Heena Purohit

Fostering collaboration can be a game-changer for improving AI adoption: 1. Turn Early Adopters Into AI Champions: Recognize team members who embrace AI quickly. Encourage them to become internal AI champions. 2. Spotlight Success Stories: Create platforms for champions to showcase their AI experiences and successes through meetings, newsletters, or AI showcase sessions. 3. Facilitate Open Dialogue: Encourage peer-to-peer discussions about the AI implementation. This can be more relatable and impactful than top-down directives. 4. Listen for Opportunities: Use the feedback, concerns and questions from slow adopters as insights to identify barriers and tailor support. This also helps build a culture of continuous learning among the team.

Establishing a dose of realism is key, and this needs to be done continuously: - Before project kickoff, have upfront discussions on clear scope definition, realistic timelines, share previous experiences, including what worked / didn’t work. Educate stakeholders using simple language and relatable examples. - This also needs to be continued during the project. One of the best practices is to establish regular check-ins to discuss progress. Use these as opportunities to demonstrate tangible progress and gather early feedback. Additionally, provide insights into what worked and what didn’t work. This provides a “show, don’t just tell” way to help stakeholders understand the complexities and appreciate the iterative nature of AI development.

Practical experience can set you apart in AI interviews! Companies are looking for candidates that can apply knowledge to real-world problems. Even if you're applying for your first AI role, you can build and showcase relevant experiences by participating in activities such as hackathons, open-source projects, personal side projects or even volunteer work. Also be prepared to delve deeper into these experiences during the interview. Companies are not just looking for technical skills but also “soft skills” like collaboration, conflict resolution, persuasion, adaptability, etc. So make sure you're highlighting these leadership and interpersonal skills as you talk through your experiences during the interview.

Funding in AI is higher than many other categories, but it's also hyper-competitive. If looking to raise external funding, be prepared to answer: - What specific problem does your AI solve, and how large is the addressable market? - What is the customer doing to solve the problem today? How does your AI solution differentiate from other competitive solutions or alternates? - What is your startup's moat? This could be anything from unique data sets or algorithms, early traction in niche segments, strong user retention, etc. - How scalable is your AI solution, and what's your plan for growth? Do the unit economics make sense? - How do you plan to navigate potential ethical concerns or regulatory challenges in AI?

Continuous learning is not just beneficial, it’s essential to stay relevant and innovative. Here’s a practical approach to do this: 1. Set learning goals related to your profession, industry or interests 2. Identify credible sources that provide curated resources or commentary on a recurring basis. Based on your preferred learning medium, there’s a ton of newsletters, YouTube channels, podcasts, etc. 3. Reflect on the new knowledge by capturing what you learned. Spend time reflecting on how this could impact your work or life. I use Notion for this. 4. Share your insights with your network. Or better yet, apply your learnings in real-world scenarios, whether it’s through experimenting with new AI prompts/tools or kicking off side projects.

While there’s immense promise with using AI-powered image recognition tools to boost productivity, ensure that you are integrating AI considering its broader impact, and not just the technical capabilities above. For instance, a study showed that only 25% of tasks suitable for automation through computer vision are cost-effective to do so. So evaluate the benefits versus the costs of building, running, and maintaining the AI systems. More info on this study: bit.ly/3UpWUbq The aim should also be to enhance human creativity with AI. So focus on empowering individuals, prioritizing long-term benefits and value over immediate productivity or short-term profits. AI should be integrated responsibly, augmenting rather than replacing human effort.