While you would love to use products and gadgets with artificial intelligence, it’s not just meant for consumers like you. Instead, it’s meant for businesses as well. With the rise of various devices like smartphones and tablets, customers have now access to different channels for shopping along with traditional retail stores.
Providing them a seamless shopping experience over the channels with context driven communication has become very important which is evident by the following statistics by Invesp- organizations implementing omnichannel customer engagement techniques have an average customer retention rate of 89%, while companies with inadequate strategies retained 33% of their customers.
PWC says by 2020 the omnichannel customer experience will be enhance by its need for accurate execution. Our aim in this paper is to establish that a perfect execution of omnichannel customer experience is better implemented through omnichannel synergy instead of omnichannel integration which has certain drawbacks. . In fact, being “overly integrated” could result in rigidity and tardiness in responding to the fast-changing retail environment driven by changing consumption patterns and new technologies such as the Internet of Things and artificial intelligence.
Businesses go into integrating different channels like physical store, laptop purchase or smartphone but the customer is not thinking about channels. They are seeking a seamless and consistent shopping experience across channels.
A survey by eMarketer shows that when it comes to holiday shopping, consumers almost equally purchase from online and offline channels. Therefore, we need to start placing consumers along a buying journey and think of how to make this journey as experiential and effortless as possible.
The Top ten AI Technologies You Need to Know About
However, enhancing customer experience isn’t the only thing artificial intelligence can help us with. Here are the top ten AI technologies you can wait for, which has the potential to change life as we know it.
On the basis of analysis from Forrester here are the 10 hottest artificial intelligence technologies coming in the market:
1. Generation of natural language
This process involved generation of text from computer data. This feature is used currently in summarizing intelligence insights from businesses, report generation and, customer services. Some of the examples are: Yseop, SAS, narrative science, Cambridge semantics, automated insights etc.
2. Recognition of speech
This is the process of transcribing and transforming human speech into suitable formats for a computer application. Currently, these technologies are used in mobile applications and interactive voice response services. Some of the examples of vendors providing this service are: NICE, Verint Systems, OpenText.
3. Virtual agents
This has received much attention and ranges from simple chatbot to other advanced systems which can build a network with the human being. This is now in use as smart home managers to customer support and services. Examples are products available from Artificial Solutions, Apple, Amazon, Assist AI etc.
4. Machine learning platforms
These platforms offer data, training and development tools, APIs, algorithms and computer power to deploy models train and design applications, different machines, and processes. At present this is used in classification and prediction type of enterprise applications. Some well-known vendors are: Microsoft, Google, Amazon, SAS etc.
5. Hardware optimized for Artificial Intelligence
These are appliances and units for graphics processing particularly architected and designed to run AI-oriented computational services efficiently. Currently, they are used extensively in applications involving deep learning. Some well-known vendors are: IBM, Nvidia, Google, Intel etc.
6. Decision management
These are hardware that inserts logic and rules inside the artificial intelligence systems. It is used for the initial training and set up or for maintaining and tuning the ongoing process. It has utilization in several enterprise applications as it is a mature technology. The automated design making applications use this technology widely. Some well-known vendors are: UiPath, Informatica, Advanced Systems Concepts etc.
7. Deep learning platform
This is a special machine providing learning assistance such as artificial neural networks having some multiple abstraction layers. Now it is used specifically in recognition of patterns and application classification that is supported by a very big data sets. Some well-known vendors are: Sentient Technologies, Fluid AI, Saffron Technologies etc.
The process enables a natural interaction between machine and human being that includes touch and image recognition, body language recognition, and speech recognition. However, the possibilities are endless. The technology is currently used specifically in market research. Some well-known vendors are: Tahzoo, Affectiva, Sensory, 3VR etc.
9. Process automation through robots
The process is to automate human action through scripts and other processes to efficiently support business activities. At present, it is used only to execute processes or tasks that become too expensive to be handled by the human workforce. Some well-known vendors are: Blue Prism, Advanced Systems Concepts, and WorkFusion etc.
10. NLP and Text Analytics
NLP which is known as the natural language processing has used in several automated assistance, fraud detection, and other security concerns. This supports Analytics of text through facilitating sentence structure understanding. It assesses intent, sentiment, and meaning of a sentence buy statistical analysis and machine learning techniques. This is also used in unstructured data mining. Some well-known vendors are: Knime, Synapsify, Indico, Basis Technology and more.
The artificial intelligence market or AI Technologies is rapidly gaining importance. It received a lot of media attention and been hyped as well. According to surveys the market of artificial intelligence will reach to $47 billion in the year 2020. It already witnessed a 300% increase in investment from 2016 to 2017.
The future of artificial intelligence is no doubt quite attractive with many business benefits already achieved through the current models. But there are obstacles as well in adopting artificial intelligence as expressed by many organizations.