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Artificial intelligence is revolutionizing industries and businesses generating demand for AI engineers and artificial intelligence solution providers. From virtual personal assistants, face recognition and grammar checkers to smart home devices, smart cars, and robotic servants – AI-based solutions are taking over our personal and business lives.
According to Statista, artificial intelligence market will only continue to expand and generate bigger revenues in the future.
Source: Statista
Meanwhile, businesses often face difficulties in implementing AI solutions because developing this expertise in-house is cost- and time-consuming. Also, there is great demand for software developers experienced in artificial intelligence and thus the competition for talent is extremely strong. Therefore, many companies start cooperation with AI development vendors and hire extended teams of engineers.
Indeed, outsourcing AI development gives a plethora of advantages. First of all, you get access to a larger pool of AI and machine learning experts. Secondly, offshore vendors usually offer a better price-quality ratio. Also, this gives businesses more flexibility and reduces time to market.
Since there are many software development vendors who claim to have vast AI engineering expertise, we have tried to establish some criteria for choosing the most competent provider and factors that are going to determine the success of the project.
What to consider when choosing AI solution provider
A company needs to consider a number of factors when choosing an artificial intelligence solution provider. Here are some of them:
Proven AI engineering experience
To choose a competent AI development vendor, you will have to sift through many companies which claim to have vast AI expertise. As this is a relatively new but very hot field, many companies lack practical experience in AI engineering but still want to jump on the bandwagon of AI. Therefore, it’s important to do thorough research.
Source: Adweek.com
First of all, you should study the portfolio and case studies of the company. You need to find out what exactly a software development vendor worked on and which artificial intelligence solutions they delivered. Check out whether a provider has any experience in different kinds of machine learning (supervised, unsupervised, and reinforcement), data structures and algorithms, computer vision, NLP, etc.
Moreover, learn about the industries the company vendor works in. Every industry has its specifics so it’s preferable that the software development provider has relevant experience in your industry.
Expertise in AI technologies
Artificial intelligence encompasses a vast variety of technologies and development practices. When choosing an AI solution provider, make sure the engineers have expertise in different programming languages and frameworks. They include Python, R (two most common languages for writing machine learning algorithms), C (good for computer vision), Scala (has great scalability), Hadoop, Lisp, TensorFlow, Caffe, Torch, etc.
When it comes to a development team, make sure there are professional data scientists and data engineers. Data scientists are responsible for cleaning and organizing data, and deploying algorithms. Data engineers develop architectures for the project and ensure the system scalability. Also, if you need to build an image recognition or speech recognition model, you should have computer vision engineers and speech recognition engineers on your team.
Capacities to scale a team
It is essential to choose the provider with enough resources and capabilities to manage your requirements. This factor is going to affect not only your primary needs but also the potential growth of your company. When you scale up, you would also need more engineers. Therefore, consider the vendor’s ability to scale your team in the future, its employer image, retention rate, and access to the talent pool.
Choose the right cooperation model
Another factor that plays an important role is the cooperation model your potential vendor may offer. The cost common ones are Fixed Price, Tima and Material, and Team Augmentation. With the fixed price model, all your requirements such as budget, deadlines, the scope of work, and others have to pre-defined from the start. However, when it comes to AI projects, they always require a lot of R&D, so it is hard to determine everything at the initial stage.
Therefore, you need a team fully focused on your project with high level of flexibility and scalability. In this case, team augmentation, or dedicated development team would be the best choice. Most companies prefer it when planning long-term projects with evolving requirements.
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Building an in-house AI development team is not always feasible. AI engineering resources are scarce and expensive. Moreover, setting up and managing R&D is going to take a lot of time a company could spend on developing its core expertise. And although finding a qualified AI solution provider is not easy, outsourcing offers tangible benefits for businesses.
So when choosing an AI development vendor, consider its ability to allocate the necessary resources, its experience in delivering AI solutions, knowledge of your domain, technological expertise as well as its capabilities to satisfy your business requirements.
