There's a growing misconception that technology capable of operating without human intervention is automatically artificial intelligence. However, upon closer examination, many of these systems are merely powered by algorithms that lack the capacity for original thought. Put simply, they produce results based on existing information rather than creating new ones—a hallmark of true artificial intelligence.

Since artificial intelligence is a buzzword proven to draw attention, it's frequently used in contexts where it doesn't truly apply. This poses a problem for hiring managers because they might be misled by the term AI when evaluating candidates' skill sets. They could end up prioritizing candidates with skills in basic automation or simple algorithms over those with expertise in true AI and innovation. Additionally, it can lead to unrealistic expectations about what their technology can achieve, ultimately impacting project outcomes and company goals.

My aim is to clarify the differences between artificial intelligence and automation skills and roles to guide a coordinated hiring strategy for your company. 

Artificial Intelligence

Target Skills

When hiring AI talent, it's important to target candidates proficient in deep learning frameworks within the Python environment, such as TensorFlow, PyTorch, or Keras. Expertise in natural language processing is also important for text generation and language modeling, as these skills all contribute to a computer's ability to comprehend and interact with human language.

Although building AI isn't just about technical proficiency, it also requires creatives who can think outside the box to generate innovative ideas. Therefore, when evaluating candidates for AI roles, make sure to strike a good balance between hard and soft skills.

Common Roles

• Research Scientist
• Prompt Engineer
• Large Language Model (LLM) Engineer
• Natural Language Processing (NLP) Engineer
• Artificial Intelligence Ethics Officer
• Deep Learning Engineer
• Computer Vision Engineer
• Neural Network Engineer
  
  

Automation

Target Skills

When looking for talent in automation, focus on their skills with key machine learning tools from the Python library, like Scikit-learn, XGBoost, and LightGBM. Also, look for strong data processing abilities with SQL, as it ensures they can manage and prepare clean data to build good models.

As for soft skills, you should target candidates with strengths in analytical thinking and organization. These skills will help them break down complex problems into manageable parts.

Common Roles

• Software Quality Engineer
• DevOps Engineer
• Automation/Test Automation Engineer
• Automation Applications Engineer
• Automation Programmer
• Network Engineer
• Product Manager
• IT Systems Administrator
• Building Automation Engineer/Programmer
• Site Reliability Engineer
• Cloud Infrastructure Engineer/Architect 

Overlap

Target Skills

As you would expect, there are overlapping technical skills. Python's simple syntax and specialized libraries make it the primary language for talent across both areas. Also, knowledge of cloud platforms like AWS, Google Cloud, and Azure will be important, as they are commonly used for deploying and managing systems.

Adaptability is the foremost soft skill to target for candidates across both areas. The rapid pace of technological advancement means that today's tools and methodologies will quickly become obsolete. Therefore, it's critical to hire talent capable of adapting to change.

Common Roles

• Machine Learning Engineer
• Data Scientist / Analyst
• Software Engineer
• Product Management

Final Thoughts

According to a Salesforce report, 78% of executives say they either currently or plan to use artificial intelligence as part of their process automation initiatives. Failing to bridge the talent gap will cause your company to fall behind competitors committed to growth. That's why it's so important to get out in front of innovation and consult with the SMEs who can pair your organization with cutting-edge talent. Consider reaching out to us to start the conversation.