Estimated reading time: 5 minutes

Artificial Intelligence (AI) has emerged as a transformative technology, revolutionizing industries and reshaping our daily lives. With its ability to process vast amounts of data and learn from it, AI is capable of powering innovative applications across various domains. In this article, we explore the “Seven Patterns of AI,” a framework that helps us understand how AI is reshaping industries and creating new possibilities. Let’s dive into each pattern, examining their applications and impact.

1. Hyper personalization

Hyper personalization refers to the tailored experiences offered by AI systems, catering to individual preferences and needs. One prime example is the recommendation algorithms used by streaming platforms like Netflix and music platforms like Spotify. These algorithms analyze user behavior, past choices, and demographics to provide personalized movie suggestions or curated playlists. Hyperpersonalization enhances user engagement and satisfaction, ensuring that individuals receive content aligned with their interests.

[image: Netflix and Spotify logos]

2. Autonomous Systems

Autonomous Systems represent a significant advancement in AI, enabling machines to operate without human intervention. Self-driving cars and drones are prominent examples of autonomous systems. Equipped with AI algorithms and sensors, these vehicles navigate and make decisions based on real-time data, enhancing efficiency and safety. Autonomous systems have the potential to revolutionize transportation, logistics, and surveillance industries, among others.

[image: Driving autonomous vehicles forward with intelligent infrastructure to understand the world context for the vehicles and take actions accordingly.]

3. Predictive Analytics & Decision Support

AI-powered predictive analytics leverages machine learning algorithms to forecast trends and outcomes. Organizations utilize these insights to make data-driven decisions, optimize processes, and mitigate risks. By analyzing historical and real-time data, AI can identify patterns, predict future trends, and offer decision support. This pattern finds application across diverse sectors, including finance, marketing, healthcare, and supply chain management.

[image: Predictive analytics within the healthcare industry is one of the examples, of how can AI save lives and predict diagnosis before it occurs based on patterns. ]

4. Conversational AI

Conversational AI refers to the development of chatbots and voice assistants that simulate human-like interactions. Virtual assistants such as Siri, Alexa, and Google Assistant have become integral parts of our lives, providing information, performing tasks, and even engaging in natural language conversations. Conversational AI enables seamless interactions between humans and machines, enhancing customer service, and streamlining processes across industries.

[image: integrations for Virtual assistants such as Mercedes-Benz takes in-car voice control to a new level with ChatGPT]

5. Pattern & Anomaly Detection

Pattern and anomaly detection is a crucial AI pattern used to identify patterns, trends, or deviations from the norm. AI algorithms excel in analyzing vast datasets and detecting anomalies, enabling applications like fraud detection, predictive maintenance, and cybersecurity. By continuously monitoring data streams, AI systems can swiftly recognize anomalies and trigger appropriate responses, safeguarding businesses and individuals from potential threats.

[image: Fraud detection using Anomaly Detection with Deep Learning]

6. Recognition Systems

Recognition systems leverage AI to analyze images, videos, or audio and identify objects, faces, or emotions. Image recognition technologies power applications like facial recognition for biometric authentication, object recognition for autonomous vehicles, and emotion detection for sentiment analysis. These systems are vital across various industries, including security, healthcare, and entertainment, providing enhanced efficiency and accuracy.

[image: Facial recognition used as biometric authentication]

7. Goal-Driven Systems:

Goal-driven systems utilize AI to solve complex problems by optimizing outcomes. These systems employ algorithms that learn from data and make decisions to achieve desired goals. Examples include AI-driven supply chain management, financial trading algorithms, and resource optimization systems. Goal-driven AI systems streamline processes, enhance productivity, and enable organizations to make better-informed decisions.

The Seven Patterns of AI showcase the diverse and transformative capabilities of artificial intelligence. From hyper-personalization to goal-driven systems, AI is reshaping industries and improving our daily lives. Embracing the power of AI enables businesses to stay ahead of the curve and leverage its potential to optimize processes, enhance customer experiences, and drive innovation. As AI continues to evolve, it is crucial to harness its capabilities responsibly and ethically, ensuring a future where humans and machines coexist harmoniously.

Note: The images used in this article are for illustrative purposes only and are sourced from the internet.

Estimated reading time: 4 minutes

“The metaverse is a completely new virtual world—just like social media presented a new CX channel 15 years ago,” says Sidharth Mukherjee, chief digital officer at Teleperformance, a global company that provides digitally integrated business services. “We’re starting to see metaverse adoption across industries like retail, consumer goods, and health care, in addition to social media, gaming, and the broader tech industry.”

Recently, there has been a lot of talk about businesses “migrating” to the metaverse, however this is a bit misleading. Brands are linking the metaverse to their conventional, two-dimensional channels rather than so much migrating into it. Nevertheless, it is impossible to emphasize how the metaverse may change the way that consumers and companies interact. The metaverse will revolutionize CX over the coming ten years, much like e-commerce did for retail in the 1990s and mobile did for social interactions in the early 2000s.

Let’s reimage how our shopping would look like in metaverse, blurring the barrier between physical and digital world.

Hybrid Shopping in Metaverse

It’s just a few years from now, and you’re shopping for new sneakers. You get a mobile notification from your favorite retailer—a new collection of sneakers has been released. You promptly grab your VR glasses and step into a digital representation of the store, where you design your fully personalized shoes, complete with custom colors. An AI avatar joins you to support answering all your questions along the way. Ultimately you hit Buy and uses your connected credit card linked to your account. Few mins later you receive the confirmation mail in your email and get the exact same pair digitally.

Preview Vacation destinations

There are equally intriguing use cases for the metaverse in the context of CX. A travel agency could showcase destinations via 3D “vacation previews” that provide enticing teasers of exotic locations and show sneak peek of what they may see when they head to those destinations.

Real estate

Already a decent number of interior design studios provide a 360 view for apartments to give a virtual tour for selling apartments to increase the rate of viewing the apartments. Ideally would be even better if you would go and check out the balcony view or walk around to get a better sense of dimensions.

In 2021, metaverse-related companies reportedly raised more than $10 billion, more than twice what they did in 2020. And so far in 2022, more than $120 billion has flowed into the metaverse.

The metaverse means different things to different people. Some believe it’s a digital playground for friends. Others think it has the potential to be commercial space for companies and customers.

Here are some real-world examples of metaverse applications

• For entertainment, you might attend a virtual concert or event: Lil Nas X performed in online gaming platform Roblox during the pandemic, for example.

• Commerce is shifting as we head into virtual spaces and shared experiences. According to McKinsey research, around 79 percent of consumers active on the metaverse have made a purchase, mainly to enhance their online experience. Virtual-to-virtual commerce—for instance, when a Fortnite player uses V-Bucks to make in-game purchases—is fairly common. Physical-to-virtual transactions are also being explored; toy company L.O.L Surprise! developed card packets with QR codes that can be scanned to unlock NFTs and virtual experiences.

• In healthcare, AR displays were recently used to perform surgeries on live patients at Johns Hopkins Hospital, helping its Neurosurgical Spine Center to execute tasks better than ever.

• Educational providers are creating coursework and materials that give teachers new ways to express and participate in classrooms; imagine that instead of building a papier-mâché model of a volcano you could virtually experience being the magma that’s ejected into the atmosphere.

• In heavy industries and other contexts, VR is being applied to help teach people new vocational skills, such as repairing trucks or other equipment—in some cases shortening training time considerably. And in field operations, people are using AR for remote assistance, which could be even more interesting as organizations begin to use the data generated from this process.

• In fashion and luxury, brands have made inroads. Take, for instance, Decentraland’s Metaverse Fashion Week in March 2022, which received significant industry attention and attracted brands such as Dolce & Gabbana, Estée Lauder, and Etro. The Gucci Garden, launched in 2021 in the Roblox gaming metaverse, saw 19 million visitors. Or consider new business models for virtual fashion, for instance, built around technology allowing for online showrooms or for 3-D virtual runways.

• NFTs, still in their very early days, represent a new asset class in financial services, with some reports that loans have been collateralized based on NFT value, and other forays into the space beginning.

• Metaverse concepts could also help build more efficient and productive operations. Take the example of BMW, which has an all-electric vehicle production line that ran as a simulation for six months. Virtual cars were built on a one-to-one scale in the metaverse before the factory’s final layout was determined.

Sources

• https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-the-metaverse?stcr=2442059EAF68499E914899E0CA2B7AA2&cid=other-eml-alt-mip-mck&hlkid=3d7655c3a3b74699a8e2a06e0894e341&hctky=11814925&hdpid=5e7643b3-afc5-4a20-a0b3-253b7e3390ec
• https://www.technologyreview.com/2022/09/12/1058144/embracing-cx-in-the-metaverse/