Main image of article Using Your Soft Skills to Teach AI Concepts

AI is transforming companies everywhere. Tech professionals are increasingly tasked with not only integrating AI into their current tech stacks, but also explaining the implications of AI to other stakeholders throughout their organizations, including those who aren’t technically inclined.

If you’re one of those tech pros who has to break down generative AI or machine learning for colleagues who are still trying to figure out how to download apps on their phone, then you know that "soft skills" such as empathy play a huge role in effectively communicating these often-complex topics. But what are the top things to consider when you have these discussions? Let’s break it down.  

Why This Is Important

While tech professionals may be deeply immersed in the intricacies of neural networks, machine learning algorithms, and data science, their colleagues may struggle to grasp these concepts. This disconnect can hinder progress, foster misunderstandings, and ultimately limit the potential of AI to drive innovation.

Meanwhile, miscommunication can have significant consequences in the context of AI projects. If non-technical stakeholders do not fully understand the capabilities and limitations of AI, they may make unrealistic expectations or embark on projects that are not feasible. This can lead to wasted resources, missed opportunities, and a loss of trust—for example, an executive who doesn’t fully understand the limits of generative AI may lay off nearly an entire team, hoping that AI will substitute for human skill, only to find that they can no longer effectively achieve their goals.

Simplifying Technical Jargon

One of the most significant challenges for tech professionals is translating complex technical concepts into language that is easily understood by non-technical audiences. This requires a deep understanding of the target audience's knowledge level and the ability to explain complex ideas in clear, concise terms. Here are some effective strategies:

  • Use analogies and metaphors: Comparing AI concepts to everyday objects or situations can help non-technical stakeholders visualize and understand them more easily. For example, explaining neural networks as a series of interconnected neurons can make the concept more relatable.
     
  • Avoid jargon: While technical terms may be essential for communicating with other experts, they can be confusing for non-technical audiences. Use plain language whenever possible, and if you must use technical terms, provide clear explanations or definitions.
     
  • Break down complex concepts into easy-to-digest chunks: Divide complex ideas into smaller, more manageable chunks. This will help non-technical stakeholders gradually build their understanding and avoid feeling overwhelmed.

Adjust Your Explanation to Your Audience

Effective communication requires tailoring explanations to the specific needs and interests of the audience. Consider the following factors when crafting your message:

  • Knowledge level: Adapt your explanations based on the audience's existing understanding of AI. For example, if you are speaking to senior executives, you may want to focus on the strategic implications of AI, while if you are addressing technical staff, you may need to delve into more technical details. In most cases, you probably can stick to the highest-level basics; your audience doesn’t need to know how a model actually works, but they do need to know what it can do.
     
  • Interests: Understand what the audience cares about and tailor your message accordingly. For instance, if you are presenting to a marketing team, you might emphasize the potential of AI to improve customer experiences and drive revenue.

Building Trust and Collaboration

To mitigate the risks of miscommunication and ensure successful AI initiatives, it is essential to build trust and collaboration between technical and non-technical stakeholders. Here are some strategies:

  • Be transparent: Openly communicate the progress, challenges, and limitations of AI projects. This will help build trust and prevent misunderstandings.
     
  • Seek feedback: Actively solicit input and feedback from non-technical stakeholders. This will help you understand their perspectives and ensure that your explanations are effective.
     
  • Foster collaboration: Encourage open dialogue and collaboration between technical and non-technical teams. This will help break down silos and ensure that AI initiatives are aligned with the overall business goals.

By developing strong communication skills and tailoring their explanations to different audiences, tech professionals can play a critical role in driving the successful adoption of AI. By bridging the gap between technical jargon and the understanding of non-technical stakeholders, they can foster collaboration, build trust, and unlock the full potential of AI to drive innovation and growth.