February 16, 2023
One of the most important dilemmas of companies is whether to keep their critical functions in-house or outsource them, especially taking into consideration that they are under increasing pressure to improve their return on assets and cut expenses.
AI has been a game-changer for many enterprises, no matter their size. It has helped them use data to obtain actionable insights and make faster and better decisions.
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By not implementing AI, you will not only miss out on a lot of opportunities to grow your business, but your revenue will also suffer losses.
You must decide whether you will build your AI solution or outsource it. In our article, you will find all the information you need to help you make up your mind. Keep on reading to find out more!
Visual artificial intelligence, or visual AI, is a discipline of computer science that allows machines to identify and understand visual data and images just like humans do. For instance, they are able to categorize objects within an image and understand if each object is a shoe, sweater, or dress, comparing them to images they’ve previously analyzed.
Visual AI has helped the development of many industries, such as security, healthcare, manufacturing, sports, automotive, and retail. It is safe to say that it’s the base for an improved end-to-end customer experience and faster learning and innovation.
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When thinking about buying or outsourcing, you should consider the following things:
To help you with your decision, we will look at the pros and cons between both options, and figure out which one suits you best.
We’re going to start off by discussing the advantages and disadvantages of building an in-house visual AI solution.
By building an in-house visual AI solution, you won’t depend on another company. You won’t have to adapt to any language barriers or time differences. Having an in-house AI solution means that you will be autonomous and self-sufficient.
An in-house AI solution means that you will build the model according to your requirements and you will be completely flexible in modifying it however you want. You will have a better understanding of your company’s systems, processes, and data, which can also help you to identify areas for improvement and make changes more efficiently.
Building an AI solution in-house means that you will have complete control over the solution and you can customize it to your company’s specific needs. You won’t have any unneeded features or features, which will reduce overhead costs.
Developing your visual AI solution means that you will own intellectual property, all the rights will belong to you and have an advantage over your competitors.
If you’re in need of a simple solution, this benefit might not be so important to you. But, if we’re talking about something really innovative and promising, you can develop a solution and then sell it to other companies, increasing your profit.
Unless you’re a leading global company, hiring experienced and talented professionals in a short time is very difficult. AI development requires a high level of knowledge and expertise in areas such as data science, machine learning, and software development. Despite recent growth, the pool of people working on machine learning is still quite small.
Moreover, there’s no guarantee that these people will stay with your business, which means you’ll constantly be going through the recruitment process. This will lead to a waste of valuable resources and a lot of delays in your work.
As we mentioned, looking for new employees and going through an onboarding process with them will take up a substantial amount of your time. The challenges in quality production, training, and reducing false positives may take even years to overcome.
Another thing that will be time-consuming is gathering the data and analyzing it. With an in-house AI solution, you will spend a lot more time on your project than you anticipated.
Your in-house team won’t work isolated from other departments, but instead, it will need their input. However, not every company has enough employees to spare so they can work from one department to another. Asking your employees to handle everything will increase their stress levels and decrease their productivity.
A lot of AI solutions need a huge amount of data that needs to be trained. For example, training software to identify objects in an image such as shoes or a dress could take hundreds of thousands of pictures.
It will be a massive undertaking to acquire that number of images and then process them. Something that will be an additional roadblock to gathering training data is restrictions and ownership of data.
By outsourcing your AI projects, you can overcome various challenges you would need to face if you deal with an in-house team.
One of the reasons why many AI projects fail is that the companies aren’t equipped and prepared properly in order to execute them. However, you can be sure that your vendor possesses the specialized skills to carry out your project.
When picking an option, you should also consider the training of AI models. How successful an AI solution is going to heavily depend on expert knowledge of taxonomies and accurate labeling.
Companies that build their AI solutions in-house have the advantage of having complete control over the process. However, they also might face challenges like a shortage of experts in the field.
On the other hand, outsourcing an AI project to a third-party vendor means that your company will get a high-quality service. These third-party vendors have the specialized knowledge it takes to carry out projects efficiently and effectively.
A lot of AI solutions are pre-built, meaning you will only need to supply data to your vendor, so they can analyze it according to the needs of your company. Additionally, AI vendors update and maintain their solutions by themselves, which will save you a lot of time.
If you’re building an AI solution in-house, you need to accept the fact that a significant amount of your time will go towards updates and maintenance to make sure that the technology remains relevant and continues to optimally perform.
But, if you buy an AI solution from a third-party vendor, the third-party vendor oftentimes includes support and maintenance services, so they are responsible for ensuring everything is up to date. This means your in-house IT team will save on resources and time they would otherwise spend on maintaining your AI software.
The amount you pay to the vendor will be a lot less than what you would spend on developing the AI model from scratch. You are hiring them not only for their expertise but for their resources and infrastructure as well.
Buying an AI solution from a third-party vendor means that you will be able to get up and running faster since the vendor will probably have a pre-built solution that they can customize according to your needs. Moreover, third-party vendors typically have teams in place that help with implementation and integration, which additionally speeds up the whole process.
Contrarily, building an AI solution in-house means that the time to market will be slower. The reason for this is that you will need to gather data, assemble a team, train models, and integrate your solutions with your existing systems. Depending on how complex your solution is, this process can take several months or even more.
When it comes to scalability, buying an AI solution from a third-party vendor can be more beneficial than building it in-house. Third-party vendors have a lot of knowledge and experience in scaling AI solutions for different businesses and can provide a scalable and robust solution that will meet the growing needs of your business.
On the other hand, if you build an AI solution in-house, you might encounter challenges to scaling it as your business grows.
One of the biggest concerns that businesses have is security. When you buy an AI solution from a third-party vendor, they are responsible for the security of the solution. This means that they are in charge of protecting you from data breaches, unauthorized access, and cyberattacks. Third-party vendors usually have security procedures and protocols in place, as well as experience when it comes to security.
As we mentioned, third-party vendors often have pre-built AI solutions that can be implemented a lot more quickly, which means that your company can start realizing the benefits of your AI investment faster. Moreover, a lot of third-party vendors have a proven track record of providing AI solutions that generate positive outcomes, which helps companies get a return on their investment more quickly.
Many companies that sell AI solutions offer free or discounted additional services. For instance, you buy a visual AI solution and you get free or discounted training for your employees on how to use the software.
As you can see, the decision of whether to build or buy an AI solution is not a simple one.
Buying an AI solution from a third-party vendor can be beneficial over building one in-house as it saves resources and time, offers technical support and expertise, and provides access to a wider range of solutions and technologies.
Third-party vendors also usually have a better infrastructure in place for security and data management, and they are often more cost-efficient than building a solution from scratch. Lastly, buying an AI solution from a third-party vendor can provide a faster time to market, and can free up your internal resources to focus on core business activities.
You should see the third-party vendor as an extension of your internal team, one that understands your key performance indicators, business objectives, and stakeholders. Together, you can develop an AI strategy that will align with your desired outcomes and goals. The result of this collaboration will be a value-generating and scalable solution that is tailored to the specific needs of your company.
We hope that our guide helps you in your thought process and that you’re one step closer to strengthening your competitive advantage by implementing AI.
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