Top 10 AI Skills You Need to Compete in the Digital World

Snowflake’s AI and Data Predictions Report 2024 reveals that the growth of Language Learning Models (LLMs) and generative Artificial Intelligence (AI) will create high demand for data scientists, data engineers, and business intelligence analysts. However, despite the growing demand, professionals are unable to secure well-paying AI roles, primarily because of the skill gap. This blog tells you the top 10 AI skills you can learn to bridge the skill gap and build a successful career in AI.

What are the Top AI Skills Required to Succeed in a Digitally Dynamic World?

Top AI skills involve both technical skills, such as programming and data engineering, and soft skills, such as communication and problem-solving. Let’s see the top 10 AI skills that you need to succeed in a digitally dynamic world.

1. Programming Languages

To become an AI engineer, you must learn popular programming languages, including  Python, Java, C++, JavaScript, LISP, Julia, R, and Haskell. Practical knowledge of these languages helps you write codes to develop AI models that can solve complex problems.

2. Data Analytics

Organizations are leveraging AI for business intelligence, which involves analyzing large data sets and deriving customer or industry insights or trends. It helps organizations make strategic decisions. Therefore, for AI enthusiasts interested in improving business processes, innovation, or generating new business opportunities, data analytics ranks as one of the top AI skills.

3. Data Modeling

This technique involves representing data flow in a structured manner. It ensures data accessibility and accuracy for AI models.

4. Deep Learning 

This is a machine learning technique that comprises multiple layers called neural networks to imitate human behavior. It helps AI models perform complex tasks like driving cars, industrial manufacturing, and detecting cancer cells.

5. Data Engineering

Data engineering refers to collecting, managing, and manipulating data into relevant formats that researchers, scientists, or professionals can interpret and utilize for decision-making. Since AI models require correct data sets to give effective results, data engineering is one of the core AI skills to learn for the future.

6. Natural Language Processing

Natural Language Processing (NLP) is a branch of AI that enables computers to understand human language in the form of text or speech. Since AI systems use large amounts of data, they need to interpret such data to provide correct results effectively. Therefore, AI professionals should learn NLP applications and functions to become successful AI engineers.

7. Communication Skills

Many organizations use AI models, including chatbots and virtual assistants, for seamless communication. However, these models require large data sets for training. Therefore, AI professionals must have excellent communication skills to chat with AI models and train them. Moreover, AI professionals should also be able to communicate AI model developments to relevant stakeholders. Therefore, communication is one of the top AI skills for the future.

8. Problem-Solving 

In AI, problem-solving means using various techniques, defining the problem statement, and finding solutions. Since AI’s main purpose is to solve complex problems that are difficult to solve manually, problem-solving is one of the most important AI skills.

9. Excellent Prompting Skills

Whether you want to pursue a career in AI engineering or management, excellent prompting skills are a must. You must know how to write clear and concise prompts for AI models to get desired outputs.

10. Ethics and Risk Management 

Shadow AI (unauthorized use of AI that an organization’s IT department does not govern) is becoming increasingly popular. Hence, organizations need AI professionals skilled in ethics and risk management who can frame corporate policies to curb shadow AI. Therefore, ethics and risk management are among the most in-demand AI skills.

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How Can AI Professionals Enhance Their Skills to Stay Relevant in the Rapidly Evolving AI Landscape?

Since the AI landscape is evolving rapidly, professionals need to stay updated with the latest trends, tools, and developments in this field. The following are some effective ways to gain AI skills:

1. Pursue Online AI Courses

Practical skills-based AI and ML courses teach AI fundamentals and help you gain AI skills through outcome-based learning and practical projects.

2. Join Online AI Communities

Also, join online communities of AI professionals on Slack, Discord, Telegram, or other platforms to exchange knowledge and ideas with other AI professionals.

3. Contribute to Open-Source Projects 

Another way to learn AI skills is to contribute to open-source AI projects, including Tensorflow, Pytorch, Deepfacelab, and Keras, to work on AI applications and acquire in-demand skills.

4. Read Blogs and Tutorials

Some of the popular AI blogs and newsletters that you can subscribe to are Gartner, IBM, OpenAI, AWS Machine Learning, and Google AI blog. You can also read reports or studies published by these organizations to learn relevant insights.

5. Attend AI Conferences

Participating in AI webinars and conferences also helps you learn the latest AI trends and skills. Propose or work on interesting research ideas or unique AI solutions.

6. Participate in AI Challenges and Competitions

Taking part in AI competitions or challenges organized by various companies, such as Global AI Hackers, is an excellent way to learn AI skills.

ALSO READ: How to Become an AI Engineer: A Comprehensive Guide

What are the Challenges of Developing AI Skills in a Digitally Dynamic World?

A survey by Salesforce reveals that 66% of employees lack AI skills. Some significant reasons for the skill gap are:

1. Lack of Effective AI Training Courses

While several AI courses are available online, many of them do not offer practical training for the latest AI skills, resulting in a significant skill gap.

2. Poor Data Quality

A study by Great Expectations, a data quality platform, reveals that 77% of organizations have data quality issues. Poor-quality data impacts AI performance and results in poor training.

3. Lack of Powerful AI Leadership

Artificial intelligence is a disruptive technology that requires skilled and ethical managers to lead the way. However, the constant advancements and challenges make it difficult for organizations and professionals to build expertise. Therefore, it impacts AI training initiatives.

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How do AI Managers Benefit From a Comprehensive Understanding of AI Skills?

Here are some of the benefits of AI skills for AI managers.

1. Future-Proof Career

AI is emerging as the most powerful technology in this digitally dynamic world. According to Gartner, generative AI will emerge as a workforce partner for 90% of organizations, creating a huge demand for AI professionals. Therefore, learning AI skills can future-proof your career.

2. Career Advancement 

An AWS Study on AI Skills reveals that 84% of employees believe that learning AI skills will impact their careers positively. Therefore, eight out of 10 professionals are determined to learn the latest AI skills and techniques.

3. Higher Pay

The AWS study also reveals that employers are inclined to pay a salary premium to professionals possessing AI skills. AI skills can boost salaries by 30% in the human resources field, 47% in IT, 38% in sales and marketing, and 37% in business and finance operations.

4. Task Efficiency

Employers believe that AI skills can substantially boost productivity. This increase in productivity will result in employers rewarding their employees.

What Emerging AI Trends Should Professionals Focus on to Survive in a Digitally Dynamic World?

AI models and their usage are constantly evolving in a digitally dynamic world. Therefore, professionals need to stay updated with the following trends to succeed in their careers:

1. Generative AI

Generative AI is a branch of artificial intelligence that generates content in the form of images, texts, audio, and visuals. According to McKinsey’s State of AI in 2023 report, organizations will leverage generative AI to reduce business costs, create new business opportunities, increase revenue, and generate valuable insights. Therefore, it is one of the most popular trends professionals need to learn to build a career in AI. 

2. AI Trust, Risk and Security Management (AI TRiSM)

Data privacy, security, and ethical concerns are some of the biggest AI challenges for organizations. Therefore, AI and ML specialists are promoting measures to boost trust, security, and management in AI, making it one of the key trends to learn. Gartner defines AI TRiSM as a framework that comprises solutions and techniques to facilitate the fairness, reliability, and trustworthiness of AI models.

3. AI-Augmented Development

This trend involves using AI and machine learning for software development. It enhances efficiency and improves the quality of software. AI-augmented development helps businesses offer better quality products and services, thus enhancing customer satisfaction and boosting revenue. Therefore, professionals must learn how to use AI for software development.

4. Multimodal AI

Multimodal AI is a type of generative AI system that can process inputs in different formats, such as images or text, and generate output in different modalities. For example, if a Ray-Ban Meta smart glasses gives a speech prompt to identify an object, the model will capture an image of the object and process speech simultaneously.

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The global AI landscape is evolving at a rapid pace. Therefore, AI enthusiasts must learn high-paying AI skills through online courses to build a successful career. Emeritus offers skills-based AI courses that help professionals learn the latest AI trends and techniques. Explore Emeritus’ online artificial intelligence and machine learning courses to advance your career.

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