4 Must-Have AI Skill Areas for Any Independent Professional

To a greater or lesser extent, AI permeates every function in an enterprise. As an independent professional, even if your services are not specific to AI you must master relevant tools and stay current as they evolve. This can allow you to achieve and retain a favorable competitive position and expand your offerings to clients by adding AI-specific services.

These four AI skill areas are key to success for independents. Though your services may not be focused on technology, it is important to have an understanding of the technical areas and how they interact with AI.

1. Soft Skills

Applying intangible skills like adaptability, critical thinking, and communication is crucial to your success. You must be knowledgeable about current AI and understand how the field is evolving so that you can effectively incorporate the right tools into your own business.

This skill area can also help you offer new services to clients. For example:

• Help your client manage the change effort accompanying an AI system rollout
• Design processes and workflows that optimize the human-AI connection to achieve desired outcomes
• Train your client’s workers to use generative AI most effectively by creating prompts that produce the best results

2. Data Science and Engineering

If your services are centered on technology, and especially if data analysis and management have been central to your business portfolio, add this AI-related skill area to your toolbox. Companies want to make the best use of their data assets, and technology leaders know that AI is the way to go. Sharpen your proficiency with AI tools focusing on data mining and analytics, especially for the enormous datasets (aka Big Data) that already exist in some industries and will be common to many more. Understand how to apply AI to optimize data pipelines, develop algorithms, and automate analysis to help your clients get significantly better value from their data.

3. Machine Learning

Machine learning is an engineering competency that quickly analyzes enormous datasets, finds patterns in the data, and assists human decision-making based on those patterns. Machine learning algorithms apply data analysis to predict or forecast future outcomes. For example, a large part of Amazon’s user interface uses machine learning to predict and present relevant product offerings based on the user’s browsing and buying activity. When you have a good understanding of machine learning, you’ll see signs of it on your internet browser and in your email!

4. AI Application Creation

While a robust list of “off the shelf” AI tools is available to companies, information and IP security concerns are likely to prompt many enterprises to pursue custom AI applications. Generative AIs like ChatGPT and Microsoft Copilot, AI platforms that help users plan through predictive analytics, and chatbots are a few types of AI applications.

Independent professionals who have AI application creation skills will find a lot of opportunities with current and prospective clients. Independents who are “AI application adjacent,” which pretty much encompasses the rest of the independent population, should be conversant with the range of AI applications available to them and their clients.