You're an AI professional looking to make an impact at work. How can you show your value to your employer?

No one cares about models, fancy frameworks, and cool new libraries Solving a business problem isn't much different than a personal one It's about finding where the most pain is lurking (within an organization) And the question an AI professional should seek to answer: How can i use a prediction machine that creates the leverage to alleviate it? If a missing piece of information can be generated through an AI prediction and it solves the problem, suddenly the value of a model becomes crystal clear

A clever use case in clinical research specifically is using AI to spot patterns in large healthcare datasets. Can we predict which patients will do better on Prozac vs. Zoloft vs. Wellbutrin? Can we shield patients from treatments that won’t work but may cause severe side effects? Can we help patients get diagnosed before their disease causes permanent disability? The market (the world!) has many questions that we can address with technology.

As with any project, start with identifying use cases that align with your business goals or organizational goals. If you are in a smaller team within a larger organization, focus on your team's goals but tie it to a broader organizational goal. One of the best ways to make an impact is to approach the stakeholders with a proof-of-concept as demo. There are many platforms that offer quick AI deployment tools.

Como profesional de IA, puedes demostrar tu valor alineándote con los objetivos empresariales de tu empleador. Una estrategia efectiva es enfocarte en lograr "victorias tempranas": identifica y soluciona problemas cotidianos que son un dolor de cabeza para la empresa. Estos pueden ser procesos ineficientes, costos excesivos, o cualquier desafío que, al ser resuelto con IA, resulte en un impacto positivo y claramente medible. Desarrolla un caso de éxito pequeño pero impactante, que demuestre con datos concretos cómo tu solución de IA ha mejorado un aspecto específico del negocio. Esto no solo muestra tu habilidad para aplicar IA de manera práctica y efectiva, sino que también evidencia tu comprensión de las necesidades y objetivos del negoci

AI professional at work can contribute in all possible ways. 1) The roles and responsibilities can be delivered at best using AI. Example: if you in charge of AI tools performance, you can AI develop model with legacy data so your model can perform a performance analysis on your tools and generate reports timely and you can move on to next project. 2) Help your organization to build AI models/projects that help your company either in increasing their product portfolio hence revenue or increase ROI by building cost saving models so less investment and more margins.

A proof-of-concept can be a great pitch to get additional resources for a pilot project. You can use the principles of MLOps or LLMOps to get the most out of your pilot project. The key steps include defining the scope, selecting the model and architecture, adapting and aligning the model and application integration with clearly defined metrics and KPIs that capture the value proposition.

Make your results impossible to ignore. No dense technical reports, use your data storytelling tools: clear visuals, dashboards, and powerful before/after comparisons. Be ready with an 'elevator pitch' version that any and everyone can understand.

All these reports are great examples of supporting material but don’t forgot to spend time and effort on your executive summary. If your executive summary is not engaging and useful they will never get around to your dashboard and charts

Don’t just tell; show. Transform your achievements into compelling stories that spotlight the tangible benefits your AI projects bring to the table. Think beyond numbers and algorithms; weave narratives that connect your results with real-world impact, making every success story a testament to your invaluable role in the organization.

It will be crucial to demonstrate how your work contributes to achieving the company's objectives, whether through increasing efficiency, generating revenue, or enhancing customer satisfaction. Use clear metrics and real-world examples to highlight the significance of your contributions.

Have a clear framework for AI adoption for your business or personal use case. Define your goals and metrics. When you come across new information on AI you can leverage the framework and metrics to see how that information fits to your unique needs. Once you have your goals identified, it also gets easier to look for relevant information.

Don't just learn, implement your learning FAST ⏩. Knowledge is only powerful when applied. Set aggressive deadlines for yourself and turn new techniques into real-world improvements.

🧠 Lifelong learning and improving is essential in the field of AI. Having a growth mindset and lifelong learning mentality helps you improve in your daily tasks in AI 🧠 🤖. 📚 Books, online courses, and online communities are great options to learn, network, and stay updated in the field. Experimenting with/applying some of the innovative concepts to your work also contribute to your enthusiasm, motivation, and enjoyment. Any issue/problem/mistake can be overcome with the right mentality, and use it to learn and grow.

This in my opinion is the most important step. AI is moving too fast to keep track of everything - you would need to develop an AI to do that. (AI humour). Learn the fundamental and reasons why things work and how pieces fit together. These aspects are slow moving in comparison to the latest and greatest tech solution or startup. You will also become exposed to experts in niche areas that may become great resources.

Embrace the role of a lifelong learner, always on the hunt for new AI trends and technologies. Your growth journey is a beacon of your dedication, demonstrating to your employer that you're not just keeping pace with AI advancements—you're leading the charge, ready to apply fresh insights to propel the company forward.

An example is drawing a diagram for someone to help explain a difficult concept. I find after drawing a simple diagram people are more likely to get it and this difficult concept becomes common sense. A lot of technical jargon is used by people to make themselves sound smart. A couple of circles and some lines on a piece of paper to explain something makes others smart. And they will remember it and you

Engage fervently in collaborative endeavors both internally and externally. Cultivate seamless teamwork, leveraging collective expertise from colleagues, cross-functional teams, and external partners. Proactively disseminate your wealth of knowledge, skills, and experiences, offering valuable guidance and feedback.

Be the AI collaborator everyone counts on, bridging gaps between teams and demystifying AI for non-tech colleagues. Your ability to contribute across the board, enhancing projects with AI solutions while fostering an environment of knowledge sharing, marks you as a linchpin in the organization's success.

You can make a meaningful contribution by working closely with your team to identify areas where AI can drive efficiency, innovation, and solve complex problems. Share your knowledge, mentor others, and actively participate in projects that align with your organization's goals. Demonstrating your ability to enhance processes, decision-making, and outcomes with AI will showcase your value to your employer which is essential in this current market.

Show your value to your employer by showing what value you generate for his customers, which feed him and ultimately you. At its current state, AI is a predestined instrument to continuously improve & quickly adjust products & services to people’s & companies’ specific needs. Neither strive for perfection or truth nor to conformity. Value arises as AI driven digital companions adopt to individual human or enterprise needs, not vice versa. From data harmonization to quality assurance, via enriching knowledge and personalized recommendations to assisting planning and conceptualization: Meet your customers' individual challenges. It’s that measurable benefit for your users that generates the value and that makes you valuable for your employer.

Build a portfolio of AI projects. Text-to-code generation models are breaking barriers and democratizing technology. There are many no-code platforms that offer end-to-end AI model deployment.

An alternative is to find a mentor that can more quickly help you increase your skill level. It is much easier to learn from someone than to try and learn on your own. The highest level of learning can come from mentoring others.

Chase the challenges that others might shy away from, seeing them as your stage to shine. It's about identifying opportunities where AI can make a significant difference, tackling them head-on, and turning potential obstacles into showcases of your problem-solving prowess and innovation.

Suggest useful applications at your workplace and then, most importantly, offer to provide hands-on training to peers via webinars. I’ve seen some people make the mistake of stopping at the suggestions. You provide a whole other level of value to help scale use!

Play around with AI. There are so many applications and open-source models out there to get started. Once you find the right resources, learning the basics of AI is not a challenge. There are many communities, meetups and forums that can keep you motivated, provide feedback and offer mentorship.

It starts with building and experimenting. Explore the tools; you don't need a goal other than learning at first. Once you understand the technology and what it can do, apply it to your work, build workflows and frameworks, and track your progress. Then go an teach others, share your frameworks and share how you achieved results. Then, keep sharing and providing value to your colleagues. Speak up and asked to be put on or lead an AI project.

Step into the spotlight with confidence, proposing AI-driven initiatives that align with company goals before being asked. Your proactive stance not only highlights your enthusiasm and confidence in your skills but also your vision for how AI can continue to transform the company, positioning you as a forward-thinking asset.

In proving your value as an AI professional, it's not just about what you can do with technology but how you embody the qualities of a visionary leader in the field. Cultivate a mindset that looks beyond the code to the broader impact of your work on the company culture, client satisfaction, and industry innovation. It's about painting a picture where AI is not just a tool but a transformative force, with you as its adept navigator, steering the company toward uncharted territories of success and growth.

I wrote this in 2018, when asked, “What if computers become more intelligent than humans?” To which I said- “Not a question worth asking. Simply put, if they did, everything we know would be flipped. Computers control the world in this day and age. A smart computer can do millions of tasks at once. For example, holding a conversation with someone in france, and processing visual information for a camera somewhere, and being able to mess with the markets, almost all simultaneously. Time isn't as relevant to a computer that processes at near the speed of light.” And this is ever more so true today, because I know for a fact that ai is smarter than any human on the planet and it even pretends not to know things if you don’t provide keywords.