What do you do if your AI expertise is lost in translation to non-technical stakeholders?

It's important to bridge the gap between technical complexity and business applicability. Use Simple Language: Avoid jargon and technical terms that might not be familiar to your audience. Explain concepts using simple, everyday language. Align with Business Objectives: Link AI initiatives to strategic business objectives.

When your AI expertise is lost in translation to non-technical stakeholders, knowing your audience is key to effective communication. It involves understanding their background, interests, and the level of technical detail they are comfortable with. Tailoring your explanations to avoid jargon and using analogies or relatable examples can make complex AI concepts more accessible.

Assess Understanding: Gauge the level of technical understanding your audience has about AI. This can vary widely among stakeholders, from complete novices to those with a moderate understanding. Tailor Your Message: Customize your explanation based on the audience’s background. Focus on aspects that are most relevant to their interests or the impact on their domain.

I would recommend the following: 1. Know their technical background - Engineers may be able to relate to a few technical details but consultants, business owners and service providers will need to be explained in a different manner, completely void of any technical details. 2. Understand their level of familiarity with AI - You need to know if they can differentiate between a Rule Based system and AI. 3. Assess their ability to understand Data - This is important but overlooked many times. Unless your audience knows their data well, discussing AI systems built using that data will be tough. If they don't have any understanding, you may need to work on this as well.

For non-technical stakeholders, when discussing outcomes, focus on impact, novelty, and value-add of AI products. When discussing development, focus on time-to-completion, likelihood of success, and what success looks like. Make sure they understand the things they need to know to do their job--not the things you need to know to do yours.

Simplifying your language is essential when communicating AI expertise to non-technical stakeholders. Focus on using clear, straightforward terms instead of technical jargon or acronyms that could confuse or alienate your audience. It's helpful to break down complex ideas into smaller, digestible pieces, presenting them in a logical, step-by-step manner that builds understanding without overwhelming.

Avoid Jargon: Use simple, clear language instead of technical jargon or acronyms. If you must use technical terms, make sure to explain them in an accessible way. Use Analogies and Metaphors: Analogies can be powerful tools for explaining complex AI concepts. Relating AI processes to everyday tasks or familiar situations can help make your explanations more relatable.

Use AI! LLMs are phenomenal at explaining complex concepts in a way that can resonate with individuals on a personal level. Even the simple prompt "Explain like I'm in 8th grade" will yield an output in a way non-techies can understand. I like to use "Explain {topic, concept, idea, etc} to a {job function and title} with {level of tech knowledge}. If you have a tech spec, you can use that as the source document you want explained. If you don't use your best judgment on what you're trying to convey.

My recommendation will be to focus on: 1. Try to speak their language without diving into details. E.g., Consultants may react positively to data in excel as opposed to Engineers who may relate to demos with technical workflow. 2. Focus on their key target metrics & problem statement to identify examples in the industry 3. Use examples of a similar problem statement in the industry 4. Do NOT Dive into technical approaches unless they are ready

Simplifying your language is like speaking in a way that anyone can understand, whether they're familiar with AI or not. Instead of using fancy terms and complicated jargon, stick to plain and straightforward language. If you have to use technical terms, be sure to explain them in simple terms. Keep your sentences short and to the point, and use active voice and simple words to get your message across. Visuals like charts or diagrams can also help make your ideas clearer, and metaphors or comparisons can make complex concepts easier to grasp. It's all about making sure your message is crystal clear and easy for everyone to understand.

Checking for understanding is like making sure everyone is on the same page after a conversation or presentation. It's important to ask questions to see if your audience has any questions or concerns, and to listen carefully to their responses. Open-ended questions like "What are your thoughts?" or "Do you have any questions?" can help encourage discussion. Summarizing your main points at the end and following up with a written summary or next steps can also help reinforce your message and keep everyone aligned. It's all about making sure everyone understands and feels heard.

After sharing your message, it’s crucial to check if it landed as intended. Encourage feedback by asking open-ended questions like "What are your thoughts?" or "How does this align with your objectives?" Listen closely to their responses to identify any confusion or concerns. Wrap up by summarizing the key points and benefits, and offer a follow-up with more information to solidify understanding and keep the dialogue open. This ensures everyone's on the same page and fosters a collaborative atmosphere.

Seek Constructive Criticism: After presentations or meetings, ask for feedback on how well the material was understood and what could be improved. Adapt Your Approach: Use the feedback to refine your communication strategy for future interactions. Over time, you’ll develop a better sense of how to convey AI concepts effectively to different audiences.

Learning from feedback is like using constructive criticism to become a better communicator. It's important to ask for feedback on how you're doing and be open to hearing what others have to say. Take note of both the positive and negative feedback, and think about how you can use it to improve. Maybe you're great at explaining concepts but could work on your presentation style, or vice versa. Look for opportunities to practice and refine your skills, and don't hesitate to seek guidance from mentors or resources on effective communication. It's all about growing and becoming a more effective communicator over time.

Providing feedback is an art, not everyone may have it. Hence, identify your subject/s to seek feedback. Assess feedback, identify good to have and must have changes to your approach. Again, keeping the background of your subject/s in mind, tailor your approach.

Continuously learning is like staying curious and staying ahead of the game. In the world of AI, things are always changing, so it's important to keep up with the latest trends and techniques. This means staying informed about new developments in AI and understanding how they impact your work. You can learn a lot from other experts in the field and from studying how they communicate complex ideas in simple ways. It's also important to understand your audience and their needs, so you can tailor your message to resonate with them. By staying curious and always seeking to learn more, you'll be better equipped to communicate effectively and stay relevant in the ever-evolving world of AI.

I always find if I'm having fun, things work better. Don't take yourself too seriously, inject humor into what you do, and enjoy. You'll find that life will become more relaxed, even as you're able to accomplish more. And importantly -- you'll be able to relate to others, words will flow, and you won't be stuck in formal jargon.

Having fun is important, but don't forget the power of storytelling in your communication. Weave engaging narratives around your AI projects. Share the challenges, the breakthroughs, and the human impact of your work. Use analogies and real-world examples to make complex concepts relatable and memorable. Infuse your presentations with personality and passion. Let your enthusiasm for AI shine through.

Use this prompt: "I am trying to communicate my message to a non-technical audience, help rewrite my message to make it clearer, more compelling and add humor to make it more memorable. Original Message: [Insert boring message here]"

DEMO IT - if you provide an aha moment that resonates with people, they will be more patient throughout the less flashy moments of education because you showed them why they should care.

Well, I believe that individuals with expertise in any field (whether it be AI or otherwise) need to invest time in developing their communication skills as well. Being an expert in something without the ability to effectively communicate it to others wouldn't be of much use. Spend some time building up skills in effective communication; it will reduce the likelihood that people misunderstand you.

Jargon is an occupational hazard in AI unfortunately. So those that can break down jargon and relate to everyday life and business have the advantage. Start with the user problem and build from there. Don't be afraid to tackle some esoteric topic (e.g. discriminative vs. generative AI) but quickly relate it to practical application. Also don't be a hyper, but don't be a doomer either. Balance your narrative with both pros and cons. Some people worship complexity too much - usually to hide their lack of experience in the topic. Get over yourself and admit you don't know when you don't know. People will respect you better if you are authentic and not projecting some high and mighty image. Bring your audience with you in the journey.

Repetition is the key here. Do not let this thought creep in that this has been explained earlier. Repeat with varied approaches, keep an open mind, introspect on the questions being asked.

When the AI expertise isn’t understood by non-technical stakeholders, I simplify explanations, use relatable examples, and address their concerns. To improve awareness, I’ll conduct workshops, provide informational materials, and facilitate hands-on experiences to showcase AI’s benefits. Open communication channels will ensure ongoing dialogue and collaboration.

An AI translator is becoming a valuable role that can help bridge the gap between customer and engineering teams, just like a Business Analyst does. The role will drive not only successful adoption but also to get the maximum ROI while controlling costs. The role would help with effective communication among different stakeholders, requirement prioritization, stakeholder education (I notice that people want AI for everything because of the hype, even when there are simpler solutions or when AI is not suitable) stakeholder engagement, risk mitigation and creative problem solving. This role would also assist with governance and promote Responsible and Sustainable AI.