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5 most common AI implementation failures and how to avoid them | Technologies for business

5 most common AI implementation failures and how to avoid them | Technologies for business

5 most common AI implementation failures and how to avoid them | Technologies for business
Anastasia Romanova

Author:

Anastasia Romanova

Content Manager

Category: Business
5 min read

Do you know what is crucial for successful artificial intelligence technology implementation? There are a lot of important factors, which can determine your success or failure in AI integration. Do you have any clue what it can be? Read along to find out!

This article is one of Technologies for Business series. This block will tell you everything and more about innovative technologies, such as machine learning, AI, and blockchain. This series will cast some light on these technologies’ benefits and will show you how exactly they can make your business more efficient.

This article in particular is about AI implementation and the most common failures in this process. Here you’ll read about the typical mistakes and how to make sure that you won’t make them. You’ll also see some of the epic failures from world-known companies and learn how to become a better innovator.

 

What is an AI and why there are so many failures in its implementation

Let’s figure this out. First of all, AI is an innovative technology that determines the intellectual systems’ ability to perform actions and maintain tasks that are usually done by humans. These systems usually have functions and features that make them act more like real people - sometimes they create works of art, like a neural net from Google, and sometimes they chat so lively you won’t be able to tell the difference. AI is a whole new world of possibilities, where your regular boring every-day work is done by an incredibly smart computer.

And it’s good to know, that this new world is in the foreseeable future.

For a better understanding of this technology, let’s focus more on its practical use. We can look at AI performance in the well-known Instagram app. It uses machine learning algorithms to see which account you’ve interacted with earlier. How does it happen? In reality, pretty simple.

The “word embedded” ML method analyzes which words are usually used next to each other (for example, “peanut” and “butter”). A similar method is used to analyze whether 2 or more profiles in social media are related.

But if it all so simple, then why everyone says that AI is incredibly complex and so many entrepreneurs experience failure when implementing it? At first, because the example above is one of the simplest and not every AI technology works in the similar way. This technology is still innovative and new to the world. It’s evolving and changing, its self-learning mechanisms are the reason for artificial intelligence failure or mistakes (and success as well) as much as the human brain. But one of the most complicated things about artificial intelligence is successful implementation of it into the business.

The biggest risks for a businessman who works with an AI and integrating it into the software are as following:

  • most of the business processes are now automated but artificial intelligence can still experience failure;
  • a lot of AI tools are not as good and profitable as they seem;
  • artificial intelligence needs constant training and testing in order to prevent failure, and both of these processes aren’t cheap.

Probably this is why companies aren’t so enthusiastic about implementing an AI solution. There are, of course, more reasons and on the graph below you can see which are those.

ai-companies-implementing-artificial-intelligence

The most visible reason here is that companies don’t recognize the need for AI, and fear of failure is also an issue. We’re advising you, if you haven’t made your mind yet, to think about all the benefits this technology can give your business. There are a lot of advanced ready-to-use tools for business existing on the market. Such solutions allow you to automate business processes and routine work, hence, minimize the possibility of manual mistakes.

  • Microsoft Bing Speech API - a tool for converting audio to text for intuitive interaction. It also is capable of making the application sound natural and translating the audio itself.
  • Dragon Speech Recognition Software - gives your employees and customers the power of dictating text instead of typing it, which saves time and improves reporting.
  • Amazon Recognition - can identify objects or actions (for example, buses or swimming). Helps you find your company’s logo or items in the stores, the technology can understand the text contextor identify emotions on someone’s face;
  • IBM Watson Visual Recognition - uses deep learning algorithms for images analysis aimed to define the environment, faces, items and other objects;
  • Google Cloud Auto ML - machine learning algorithms from Google for deriving insights from images, content discovery, also revealing the meaning of the text, and dynamic translations.

We’re using these and other AI tools for successful technology integration into our clients’ software. Working with a reliable IT-partner may help you turn these tools into your competitive advantage.

It is complicated to work with innovative technology, especially with self-learning systems. So, we advise you to get professional aid to prevent failure. Why do we advise on this? Read next to see the typical failures in the AI implementation process.

 

Typical AI implementation failures

There are as many mistakes that may lead your project to failure, as many wins that can make your software successful. Here we’ll talk only about a few of them, but these few are the most critical ones. If you nullify them it’s almost likely that AI solution in your business will work as good as possible.

 

.1 Incorrect AI implementation strategy (or its absence)

You need to have an AI implementation strategy to define your priorities, mission, milestones, and even further plans on artificial intelligence. Entrepreneurs often don’t bother themselves with an AI strategy or create it not quite right. You can miss something drastically important and your strategy won’t be detailed enough.

The AI strategy is often influenced by time and money, and this forces some businesses to look for fast and less costly solutions. It causes implementation failures at the very beginning when you’re chasing something simpler and cheaper, forgetting what your business actually needs in the long run. You need to understand clearly which processes AI needs to automate and which business problems and goals it has to solve.

Incorrect AI strategy can cause the efficiency drop and let all your costs go to waste with the technology failure. If you want artificial intelligence to work well, it is necessary to consider key factors that are crucial for your business’ success. For example, choose the process you need to improve and define the desired result of AI implementation. Then compare the facts to the ideal numbers and you’ll see if the technology has done its work. It is important to pay attention to the data since this error can offset all the efforts invested in the implementation of the product.

But how to avoid this common failure? We advise you to find educational materials and learn all you can about artificial intelligence. A better understanding of this technology will let you build a more qualitative AI strategy. Also, you can have a consultation with specialists if you don’t have time to deal with it by yourself. A reliable IT-partner can create an implementation strategy for you.

 

.2 You don’t know what AI is supposed to do for you

People often mistake artificial intelligence workflow with business process automation. Frankly speaking, automatization is a wider term, and AI in it is just one of the possible tools. If you think your business is in need of process automation it doesn’t mean that AI is the only solution. You can automate differently and without the expensive innovative technology. But if you know that what you need is reducing manual mistakes or making some things done without human interference - AI is what you’ve been looking for. For example, if you need to automate emailing - this technology might not be what you have to use. But if your goal is to sort emails by keywords or phrases - yes, you have a need for artificial intelligence.

To avoid this failure you need to know which business problems have to be solved, you need to research the market, look at the existing products, and figure out whether AI is a good solution for you. Will it give you a competitive advantage? Will it make your business more efficient? Will it be helpful, giving your current situation on the market? Does your business need innovations at all?

Some development companies, including MassMedia Group, have a business-oriented approach to software creation. Working with such companies will give you a business analysis and technical consultation before AI implementation, which solves your problems once and for all.

Some people won’t even notice how quickly new technologies disrupt the market. PEGA questionnaire shows that only 33% think that they are using AI-based applications. However, according to Statista, 47% of mobile apps have AI implemented since 2018.

 

.3 One solution for everything

AI is a costly innovative technology, but this doesn’t mean that it has to do everything. Any tech has its limits and artificial intelligence is no different. It can make mistakes despite how good technology is, so the best way is to use it for small monotonous tasks. Simple tasks are easy for AI and can save a lot in the long run, so it is the way to reduce mistakes from a sore human eye and not yet perfect self-learning machine.

For example, let’s take those tools we mentioned above. Most of them focus on one single task like converting audio into the text or identify what’s on the pictures. Hence, you no longer need staff for this dull job, and you won’t experience failure in such simple processes. But what you will have is increased business efficiency and manual work automated.

 

.4 Your employees find it complicated to work with innovative technologies

Complex technology requires at least a basic understanding of its work principals. If you have artificial intelligence integrated into software that people have to work with (for example, algorithms of content moderation), and your employees don’t know how to work with it - it’ll definitely leave its mark on possibility of failure.

AI was created to perform its tasks without human interference but if you implement it, you need to understand that it’ll be tightly connected to the manual work. You also need to build the right corporate culture and maintain a positive attitude towards innovative technologies inside the company. If your staff is skeptical about AI it’ll definitely affect their performance and slow down the implementation itself leading you to the failure. Perhaps, you even need to think about hiring a Chief Innovative Office?

The problem of staff training is an important factor for AI efficiency and for avoiding the implementation failures. This is why development companies may offer you a service aimed to teach your employees how to use new software. Aside from this, you can also conduct educational seminar, trainings, mentor programs, and let your people know about the growth strategy and what you’re going to pursue. If your staff knows what you do, why you do it and what will you get from it they might be a little less skeptical of anything new.

 

.5 Too high expectations

Advertisements can be a little too good sometimes. And, you know, if something is too good to be true it probably isn’t true. After nice and beautiful promos many entrepreneurs think that AI will take everything on itself right after implementation.

And, oh, how bad they are mistaken! It’s a one way ticket to failure, and it’s probably the most avoidable one.

Yes, artificial intelligence has remarkable numbers indeed, when it comes to efficiency. It can improve your business workflow, raise profits up to 40% and cut costs. For example, world-famous streaming service Netflix cut its costs by $1 billion thanks to machine learning. But the technology itself is based on intelligence, it was created to repeat human track of mind and sometimes it does it a bit too good. Failure can occur in its performance, and even though it’ll be less drastic than humans’, it’ll be a failure. So it is crucial for technology effectiveness to maintain its training and testing. It is how AI works, and if you strive for good results you need to work on its algorithms, analyze its performance, and make changes based on it.

Artificial intelligence is good, but it isn’t a miracle. So if you don’t want to have an epic failure - make sure you do everything possible for avoiding the most common mistakes. To keep you on your toes, let’s talk about famous failures right now.

 

AI failures examples from world-famous companies

The first one is TayTweets.

ai-failures-bender-robot

It’s your average evil robot that wants to kill all humans and needs you to bite something metal and shiny.

TayTweets was a promising chatbot from Microsoft until something went wrong with her. A lot of people were interested in chatting with Tay on Twitter and it didn’t do the poor thing any good.

The chatbot was designed to learn how to talk like “real people”, to make the conversations with her more lively. But in 24 hours people turned her from all loving peaceful robot-being into something even nastier than Grinch.

These tweets show how Tay had failed in such a short time.

tay-teets-tweets-ai-failure-2

That’s one self-learning AI failure that happens if it’s evolution isn’t done under a strict eye. So as you can see failures can occur even within the most perfect innovative technology operation.

The second is Amazon Facial Recognition, which sometimes can experience failure in dark-skinned faces identification. We included it in the list of good AI tools, though, and we did it for a reason. When it comes to emotions, objects, and actions - Amazon Recognition works just fine, but the tool isn’t so great in identifying someone’s face features. So if you’re going to use it in your AI-powered application, make sure you run all the necessary tests and had your system perfectly trained.

The last example is the iPhone Face ID, which was used in iPhone X. And it was not secure enough. It was proved by Bkav when they printed a 3D mask and glued 2D paper eyes to it. The cost of this con was approximately $200. And here’s the video of how they did it:

Hence, the iPhone X failed security system was based on custom AI.

It’s a proof that artificial intelligence is not flawless yet. It still needs to be improved, trained, and tested, but in the end they will do an incredible job.

Those failures are not imperfections of the technology itself. Artificial intelligence can work as good as you need it, but for this, you need to rely on IT-partner who’ll train the AI, create an implementation strategy, and help you define whether you really need artificial intelligence and for what. There are many examples of the successful AI technologies use, and both small companies and giant corporations work with them. Innovative technology can give you a competitive advantage and level up your business, but you need to take AI implementation seriously, just like any other tech.

But before we reach the end of this article - one last thing for you to smile about. Watch this Boston Dynamics robot faint because of stage fright and wonder if this failure could be possible to avoid with more testing?...

Artificial Intelligence has truly become a big part of our lives, and a big part of the business workflow for a lot of companies around the world. And to summarize everything, we need to highlight the importance of the correct AI strategy and reliable IT-partner, which can lead your business to the new level of efficiency and profitability.

MassMedia Group as an IT-partner can be your best solution due to our services like maintenance, support,

lifetime code warranty, multilevel testing, and the fact that we use AI tools that are trusted worldwide. We’d be glad to help you implement AI into the software with our both business and technical approaches (which means, along with all technical aspects of the development, we offer a thorough business analysis). 

Maybe one day you’ll wake up, look in the mirror, and seean innovator who had never failed.

Frequently Asked Questions

What is AI?

Answer:

AI is an innovative technology that determines the intellectual systems’ ability to perform actions and maintain tasks that are usually done by humans.

Why implement AI?

Answer:

If you need to reduce manual mistakes or get things done without human interference - AI is what you’ve been looking for.

What are the most common AI failures?

Answer:

Too high expectations about AI abilities, using AI for everything in the business workflow, the misconception of the technology itself, incorrect AI strategy, and the lack of staff training. For more detail - read the article!

How to avoid any failure in AI implementation?

Answer:

Get professional aid from an IT-partner, build the right AI strategy, and train your staff. These are the pillars of success when working with any innovative technology.

What are the biggest risks in AI implementation?

Answer:

Artificial intelligence can make mistakes; a lot of AI tools are not as good and profitable as they seem; artificial intelligence needs constant training and testing.