How to Lead Artificial Intelligence Teams Within Organizations

Artificial Intelligence

Dealing with technical teams is not as straightforward as overseeing non-technical teams, because technical teams operate in a discrete manner. “Own it” is the catchphrase used by technical teams for optimum work efficiency. To effectively manage a technical team you must take full responsibility for the product and be ready to manage communication among team members.

Being a technical leader can be a rewarding experience if you know how to deal with a bunch of people who have limited people skills. Following are some of the major challenges faced by executives managing a tech team:

●  Getting along with the intense work pressure- The technical team is at a higher risk of burnout due to workloads than any other team. Hence, it becomes a challenge for a leader to help the team members cope up with the workloads without compromising the project expectations. 

●  Keeping up with the continuous technological changes- In contemporary times, technology keeps on changing at a rapid pace. The programming language that was used in the early 90s is not used in the 2000s. Every now and then some updates and advancements are coming, thus increasing the learning pressure and decreasing the value of existing knowledge.  The result can be poor performance, ultimately affecting the growth. In such cases, the team leaders must communicate with the team and help them find solutions, thus encouraging them to perform satisfactorily.

●  Dealing with routine tasks: Rapid growth in the organizations compels leaders to check on the strategic tasks instead of investing their time on routine tasks. To deal with such issues, the leaders must find or hire people who will be available to do those repetitive tasks. It must be ensured that the tasks are in responsible hands leading to more growth opportunities for the business.  

 AI teams’ focal challenge point – Lack of Experience

Since AI is in the nascent phase, executives do not have enough experience to build and manage AI teams. Thus, it becomes important for executives to choose their team members wisely. The primary requirement of the team is to have talent who have an in-depth understanding of the computer’s learning capabilities. Then only this team can collaborate with business leaders across functions to develop customized artificial intelligence applications.

As the leader or Chief AI Officer (CAIO), you need to have artificial intelligence education as well. The AI skills help these leaders to analyze different AI possibilities. If you are planning to develop your AI skills and manage the team more efficiently, enroll yourself in AI Certification courses. Be the Artificial Intelligence Leader who can assist their team as and when required.

Making Employees makes you the star leader

As per the report published by the World Economic Forum, Artificial Intelligence will replace 85 million jobs by 2025. It also states that AI will create 97 million jobs. While the numbers can be scary, there is no denying that Artificial Intelligence is disrupting the existing work culture. The current workforce needs to be upskilled or reskilled to survive in an AI-driven world. Hence as an Artificial Intelligence Leader, you must encourage your team members to devote a part of their time to gaining AI skills.

To create a team of AI expertsleaders can introduce programs within the organization that will help individuals get artificial intelligence education. This will not only benefit workers but also assist organizations in carrying out their AI strategy.

Be Future-Ready with global mindset and adaptive capacity

Organizations planning to adopt AI technology in their business processes are looking for talents that will help them transform AI research into applications. Thus it is highly important for organizations to have AI teams that are skilled in Applied Mathematics, Statistics, Computer Vision, Neural Networks, Machine Learning, etc. With technical diversity and complementary talents in the team, the organization can outline the AI strategy more precisely.

As per the estimates of Gartner, 50% of leaders in the IT sector struggle to get their AI projects beyond proof of concept (POC). The rate of failure of AI projects is high and needs to be dealt with properly. This is why the leaders must build appropriate roles within the organization. Since AI teams can be majorly divided into four categories viz. Data Engineer, Data Scientist, AI Architect, and Machine Learning Engineer, the goal should be to get all talents onboard. Thus assisting organizations to successfully initialize, implement, operationalize, as well as scale Artificial Intelligence projects.


There are no hard and fast rules to lead an Artificial Intelligence Team within an organization. However, the effectiveness of the AI team depends on the leader’s ability to define roles associated with AI within an organization. Furthermore, to increase the efficacy of leadership and assist the team to deliver project expectations, the leader must be aware of AI capabilities to outline project descriptions accordingly. As long as the leaders know that the team is not overloaded with work and are learning while working, the team will prove to deliver exceptional results. Thus, ensuring the leadership capability of the lead. 

Top 7 Popular Career Options in Artificial Intelligence

Career Options in Artificial Intelligence

Artificial Intelligence is one of the emerging technologies of the decade. Studies suggest that the industry will have 2.3 million positions by the year 2030. Artificial Intelligence is being used for multiple applications in multiple industries leading to more openings for AI jobs. AI will not seize jobs from us but is creating more jobs and making our mundane tasks easier and faster.

Some of the industries impacted by AI include manufacturing, healthcare, business intelligence, transportation, education, supply chain management, construction, retail, cybersecurity, and information technology.

When it comes to careers in AI, these industries stand out. Gartner’s report suggests that enterprise applications for AI have grown 270% in four years. Likewise, the number of industries using AI is also increasing rapidly. This has paved the way for qualified job candidates to take up AI jobs.

Let’s take a look at the career opportunities in AI here.

Robotics Programmer

As industries turn toward AI adoption, many industries are looking forward to hiring robotics programmers who can program their machines. Robotics programmers are generally involved in robotics design; an assemblage of robotic devices; corrective or preventative maintenance of the robotic systems; disassemble, repair or reassemble of robots or their components, test performance, train operators, and develop path programming.

A robot programmer earns about USD 54,600 per year or USD 28 per hour in the USA.

AI Engineer

AI Engineers are responsible for the commercialization of AI in businesses. AI engineers are responsible for designing and implementing AI applications; understanding business problems and find solutions with AI; apply the right AI computing technologies to solve the problems. They are mainly responsible to transform the entire infrastructure of the organization.

In general, the national average salary for an AI engineer is USD 1,15,320 in the United States.

Computer and Information Research Scientists

It is a special designation where professionals use data to design new technological solutions for businesses. They develop innovative applications by using existing and emerging technologies. The professionals may work with robotics, AI programming, algorithms, and cloud computing.

The average salary for a Computer and Information Scientist is USD 115740.

AI Research Scientist

Research in Artificial Intelligence is as important as other application careers in AI. Discovering ways to advance AI technology is as important as applying the technology. AI research specialists help to advance the data systems, get actively involved in the development of new software, and look for new possibilities in the domain. They are accountable for creating new AI tools.

Studies show that AI Research Scientist earns about USD 109,859 per year.

Machine learning engineer

Machine learning forms the core of AI projects. Machine learning engineers are responsible for understanding theoretical data science models and scale them out to production-level models which can handle terabytes of real-time data.

In fact, machine learning engineers command high salaries with a record salary of USD 127,000 per year.

Working in the defense department

Professionals having an AI certification and a relevant degree can land a position in military forces. The AI professionals here are generally involved in developing smart weaponry. They also have the option of pension after their retirement period.

The AI professionals in the military force earn about USD 73,000 per year along with a benefits package.

Video game programmer

This is an interesting AI job profile. Candidates with AI degrees, AI certifications, and computer languages are eligible for this job. They also should know 2-D and 3-D animating and design and its related themes. They are mainly responsible for role-playing mechanics and improve the user experience.

Currently, video game programmer earns about USD 75,000 to USD 125,000 per year. 

To conclude…

These are some of the most popular career options in Artificial Intelligence we find today. To choose anyone among them, it is best recommended to hold an AI certification along with a degree. Being a problem solver along with business skills is much needed to ace a career in Artificial Intelligence.