During the pandemic, companies have taken big steps in adopting artificial intelligence (AI) and machine learning (ML) in their daily operations. According to a study, the majority of enterprises expect AI to significantly change their business model by 2023.
AI and ML are being developed and used to automate processes and solve business problems autonomously. These investments will continue to rise in the forthcoming years. Statistics showed that the global AI and ML market size is projected to reach US$299.64 billion by 2026.
AI and ML technologies are also transforming software development. They help developers build high-quality software by improving processes, from the code to the deployment. Many software development teams are now using AI and ML in their advanced digital products, demonstrating how popular and essential these technologies are.
The applications of AI and ML in software development are infinite. Here are some examples of AI/ML software development trends you should be aware of.
AI Improves Customer Experience
Every company during the pandemic is finding new ways to operate efficiently and to meet the need of social distancing, the changes of consumer behaviors and working arrangements. AI and ML are playing a key role in enabling that shift by providing tools to track and improve customer experience.
Using AI and analytics can help businesses keep up with the speed of innovation. One typical example for AI adoption is that a company providing Benefits Cards deployed a new chatbot to handle the increasing number of customer inquiries.
Often, customers called a contact center to check balances, update PINs and for other purposes. Developers created an AI-based chatbot to handle those simple and repetitive inquiries, reducing costs in call centers and increasing response rates.
AI and ML tools can help companies analyze large amounts of data more quickly and efficiently as well as provide timely and accurate answers. By learning the user’s transaction and other data collected from multiple sources, designers can deliver a better user experience for customers.
Machine Learning Gains Traction
Automated ML promises to speed up AI-powered software development even for users without advanced technical knowledge. This makes it easier for companies across different industries to adopt and experiment with the technology.
Automated ML are developed to help companies without data scientists or lack of computing resources to deploy ML and drive better business outcomes. By using automated ML, businesses can build ML models with high scale, efficiency, and productivity – in minutes with zero codes.
Automated ML can help save time by automating repetitive tasks in ML projects. It allows developers with limited ML expertise to create models that suit their business needs. The applications of automated ML include performing risk assessment in the insurance industry and improving the speed and accuracy of fraud detection in the financial services industry.
The Rise of Natural Language Processing
Natural language processing or NLP is a part of AI and ML. It allows computers to read, interpret and understand human language. Voice assistants, translators and chat box software are the most common applications of NLP.
The emergence of pre-trained models has brought NLP to a new era. NLP identifies structures or patterns in unstructured data to predict user’s behaviors. Most often, it is used in call centers to enable businesses to interpret spoken words, convert them into text and then analyze it.
In a contact center of Sky (a large European cable TV company), NLP is used to handle customer calls and convert them into text. Instead of spending time and effort monitoring and recording calls, businesses can leverage AI to automatically transcribe audio records and analyze sentiment in a dashboard.
With the help of NLP and AI, the company saves 80% on current operational costs to glean customer information and improve their satisfaction.
Preparing for AI-augmented Software Development
Traditional software development is still alive and well. But companies adopt AI and ML technologies to experience outstanding results. When being used in software development, those technologies can influence how developers create applications and how consumers use them. Software developers, therefore, need to keep up with technology trends to gain success and stay on the top in a competitive market.
