10 AI skills you need for a career in tech
By now, it’s no secret that proficiency with artificial intelligence (AI) is a necessity to move forward in the tech job market. Advancements in technology or new platforms roll out seemingly every day, and some of the biggest brands in the world are exploring the best implementations for AI—if it’s not already an integral part of their workflows.
If you’re curious about where AI is heading, take a look at these statistics:
AI still has a lot of growth left to accomplish. But one of the most eye-opening numbers is that 88% of those who don’t use generative AI are unclear about how it will affect their lives. This presents a huge opportunity for you to learn AI skills that will help boost your tech career.
What are those skills, exactly?
Why are AI skills in demand?
Experts and major publications in the tech space say that AI shows no signs of slowing down. In fact, according to Bloomberg Intelligence, AI’s market size is expected to grow to more than 30 times its size in the next decade.
Given these growth numbers, some of the most in-demand skills in today’s job market relate to AI for many reasons.
Firstly, artificial intelligence skills enable businesses to meet the current state of customer service. The digital age has given rise to smarter customers who know what they want and when they want it. As a result, companies must make the purchasing journey feel personal to each customer. Traditionally, pulling that off would require a lot of company time and resources. But, with AI, businesses can customize each user’s experience (through data-driven insight and AI chatbots, among other tools) to the point where they feel it was built for them alone.
Naturally, businesses can also use AI for data management automation. The primary benefit of this use case is reducing human error when handling large datasets. While that makes businesses in any industry run more smoothly, it’s an indispensable advantage in sectors like finance, where highly sensitive data like credit scores and bank account information are handled daily.
While these trends open tremendous growth opportunities for the technology itself, humans with in-demand AI skills still have their place in the job market. Today’s AI platforms can do amazing things, but such complex technology requires a guiding hand. The people responsible for monitoring and managing these machines must have highly specialized skills and education.
Essential AI skills
So, if AI needs humans, and these humans need to be highly skilled, the question becomes, “What specific skills are necessary?” Let’s explore some of these skills:
Technical skills:
- Programming languages: Python is the best, but R, Java, and C++ are also important based on your job. You’ll need to be proficient in writing clean, efficient code to build and interact with AI models.
- Data expertise: AI is all about data. Understanding data modeling, warehousing, and processing is essential. Familiarity with big data concepts and tools is a plus.
- Machine learning: This is the core of AI. It’s crucial to grasp machine learning algorithms, including deep learning and reinforcement learning.
- AI and ML frameworks: TensorFlow, PyTorch, scikit-learn—these are the tools that will help you build and train your models. Proficiency in these frameworks is a major asset.
- AI deployment and DevOps: Once you’ve built your model, you need to deploy it in the real world. Understanding deployment techniques and DevOps principles is becoming increasingly important.
- AI security: AI systems are vulnerable to attacks. Knowledge of AI security threats and mitigation strategies is a valuable skill.
Non-technical skills:
- Communication and collaboration: AI projects are rarely solo endeavors. You’ll need to explain complex AI concepts to nontechnical stakeholders and collaborate effectively with team members from various backgrounds.
- Adaptability and continuous learning: The AI field is constantly evolving. A willingness to learn and adapt to new tools and techniques is essential.
- Critical thinking and problem-solving: AI is all about solving complex problems. Strong analytical and problem-solving skills are key.
- Domain knowledge: While not always required, having deep knowledge of a specific industry (e.g., healthcare, finance) can make you a highly sought-after AI specialist.
The specific mix of skills you’ll need will depend on your chosen AI career path. But this should help give you a strong foundation for success in the exciting world of AI.
How to build AI skills
Job seekers should look into the following methods for developing marketable AI skills:
- Internships: An internship is an opportunity to gain practical, real-world experience on impactful AI projects. You can explore the practical implications of the latest platforms and build up your portfolio of work. Some companies may even offer apprenticeship programs combining the experience of an internship with the structured curriculum of an educational course.
- Online courses: Many companies, including some of the leaders in the tech space, offer online resources teaching the ins and outs. Students can choose subjects ranging from data science to machine learning (ML). The courses often use self-study formats, which is great for learning at your own pace. However, additional learning may be necessary without the guidance of an expert or instructor.
- Boot camps: Think of a boot camp as a more intensive internship. You’ll gain knowledge in the AI space by working on actual projects and acquiring skills necessary for the job market in a shorter timeframe. Be sure to research boot camps thoroughly, as some have a higher placement rate than others.
- College degrees: If you choose a more structured curriculum, the degree you receive would most likely be in a concentration like computer science, math, or data science, limiting the amount of time and experience you would have with practical AI applications.
Best jobs in AI right now
Designing a long-term career in AI means carefully selecting which path in the AI ecosystem you choose to follow. Many currently available job titles call for the AI skills that are in demand.
Here are some of the top positions to look for. Unless otherwise noted, the salaries listed below are according to Simplilearn.
1. Machine learning engineer
Machine learning (ML) or AI engineers are responsible for the end-to-end management of AI systems. They play an integral role in designing, building, and managing AI models that analyze large datasets and continue to improve and grow through their experience.
Qualifications: This position typically requires a degree in statistics, computer science, or a related field. Additionally, you’ll want to build your proficiency with programming languages like Python, R, and Java. Potential ML engineers would also do well to gain any prior experience they can with machine learning algorithms.
2. Robotic scientist
Robotic scientists are responsible for building robots that emulate human intelligence. Their tasks can range from assembling products to handling hazardous chemicals or assisting in precise medical procedures like surgery.
Qualifications: Robotic scientists generally require a mechanical engineering, electrical engineering, or robotics degree. You’ll also need intricate knowledge of systems engineering, robotics hardware, and computer programming to excel in this role.
3. Data scientist
Data scientists, or data engineers, focus on finding patterns and trends in large amounts of raw data. They depend on algorithms and statistical tools for their work, and companies use data scientist’s findings to make data-driven decisions to propel their business forward.
Qualifications: You’ll typically need a degree in data science, computer science, statistics, or a related field to become a data scientist. Proficiency in programming languages like Python and R, as well as data analytics tools like Tableau or SQL, is a plus.
4. Software engineer
Software engineers in the AI space develop software applications that leverage artificial intelligence or machine learning. These platforms can help businesses:
- Identify cost efficiencies that enable investments in other areas of potential growth
- Streamline development workflows and decision-making
Qualifications: A degree in statistics, mathematics, computer science, or a related field is required. Strong familiarity with programming languages, AI or ML algorithms, and data analysis is also important.
5. AI product manager
AI product managers serve more of an oversight function, monitoring teams that produce AI products from ideation to rollout. Ideally, these individuals possess intricate knowledge of the AI marketplace. They understand industry regulations, technical challenges, and other hurdles production teams might face on their go-to-market journey.
Qualifications: To fill these positions, you must have a deep understanding of both product management and AI technologies. Additional technical background is a bonus.
Interested in a tech job at Intuit?
Leveraging these AI skills can not only help boost your career but make you more marketable in the present. As this technology grows, these skills will only become more in demand. Spend time learning them, and your transition into today’s AI job market can be smooth. At Intuit, our strategy is to build an AI-driven technology platform to help power prosperity for small businesses. If you’re interested in being part of our team, visit the Intuit careers page for all AI openings and other technology roles. Learn how Intuit technologists are leveraging AI to solve some of the world’s most challenging financial problems and make a meaningful impact.