7 Challenges with AI in Mobile App Development

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AI in Mobile App Development

Never has technology advanced at such an exponential rate and artificial intelligence (AI) is now at the very forefront of this ever-evolving industry.

Mobile App Development Meets Artificial Intelligence (AI)

Artificial Intelligence is still for many people the stuff of sci-fi movies and something that will happen in the future, unaware of the fact that various applications have already been influencing different areas of our everyday lives through areas such as IoT and Machine Learning for some time.

Adoption is widespread and has been taken up by the likes of Microsoft, Facebook, Google, and Amazon who are in an all-out development race the likes of which can be likened to the early days of the space race of the last century.

AI has a different classification from strong to weak with development companies. Although many DIY Apps are now starting to hit the market, high-end Mobile App development is complex and can be costly.

Strong AI is in the realm of programming that allows the device to mimic a humans thoughts and activities.

Other classifications are ‘restricted’ and ‘general’ AI. The specifics of this are down to the individual companies programming capacity and therefore comes with certain advantages and disadvantages, some of which I am going to list for you below for you and your team to consider when moving into the AI realm of App development.

Pros of AI

  1. Tedious Tasks – Completed Efficiently

The ability for AI to be able to handle mundane an repetitive tasks that are time-consuming and cost a lot of working hours can be vital to a business to be able to focus their workforces time to be better spent elsewhere.

Integrating AI to complete these tasks can lead to significant benefits for companies for increases in productivity and profitability.

  1. Everyday Applications

AI is already integrated into our day to day lives. In the travel and tourism industry, AI applications can be utilised to detect areas of interest effortlessly by employing Augmented Reality (AR). AR’s computer-generated real-world view for the client enhances the surroundings and helps to cut out the human aspect as the visual aids in the selling of the product.

Apps for ride-sharing have to calculate time, traffic conditions and process other real-time relevant data and will feature in self-driving cars requiring the latest AI innovations.

Social media platforms are now moving into the realm of AI detecting people’s features incorporating biometrics type interface features.  Already in place are predictive writing and spelling correction, And chatbot automated replies are everyday life applications in use.

  1. Fewer errors

Of course, the human element comes with mistakes when fatigue and repetitive factors are considered. AI machines are becoming irreplaceable in areas that require high levels of accuracy over a long period.

Space exploration, mining, and deep-sea oil rig repairs are three areas that this kind of technology has started to be used in as mistakes are incredibly costly with human lives, technological advancement and company’s bottom line all on the line!

  1. Compelling use cases for smart robots

AI has tremendous significance in the medical field. Smart robots are now being used in the area of diagnosis and diseases.

They can instantly inform doctors of the potential side effects of medications for a particular diagnosis. Additionally, this can be used in artificial surgery simulators for training purposes and soon will look to be integrated into the operating theatre itself.

Cons of AI

  1. Delivering a Lack of Human Creativity

AI is only able to follow algorithms, so with mobile Apps requiring to differentiate themselves with differing features, this can hit a wall. Human creativity and imagination can just be programmed to be reactional.

So although AI enables devices are helpful in mobile app development, it will be generic and void of creativity. Maybe in the near future, the breakthrough will come where AI can create code on-the-go in real-time and come up with human-like solutions, but we are not there yet.

  1. Specialist Implementation leads to cost

AI implementation in mobile app development is not an easy task.

Specialist programmers are required as not all mobile app developers are familiar with the latest code involved with AI solutions.  This comes with budget increases as it is a specialised skill-set and more development is needed than a standard app, so if a budget is tight, then a company should be looking more towards ‘ restricted’ AI.

  1. Continual Software Updates

AI system software needs to be continuously updated also, as it will become out-of-date quickly so a team must be dedicated to enhancing and releasing new App updates and features on a regular basis. AI collects and stores a massive amount of data but has to be directed in how to use that data.  It is unable to be responsive to a changing environment and make distinctions like a human.


With varying levels of AI available to be implemented on mobile devices, it’s a case of what portion of the market you are targeting and what price range you are looking to market your device in.  Factoring in your competitors and weighing up expectations of the consumer are part of the decision-making process of what area of the market is your niche where your devices will sell, given the amount of technology justifies the price bracket.

With Google and the consumer basing their decisions more prevalently on the UX and UI experience, your device must provide engagement to the consumer and be easy to use.  AI is becoming a more important factor; your job is to gauge how much and what level of AI you need right now to gain and keep your customer base loyal to your devices.

Author bio:

James Row is a passionate blogger and professional software developer who is associated with Web Designs who are heavily involved in mobile app development Melbourne. He has a love for informative writing and looks to keep you up to date with the latest information about the industry.


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