Careers in AI: 4 skills to help you succeed

The rapid growth of artificial intelligence (AI) is revolutionizing the business landscape. From the rise of large language models such as ChatGPT to the widespread use of AI-powered tools, the integration of AI technologies is set to create waves of disruption throughout the labor market. 

With a staggering 75% of companies looking to adopt disruptive technologies in the next five years, the urgency for businesses to adapt is clear.

As AI and machine learning specialists become the fastest-growing job category, the demand for workers skilled in harnessing AI and big data is on the rise.

The pressing question for business leaders is: What essential skills are needed for careers in AI? 

To find out, BusinessBecause sat down with professors Stéphanie Gauttier and Pierre Dal Zotto from Grenoble Ecole de Management.

Skills for future careers in AI

1. Knowledge of technologies to inform decision-making in careers in AI

Just as business leaders and project managers need a broad understanding of various departments and their functions, AI leaders must possess a foundational grasp of AI technological concepts. 

This knowledge is crucial when it comes to making informed decisions about allocating resources and addressing challenges in AI-driven projects. 

At Grenoble Ecole de Management (GEM), the MSc Managing with Data and Artificial Intelligence program covers the fundamentals of Python, SQL, and AI, fostering an algorithmic, step-by-step approach to problem-solving. 

These tools equip students with the necessary technological knowledge to inform business decisions and drive AI projects to completion, says Pierre.

“Algorithmic thinking is a logical skill that is more important to AI leaders than programming,” he adds.

The master’s in AI also includes courses on automation with low-code, no-code platforms—a method that allows individuals to develop applications and automate processes with minimal programming knowledge. 

2. Leadership skills in the age of AI

The integration of AI tools adds a new dimension to business leadership. To extract value from AI and enhance performance, leaders must develop a strategic approach for implementing AI within their organizations. By leveraging AI for routine tasks, employees can focus on more critical issues.

“There is more to AI leadership than technical skills. You need to know how to create value from AI, have a good sense of strategy, and understand how you're going to affect the processes of your organization,” says Stéphanie.

GEM students learn these skills through taught courses in strategic and project management, complementing their technical knowledge with business acumen. 

Practical opportunities to put this in action include a six to seven-week capstone project where students learn to fuse their technical, managerial, and strategic skills to solve real-world problems for local businesses.

“The capstone project simulates a client brief. At the end, students present their work to the director of data and AI from Microsoft, and receive feedback on their ideas,” Stéphanie explains.

Additionally, students can access immersive experiences with virtual reality to exercise soft skills such as managerial conversations outside of class. 

3. Ethical risk awareness is important for careers in AI

With rising concerns around the ethical implications of AI, understanding how to manage these risks is an important part of adopting AI technologies in business. 

This involves accounting for a range of critical issues such as data responsibility, biases in data models, and privacy concerns. On the GEM MSc, ethics is a core pillar of the curriculum.

“You have to be mindful of all the ethical problems that society is discussing.As a business leader,these become your problems too, so we place a strong emphasis on ethics at GEM,” adds Stéphanie. 

The master’s degree in AI teaches core theoretical knowledge of ethics through courses in responsible AI, focusing on ethical, legal, and societal risks.

“We provide students with the theory behind ethics in very practical terms and make them investigate different technologies to identify and analyze current ethical dilemmas,” says Stéphanie. 

Translating this to a real-world context, students visit companies that emphasize responsible development and technology, providing insight into how ethically driven AI-use can align with company objectives.

4. Adaptability and a willingness to learn

In the fast-evolving landscape of AI, adaptability and continuous learning are critical traits for effective leadership. 

The master’s in AI cultivates this mindset with a diverse student body. Comprising of professionals at various career stages, this makes for enriching classroom discussion.

“We have professionals who are decades into their careers and interested in studying AI, and others who have just finished their bachelor’s degree,” says Pierre.

Grenoble reputation as the ‘Silicon Valley of France’ provides a strong backdrop to study AI. Immersed in a high-tech ecosystem, students benefit from close proximity to industry leaders and cutting-edge tech developments, adds Pierre.

The AI-driven workplace calls for leaders to upskill. By committing to continuous learning and maintaining strong ethical standards, business leaders can ensure their implementation of AI provides their organizations with a competitive edge in the market.