Artificial Intelligence (AI) can increase the productivity of your business by up to 40%. Sounds inspiring? Definitely, it is! However, implementing an AI solution can be pretty challenging. And the first decision you will have to make is to choose the way of building your AI solution. There are three available options. The first one is to build a solution in-house. Outsourcing is the second variant. The third option is to buy a ready to use AI solution. Each of these ways has its advantages, and you have to know all of them to make the right choice. To make your life easier, we have collected all the essential information about building AI solutions. Keep reading to learn more.
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Building In-house AI Solution: Pros and Cons
Let’s start with an in-house AI development method. It has both advantages and disadvantages, and knowing them will help you to understand if this option is for you or not.
So, here are the benefits
Better customization and flexibility
A lot of companies prefer the in-house method exactly because of customization. The thing is that their solution won’t have unnecessary features or features which will require complicated customization. And they won’t have to explain to other AI vendors what they need. They just build a solution according to their requirements and modify it whenever they want.
Intellectual property ownership
An AI solution can not only make your business more productive — it can also become an asset to your company. But it will be impossible in case your solution is developed by a different company and you haven’t agreed on the AI solution ownership. They will own intellectual property and, therefore, have a competitive advantage. But if you build a solution on your own or agree with AI partner, all the rights will belong to you. This benefit maybe not that important in case you need a pretty simple solution. However, if we are talking about something special and promising, it is better to take charge of building a solution. After it is developed, you will also be able to sell it to different companies and, in this way, increase the income of your firm.
You won’t depend on another company’s expertise. Such challenges as time difference and language barrier (which often accompany AI offshoring) also won’t disturb you. Building an in-house solution means being self-reliant and independent, and this can be an advantage in some cases.
However, an in-house method also has some disadvantages.
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Take a closer look at the disadvantages
Potential lack of expertise
If your team is experienced enough, that’s great. But certain AI solutions may require hiring new specialists. In turn, finding true experts can be complicated enough — you will have to look for new employees, to make sure that they know what to do, and so on.
Increased time commitment
This disadvantage is closely linked to the previous one. Looking for new employees is time-consuming. Training the existing workers is time-consuming as well. Gathering the data may also take a lot of time. In this way, you may devote to your project much more time than you expected.
Lack of delivery-oriented approach
If the project for which you need developers is not the core business of the company, such a project could be a huge burden on your IT resources. And an overload usually results in unsatisfied employees and non-optimal products.
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Advantages of Buying an AI Solution
The second option you can try is buying an AI solution. Sure, this way is not flexible at all, and the intellectual property won’t belong to you. Besides, it may be impossible to integrate available services with your application due to the compatibility issues. But on the other side, there are several advantages you have to consider.
Time and cost savings
You won’t have to look for experts, train your employees to build a solution, and do many other things — you will simply buy a ready package and start using it. In this way, you will spend much less time and money on implementing an AI solution. Actually, that’s the most cost-effective AI solutions building option.
Unlike specific and customized solutions, the packaged ones often boast of higher quality. If you choose an in-house option and build something very special, you may make a lot of mistakes. As a result, you will spend a lot of time testing and fixing your solution. But ready solutions have already been tested and fixed, if necessary. Just buy one, and that’s it.
Some companies selling ready AI solutions equip them with additional services either for free or for a discount. For instance, you buy a solution and get a discount on training for your employees, so they will learn how to use it.
Buying an AI solution is a great decision in case you need nothing specific. In turn, unique solutions require in-house development or outsourcing.
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Outsourcing as an Alternative to an In-house AI Solution Development
Outsourcing is a very popular way of software development nowadays. You simply use external AI partners, and they do everything for you. This may be a company or even an individual, depending on the difficulty of the project. But in any case you don’t rely on your own employees — you cooperate with an outside supplier.
Obviously, outsourcing has a couple of benefits that may convince you to choose exactly this way of building an AI solution.
Here are some benefits
An opportunity to work with real experts
True AI experts are usually hard to find. Moreover, as full-time employees, they ask for pretty high salaries. But you won’t have to deal with these challenges in case you choose outsourcing. An external provider already has all the essential professionals on board. They have enough experience to build your solution, and you won’t have to pay them as much as you would do when hiring them on your own. Their hourly or daily rates are sometimes much lower than the full-time salary of your employees.
Potential access to the demand-driven data
Companies that focus on developing AI solutions often have access to demand-driven data. This data can be extremely useful for your project while collecting it on your own can be virtually impossible. Cooperating with an outsourced provider is a way to solve this problem.
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An opportunity to avoid mistakes
An outsourced company can not only build an AI solution for you — but it can also help you to plan the project. Having experts on your side from the very beginning will save you from making diverse mistakes, especially if that’s your first project related to AI. And since making mistakes usually means spending extra time and funds, this advantage is really important in case you have a more or less limited budget.
Building AI solutions on your own could take much longer than outsource that to the AI consulting company. Lack of proper experience and delivery oriented approach results in time consumption and a lot of mistakes and lack of fast results. AI partners are putting all effort into the delivery in a cost-effective way and present results of MVP solution as much faster it is possible.
AI development outsourcing helps to save money. Compared to working with a local AI solution provider or hiring your own team of experts this is definitely a cheaper option. The costs of nearshoring could be a little bit higher than offshoring, but still gives you a great opportunity to save money and time. Here for you some examples of man-hour costs in different regions in the world: the USA $100-$150, Western Europe — $80-$100, Central and Eastern Europe — $30-$50, India — about $20.
We know, it may still be difficult to make a final choice. Each of the ways we described above has some benefits and drawbacks. However, you can start by checking if the solution you need is already available on the market. Then, move to estimate costs and delivery. How much money are you ready to spend on your project? When do you need it to be ready? Answering these questions can help you to decide which way of building an AI solution is more suitable for you. But if you still have any questions, don’t hesitate to ask them. We are always ready to talk about the know-how of AI companies with you.
 Jacquelyn Bulao. The Role of AI in Cybersecurity – What Does The Future Hold?. Feb 9, 2021. URL: https://techjury.net/blog/ai-cybersecurity/. Accessed Jun 18, 2019.