AI Development Team

Artificial intelligence (AI) is now a part of all industries, from e-commerce to health care and finance. Businesses failing to incorporate this type of technology will likely find themselves surpassed by their competitors and completely left behind.

Different companies take advantage of different types of AI-driven technologies, including natural language processing, predictive analysis, machine learning, and automation. All of these require a dedicated set of professionals with specific skills and knowledge.

An AI development team comprises a wide variety of roles that remain involved in every step of AI development, from conception to development and implementation. Such a team requires experts with different backgrounds, skills, and ideas; its success doesn’t depend only on a group of data scientists anymore.

AI Development Team 8

What Does an AI Team Do?

An AI team is responsible for designing and creating AI-based models and systems and then applying them to solve business problems. They need to work closely with IT teams, vendors, and business leaders to fully understand the needs of the company. A few tasks assigned to an AI team might include:

  • Identifying AI needs in the business – AI experts need to convey to business executives what AI can do for the company and which models and strategies would work best to optimize the business.
  • Creating proposals – This is where the AI team devises pilots or prototypes to test their new ideas. These innovative ideas should include a clear pipeline that leads to production and deployment. Usually, it’s best for teams to begin with smaller tasks and less ambitious projects.
  • Defining the required infrastructure – AI experts need to define the different platforms and tools they need to work efficiently. These might include data management platforms, analytics tools, and others.
  • Developing and deploying AI tech – Once the experts have everything they need, they begin designing and creating the AI-based tech the business requires. Upon completion, it’s also their responsibility to deploy, test, and maintain it to ensure everything is working properly.
  • Sharing success stories – Spreading early success stories is key to keeping executives and business leaders interested in embracing more AI activity. This helps guarantee better and continuous funding for the AI sector of a company.

The Characteristics of a Good AI Team

The success of an AI department depends on building a good AI team. To recognize if the team is working well and every member is right for their role, there are a few things that leaders should look for:

  • Well-defined and structured processes
  • A range of skills and experience that covers the projects’ needs
  • Capability to work well individually and as a team
  • Great communication
  • Quick problem-solving abilities

The Importance of Creating a Diverse AI Team

Creating a diverse AI team is imperative for the company’s projects to thrive. Diversity in the team is critical when it comes to solving different problems, driving creative thinking, and avoiding artificial intelligence bias.

Having team members with different backgrounds and skills not only determines how well they’ll do with AI-related tasks but also impacts how they collaborate with users and leaders, communicate changes, and work across functional groups.

AI Team Structure

The structure of an AI team depends on the projects at hand and the company’s needs. However, there are a few fundamental roles that are necessary for a successful artificial intelligence team.

Data Scientist

Data scientists gather data from various sources and analyze it to better understand how the business is performing and determine which AI solutions it might need. Typical responsibilities of this role include:

  • Analyzing data and communicating findings across multiple departments such as digital marketing, sales, product management, and software engineering
  • Developing data visualization strategies and creating reports
  • Identifying opportunities where the company can leverage AI to get business benefits
  • Advising the internal development team regarding existing and future products

Data scientists come from many different backgrounds including statistics, engineering, computer science, and mathematics. While their role requires some programming ability, their skills are a bit less technical and they’re usually the bridge between the technology and business departments.

Data Engineer

Data engineers work closely with AI software engineers and data scientists and are responsible for the internal intricacies needed for an AI project to work. They take ideas, models, and algorithms from data scientists and turn them into code that runs smoothly on servers and across all users’ devices.

The main focus of a data engineer is evaluating, developing, and testing big data solutions for analytics projects. They might also work together with data scientists to transform sets of data into actionable business insights.

AI Software Engineer

AI software engineers integrate the models designed and curated by data scientists and data engineers into functioning production systems. They ensure that those models see a successful transformation into the designated, designed applications.

An AI software engineer creates front-end systems and builds APIs and user interfaces. They also make sure that the final product is exactly what the product manager, business leaders, and stakeholders were looking for.

User Experience Designer

User experience (UX) designers are responsible for adjusting the front-end parts of a product to make them highly responsive, offering the best user experience possible. They usually design and deploy user stories, journeys, and product mock-ups optimized for all devices.

UX designers also make sure that the AI used in the product or service is working exactly as it should. For instance, they would ensure that the AI in a specific product is reflecting everything that it has learned by examining user behavior.

Chief AI Officer

The chief AI officer, also known as the chief research officer, has an information-driven role inside the company. Their main function is to keep the company informed about the latest developments in the field.

They understand how novel advances in AI and machine learning could be helpful in solving different problems within the company. Communication skills are a must for chief AI officers, as they must translate complex technical topics into nontechnical language.

This expert might also help inexperienced team members identify potential AI opportunities in the company. The chief AI officer helps the team understand how artificial intelligence serves as a resource to solve a problem.

Other Roles

There are a few other AI team positions that most teams will need, especially as an AI department grows. Some of them include:

  • AI ethicists – These employees understand how artificial intelligence programs impact people and whether or not under-represented groups receive fair treatment, for example.
  • Marketing and sales leaders – This is crucial for companies that sell AI-based products or services. 
  • Data analytics lead – This team member manages data scientists and data engineers in companies with bigger AI teams.
  • AI product manager – They take on a similar role to the standard product manager but require significantly more experience and knowledge in the AI field.

AI Infrastructure

Before setting up an AI development team, companies should make sure that these experts have everything they need to work efficiently. From ensuring enough data to providing the right tools, leaders should work closely with the AI team members to establish the right infrastructure.

A few of the core components of AI infrastructure include:

  • Ingestion – Ingestion is the process of gathering information from various sources and transporting it to a site that then stores it for further analysis. Data ingestion tools have the ability to collect data in batches or in real time.
  • Data storage – Once collected, the ingestion tools store the data in massive databases. From here, team members analyze the data and use it to create new models, experiment with simulations, or help with decision-making.
  • Networking – Storage and processing are usually done in a cloud system. This is why AI teams require fast networking that supports massive data movement.
  • Analytics – Data scientists, data engineers, and any other team members who work with analytics need specific tools for their jobs.
  • Automation pipelines – These pipelines guide AI software developers through a path that goes through creating, testing, and deploying their code.

How to Set Up an AI Team in Your Company

To successfully establish a custom AI solution in a company, leaders need to set up a good AI team. A few steps that businesses should take to implement an AI development team include:

  1. Planning – Leaders need to determine budgets, allocate resources, define goals, establish practices, and define company culture first and foremost. This requires proper planning and evaluation.
  2. Understanding the business values – The implemented AI projects will need to keep up with the business values in order to deliver any tangible return on investment (ROI).
  3. Discovering what AI can do for the business – Here is where leaders must ask themselves which of their business problems to address with AI projects and which forms of AI to use for those solutions. There are many different subjects within AI to choose from, including machine learning, deep learning, image recognition, automation, and many more.
  4. Outlining the skills required for the project – Depending on the type of AI applications a company wants to develop, they need to outline the skills, knowledge, and experience needed for the projects. This is where leaders figure out which types of experts they need in their AI team.
  5. Choosing a hiring model – Once the company knows what it needs, all that’s left to do is decide which hiring model is more beneficial to the business. Here, recruiters need to choose between building an in-house AI team or working with an outsourcing provider.

The Benefits of Working With an Outsourcing Provider to Build an AI Development Team

Working with an outsourcing provider to build an AI development team has several benefits in comparison with building an in-house team. Outsourcing an AI team is much more affordable than hiring locally because companies can choose talent from countries with lower average salaries. 

Creating an in-house AI team (and perhaps a dedicated department) is also much more time-consuming than working with an outsourcing vendor. Extensive recruitment processes can take up a lot of time, especially when building an AI team, since candidates need to prove their skills.

In the event that the company isn’t able to find team members with the necessary skills and experience, they’ll need to spend even more time and money training them.

Outsourcing an AI team extinguishes these issues. Providers have access to a pool of talent and are able to pick and choose the right team members with the necessary profile for the project.

Another great benefit of working with an outsourced AI development team is that the company doesn’t have to invest in infrastructure, like costly office space or equipment. The team members already have everything they need to work on the project remotely.

Outsourced AI development teams are typically so resourceful and experienced that they can easily help a business scale their AI-driven projects up or down, according to the needs at any given time.

How to Hire the Best AI Developers With BairesDev

Hiring and maintaining an in-house AI team is sometimes extremely expensive and time-consuming, especially if the current team doesn’t already have the necessary skills. This is why many companies resort to outsourcing their AI teams.

The first step to hiring the best artificial intelligence developers with an outsourcing provider is to do some market research. Companies should try finding which countries have the talent they’re looking for and where they can find the most affordable and capable experts. Many companies choose to work with BairesDev based on expertise and quality of work.

Once that’s settled, it’s then time to look at different outsourcing providers from that country. It’s always a good idea to have a few options in mind. Leaders should be comparing portfolios and reviews to determine which would be the right provider to work with.

At this point, the company should get in touch with the provider and spend some time achieving a mutual understanding. The company leaders should question the outsourcing provider about communication methods, reporting practices, and management options to figure out if their values are similar.

It’s also important to take time zone differences into consideration. The hiring company should try to understand how the outsourced team works when time zones don’t match and how they report and solve problems in these situations.

At this point, the outsourcing provider understands the company values, knows the type of skills and experience required for the project, and is able to put together a dedicated AI development team. The final step in the process is choosing and establishing the right type of contract.

Common contracts used in AI development outsourcing include fixed price, time and material, and dedicated team contracts. The first type typically applies more to small to medium projects with a predictable development process.

Time and material contracts are useful in situations where the company wants to improve a particular solution with the help of AI. Dedicated team contracts are usually the most expensive but they also benefit the company the most, in the long run.

Related Pages

AI Development Team 9

AI Development Services

Artificial intelligence (AI) is already becoming progressively more common across multiple industries and their verticals.

Start Building Your AI Development Team With BairesDev Today!

Building an effective AI team starts by understanding the company’s needs and which roles would help it meet the specific goals of the organization. This requires planning, setting goals, and keeping up to date with AI research to decipher which methodologies would work best in solving the company’s problems.

AI development teams can have a wide variety of experts. Data scientists, data engineers, AI software engineers, and chief AI officers are only a few of the roles necessary to establish a solid AI team structure.

These teams should be as diverse as possible. The more diversity in an AI development team, the easier it is to overcome AI bias, drive creative thinking, and solve problems using different strategies.

It’s also imperative that the company provides the right infrastructure so that the AI team can work as effectively as possible. Different experts will require different tools, so leaders should work closely with them to understand what they need to succeed.

Once the company knows exactly the type of talent they need for its AI-driven projects, it must choose the right hiring model. Recruiters can decide between creating an in-house AI development team or working with an outsourcing provider.

To hire the best AI developers with an outsourcing provider business leaders should follow a few steps. First, they must conduct some market research to figure out which country has the most talented and affordable AI experts. 

Then, they should compare different outsourcing providers and choose the one that offers the best solutions while still maintaining values that are similar to the ones the company holds. Once both parties achieve a mutual understanding, all that’s left to do is to create and sign a contract.

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