The rapid digital adoption of AI and ML technologies shows that they cater to the needs of businesses.
Digitalisation has been revolutionizing businesses for a long time now. There would hardly be a soul that is not incorporating digital technologies into its business. The technological realm is a real thing and now that more and more companies are mastering their use of applied science, they are delving deeper into a highly machine-driven world for increased efficiency, a greater competitive advantage and make their brand more enticing to the audience.
The era of simpler technologies and basic services are long gone and mobile app development companies simply cannot afford to be left behind in the race of forever evolving technologies.
Machine Learning (ML) and Artificial Intelligence (AI) are two such technologies that are two sides of the same coin. They are the most used comprehensive analytics strategies that are implemented in the data infrastructure to achieve business goals. For this and many other reasons, companies have already begun the implementation process profitably.
Since machines are capable of learning our behaviours and on the way to understand our emotions, from the day of inception and until now, Artificial Intelligence and Machine Learning technology have been evolving and improving. Some famous companies that are using AI and ML for Mobile App Development are:
Due to their ability to learn and making our everyday lives easier, AI-ML development is widely used in multiple spheres. Particular applications include Speech Recognition, Machine Vision and Expert Systems.
Today, almost every mobile app we use has been incorporated with Artificial Intelligence and Machine Learning that has made it necessary to have the knowledge of integrating machine learning and artificial intelligence in mobile apps.
Every business is coming up with intelligent applications, integrated with AI and ML-enabled features to reduce marketing costs, broaden their market coverage, enhance the customer experience and gain a competitive advantage.
The stats given below prove that ML and AI-powered mobile apps are a favourite among funded startups and businesses.
- Research by Allied Market states that the market for ML will reach $5,537 million in 2023 further proving its ever-increasing popularity.
- AI software will grow from $1.4 billion in 2016 to $59.8 billion by 2025.
- According to the 2019 CIO Survey by Gartner, the number of companies implementing AI technologies in some form has grown by 270% in the past years.
- According to Microsoft, 44% of organisations fear they’ll lose out to startups if they’re too slow to implement AI.
- About 76% of US companies have exceeded their sales target and European banks have increased product sales by 10% & lower churn rates because of ML.
- According to the statement by The Wall Street Journal, the advancements in AI and machine learning have the potential to increase global GDP by 14% from now until 2030.
So you see, to gain a leg up against your competitors, you should focus on improving your existing application by implementing AI and ML.
Let’s dive into details.
Artificial Intelligence Explained
Introduced by Marvin Minsky and John McCarthy, the term AI means a task performed by a machine or program that requires some intelligence to complete.
Though there are n-number of definitions of artificial intelligence (AI) over the past few decades, the most make-sense definition is by John McCarthy, “It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.”
This wide-ranging branch of computer science, that is building smart machines, is capable of carrying out the tasks that usually require human intelligence. AI is virtually creating a paradigm shift in every sector of the tech industry. Cortona, Google Allo, Chatbots, Google Assistant, Amazon Alexa and even Tony Stark’s Jarvis are some of the examples of AI in mobile apps.
There are innumerable reasons why AI is becoming people’s favourite in building the best artificial intelligence android apps. Some of its benefits to tech giants and local users include-
#1 – Contextual Marketing
Send out the selected marketing messages based on the user’s location, browsing activity or recently searched terms with contextual marketing. The contextual AI can detect products over OTT and show ads based on what users are currently watching or interested in.
One of the most popular apps that have integrated this feature is Netflix that tracks and collects its user’s data to give content recommendations accordingly. This way users get what they want without having to search for it.
#2 – Neural Networks
One of the interesting things about Artificial Intelligence is Machine Learning. Machine learning comes highly handy for technologies like automotive, aerospace, forecasting or voice synthesis, real estate valuation, credit counselling, mortgage, recognition of signals, images and autopilot.
Neural networks are capable of carrying out all these functions easily. Neural networks or popularly known as Machine learning are present everywhere and used by all of us in our day-to-day lives.
#3 – Accuracy & Perfection
Why should you integrate AI in mobile app development for startups? Because technology is the best way to get quick results that are highly accurate and precise. In fact, there is hardly or no room for mistakes in the sector where AI is implemented. AI is well utilised to solve errors related to data.
#4 – Offers Automated Reasoning
Automated reasoning is one of the significant AI technologies to integrate into mobile apps for improved productivity. Ridesharing apps like Uber or Lyft are the best proof to this.
These taxi booking apps make use of automated reasoning to see the closest route to drop the rider to its destination faster. The data is collected from all the drivers who have taken a similar route in the past by the means of automated reasoning.
#5 – Finishes off the Monotonous Tasks Quickly & Effectively
Nobody likes doing the same task repeatedly every day. It kills both efficiency and interest at a certain point and also wastes time and resources. But with AI, these monotonous tasks can be completed easily and quickly.
This way users get to invest their time into doing something innovative, constructive and solve real-time issues.
These are plenty of reasons that show why mobile app development companies are implementing the top AI trends to not be left behind in the race of continually evolving technologies.
Machine Learning Explained
Machine Learning (ML) is just one of the many applications of Artificial Intelligence (AI) that empowers software to learn, explore and predict the outputs automatically without any human interference.
Why is machine learning right for data analysis? This is because it can apply the knowledge acquired from a large database to be outstanding at facial and speech recognition, chatbots, object recognition, translation, etc. Machine learning is capable of recognizing patterns without any human intervention to predict the next step.
Over the years Machine learning is being used in multiple sectors and has now paved its way to serving mobile application development. Take a look at some of the applications of Machine Learning and know how it is helping to build intelligent new and better products/services/systems.
#1 – Facial/Image Recognition
Facial/Image recognition is one of the most common applications of Machine Learning. And the simplest example of such an application is our smartphones. Almost every smartphone today has an inbuilt feature of facial recognition which unlocks the device in an instant. It can be successfully applied for security purposes like identifying criminals, getting information about missing individuals, speeding up forensic investigations, etc.
#2 – Automatic Speech Recognition
It converts speech into digital text. ASR’s applications involve performing tasks that require human voice inputs and authenticating users based on their voice. The vocabulary and speech patterns are fed into the system beforehand to train the model.
Medical assistance, aviation, defence, IT, industrial robotics and home automation & security access control are some of the applications that integrate ASR system.
#3 – Marketing & Sales
“Business has only two functions – marketing and innovation.”
– Milan Kundera
Machine Learning has improved lead scoring algorithms by the means of different parameters including website visits, downloads, emails opened and clicks to score each lead. This helps businesses improve their dynamic pricing models via regression techniques to predict and determine the most successful outcome. On the other hand, chatbots are becoming more and more responsive and intelligent with the help of machine learning.
Also Read | Role of chatbots in enterprises
There is another application that can gauge customer response to either a specific product or a marketing initiative – Sentiment analysis. With ML, brands can identify their products in the form of images/videos online. These brands also make use of computer vision to measure the mentions that miss out on any relevant text.
#4 – Healthcare
Machine learning technologies are making a successful breakthrough in the diagnosis of diseases and ailments that are otherwise difficult to diagnose. Not only this but scientists are using machine learning to also predict epidemic outbreaks.
Radiotherapy or Radiation therapy is also improvised with Machine Learning. Chatbots are being applied actively by Healthcare service providers. These online programs can benefit patients in several ways such as scheduling appointments, getting answers to basic questions, getting simple virtual diagnostics and even facilitating the payment process.
In short, healthcare has become one of the best platforms to develop a mobile app with Machine Learning.
As you can see, ML can facilitate a smooth workflow of different sectors. That’s why the adoption of Machine learning technology is moving at a breathtaking pace. If you wish to offer advanced features to your end-users, implement Artificial Intelligence and Machine Learning in your existing app. Know-how in the following section.
How to Integrate Machine Learning & AI into your Mobile App?
By now you must have realized how important it has become to incorporate AI and ML into your application development to become more capable of meeting customer requirements and stay ahead in the ever-growing competitive markets.
Listed below are the primal ways through which you can leverage the power of Artificial Intelligence and Machine Learning to make your app more efficient, personal and intelligent.
#1 – Identification of the Key Areas
To invest in ai application development and its subset – Machine Learning – it is vital to understand what is possible through it. In order to understand the efficacy of AI and ML, the very first step is to identify the problems that you need to resolve. Different businesses encounter different problems. The most common ones being data-based insights, customer service, recommendation systems and security systems.
Take the help of consultants and discuss with key stakeholders – There exist many AI and ML mobile app development companies that can be contacted for their valuable services and support.
Browse through online resources and digital information to improve your knowledge of Artificial Intelligence and Machine Learning to get a clear idea. Follow up with case studies to understand how businesses have implemented intelligence algorithms into their products successfully.
#2 – Know the Areas Where AI & ML can Improve your App
Not that you’ve grasped the know-how on Artificial Intelligence and Machine learning, identify the challenges you wish to resolve with AI-ML.
Jot down a list of possibilities you can propose to your existing application by utilizing AI. To be sure of your ideas, run a market analysis and check whether a similar implementation has worked or not.
In short, here you should focus on identifying the problem and following the most suitable strategies.
#3 – Map out the Results & Consider the Budget
Now, in this step, roll out the plan for AI-ML integration. Decide how much you want to spend on AI-ML integration. If there are no financial constraints, you can go for a complete makeover all at once. However, it is suggested to get things done one by one to keep everything in order.
Moreover, since you have already identified the black spots or areas that need improvements and also kept your budget in check, you can easily prioritize what needs to be done first.
#4 – Ease of using & Practical Application
Now is the time to tick a few checks before moving on to the next step. A quick feasibility step could help you understand whether or not your implementation will benefit your business, improve user experience and increase engagement in the long run.
If the additions and changes are in no way enhancing the efficiency of your app, there is no point in going forward with the plan. If your internal team is unable to deliver the requirements and use ai as a service, hire or outsource reliable resources like that of Appventurez to develop, test and launch the product. The team should involve consultants and development/design experts who know how to carry out your plan in an effective, practical and achievable manner.
#5 – Data Integration & Security
When implementing Machine Learning, you must have a better data organization model for your app as there are chances that the old data may affect the ML deployment efficiency.
Therefore, once the additions and alterations are planned, shift your focus on databases. A well-organized and thorough data keeps up the app performance for the long term.
Also, security is one such critical issue that should be considered carefully. Build a robust and intrusion-proof plan to adhere your app to the security standards.
#6 – Time to Implement
Now that everything – planning and pre-deployment assessment – is aligned, development and deployment will be done in no time. This is the most crucial step where your team needs to be extra careful while deploying and testing the implementations before making the changes live.
#7 – Use Robust Supporting Technological Aids
Be meticulous when choosing the technologies and digital solutions to back your mobile application. Everything from security tools, optimization solutions, data storage aids to backup software needs to be strong and future-proof to ensure the consistency of your app.
Neglecting this can result in a drastic decline in the app’s performance.
These are the best, step-by-step methods to implement artificial intelligence and machine learning in an existing app to improve user experiences, make it more powerful and reduce churn rate.
This goes without saying that AI and ML combined are the future of mobile app development. To offer a personalized user experience, providing advanced services and multiplying your revenue by manifold, it becomes important for both new and existing apps to utilize these cutting-edge technologies.
Now that you know the benefits and ways to implement AI and machine learning into an existing app, it’s time to apply the practices to take your app up a notch.
If you are looking to develop an app that advances with time and technology, Appventurez can help. We are well-versed with the latest technology features and changing market needs to bring you quality results.
Co-Founder and AVP Technology at Appventurez Mobitech. A tech enthusiast who has broad expertise in delivering end to end software solutions. He is an expert technocrat ho has in-depth knowledge and is highly experienced in delivering solutions for Android, Xamarin, Ethereum Smart Contracts, ASP.net.
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