the multinational financial services enterprise Wells Fargo has implemented an advanced AI-powered platform to detect and respond to cybersecurity threats. The platform uses cutting-edge machine learning models and algorithms to analyze large volumes of data, such as network traffic, email communications, and files. By analyzing this data in real time, the AI system can efficiently spot potential threats and unusual patterns that might signal malicious activities.

As soon as a potential danger is identified, Wells Fargo’s AI system will automatically initiate proactive response measures. It can, for example, instantly block harmful traffic or isolate infected files, stopping the threat from spreading throughout the organization’s network.

Leverage AI for Your Business with Neurond

Artificial intelligence continues to push the boundaries of what is possible in business management, from marketing and customer service to cybersecurity. Apart from the nine examples discussed above, many other organizations have grasped the chance and taken advantage of AI to maximize their business processes and profits. So, what do you do?

Not every company is ready to adopt an AI strategy, of course, and we get that. That’s why, here at Neurond, we respect your business needs. Taking a trusted advisory approach with our partners, we commit to providing a solution that fits your organization. Having a team of highly skilled technical and analytical engineers with unrivaled expertise, we are confident to bring you state-of-the-art solutions, from machine learning, natural language processing, and chatbots to recommendation systems and custom model building. Whatever you need, we serve!

Contact Neurond now to unlock the power of AI!