top of page

People-First AI:
Using AI To Offer Equal Chances for All

This blog is a collection of 2 LinkedIn Newsletter:
AI-For Families
AI-First Companies

Human Skills = Key for Success with AI

Successful AI careers and businesses requires more than just technical skills.

Human skills and understanding lay at the heart of success in the AI era.

To thrive, professionals and businesses must develop a set of soft skills that complement their AI knowledge and better solve problems.

This week, we'll explore the key soft skills needed for success with AI and provide tips on how to develop them.

  1. Data Literacy Data is the fuel that powers AI. Understanding your data is crucial. Data literacy involves the ability to read, understand, analyze and communicate data effectively. Tips: Invest time in learning about data collection, management, quality and governance. Practice working with different types of data and tools to build your confidence and proficiency.

  2. Critical Thinking and Problem Solving The best AI projects are the ones that solve real world problems. Develop a systematic approach to analyzing problems, evaluating solutions, and implementing effective strategies. Additionally, AI outputs should not be accepted at face value. Question and analyze them critically. Tips: Question assumptions, consider multiple perspectives and evaluate evidence thoroughly. Develop a habit of seeking out diverse perspectives and considering alternative explanations.

  3. Problem Framing Complex problems for humans can be complex for AI too. Learn to Problem Frame — break down complex problems into smaller, more manageable pieces that AI can handle effectively. This requires a deep understanding of the problem domain and the ability to identify key variables and constraints. Tips: Practice breaking large problems or tasks down into smaller sub-tasks.

  4. Domain Expertise AI can do many things. The value comes from using it for tasks that can lead to a measurable ROI. This involves a deep understanding of the industry, its challenges and its opportunities. Domain expertise can allow you to ask the right questions and create solutions that aligned with business objectives and customer needs. Tips: Invest time in learning about your industry and its unique challenges. Talk to everyone. Customers, managers, teammates, competitors, audience, etc. Collaborate and learn!

  5. Curiosity and Collaboration Curiosity drives innovation and exploration — collaboration encourages teamwork and knowledge sharing. Cultivating curiosity and fostering collaboration can lead to company and even industry breakthroughs. Tips: Encourage curiosity and collaboration. Incentive different team members to discuss diverse perspectives to drive innovation.

  6. Creativity and Innovation Let’s get something straight. AI is predictive. Humans are creative. Whatever AI creates is based on humans creativity. Hope that wasn’t confusing but if it was — AI is trained on data and when humans apply their creativity something amazing can happen! AI is not creative on its own… yet. Tip: Brainstorming sessions, hackathons, collaborate with diverse teams and experiment with new AI projects and techniques to spark innovative ideas.

  7. Adaptability and Flexibility AI and technology is always changing. The ability to adapt and remain flexible is crucial. Embrace change, be open to new ideas and continuously update your knowledge and skills to stay ahead of the curve. Adaptability involves the ability to embrace change, learn from failures and continuously update one's knowledge and skills. Be a forever student. Tips: Stay curious and open to new ideas and approaches in AI. Experiment frequently and view challenges as opportunities for learning and growth.

  8. User Focus: Keeping the users(people) at the heart of everything is crucial for the success of AI solutions. It involves understanding user needs, preferences, and behaviors, and designing AI solutions that serve them best. User-focused AI professionals prioritize user experience, usability, and accessibility in their designs. Tips: TALK TO YOUR USERS! Conduct user research to gain insights into user needs and preferences.

  9. Emotional Intelligence and Empathy: They enable professionals to build stronger relationships, collaborate effectively, and consider the ethical implications of AI solutions. These skills allow individuals to understand and manage their own emotions, as well as those of others, leading to improved communication, trust, and decision-making in an AI-driven workplace. Tips: Practice active listening, develop self-awareness, and engage with diverse groups to cultivate empathy and understand the potential impact of AI on different communities.

  10. Communication This should’ve been #1 but I wanted you leave on it. ‘Prompting’ is just communicating your natural language to an LLM. The better you can clearly communicate what you want an AI to do → the more likely it will be able to do it effectively. Being able to clearly communicate tasks, goals, ideas, needs, etc., will carry over and benefit other aspects of your career (and life) as well. Tips: Try explaining things in simple terms. Then try to make it even simpler. Learn to explain things in different ways, to different audiences with different levels of understanding the topic.

Mastering these soft skills will not only increase the likelihood of success in your AI projects but make you (or your organization) more well-rounded as a whole.

Next week, we’ll explore how to design AI-solutions that help identify and prioritize the most pressing problems faced by consumers and communities.

To start identifying some of the soft skills in yourself, your team or potential candidates check out: - Psychometric Workplace Assessment 👀


Jared - CAIO, AI Advisor & Founder


bottom of page