Thought leadership is hard to find in AI and with GenAI it’s only getting harder. Navigating the world of Generative AI (GenAI) can be overwhelming for many leaders. The challenge is magnified by the scarcity of skilled professionals in this high-demand field. Future teams led by true thought leaders will outpace those relying on blind experimentation. GenAI compels leaders to elevate their tech acumen to effectively envision and execute strategies. Simply holding a title isn't enough; true value comes from a deep, practical understanding. How can you develop such skills? Analyze patterns and trends to build thought leadership. There are no shortcuts. Read as much as you can. Make AI Engineers, Software Engineers, Data Scientists your best friends and understand the base of technology. These are some common things I saw with some of the best AI leaders I worked with, that makes them different from others. The goal is not to learn “how to code”, but rather “what to code”. Leaders must not dismiss AI as just another tool. The basics of AI don't require you to be an engineer to appreciate its complexities. Someone who has practical skills and proposes an idea is more likely to be listened to than someone who is just throwing out fancy words. GenAI has already shortened the experimentation lifecycle and it will make things clear soon to flush out the fluff unless decision-makers don't want to see it. Don't assume that I don't need to know about mechanical engineering to drive a car. You do not need to know about thermodynamics/engine composition, but you should know about EVs vs ICs, support/maintenance needs, mileage/tire pressure, and when to take it to the garage to have it repaired. Ask yourself: Are you crafting a Flintstone cart or a sophisticated machine? In AI-driven projects, core technology is paramount. Embrace the challenge, invest in understanding, and lead with vision. #ExperienceFromTheField #WrittenByHuman #EditedByAI
Chris McKay
3w
This is so well articulated Nitin. I few things I recommend: 1. Regularly prune your social media feeds. Take advantage of the bell notifications on LinkedIn and lists on X. I have lists of creators, founders, researchers and builders/tinkerers/engineers. 2. Find credible sources that can help you to stay updated on important AI news and developments. It’s easy to get lost in the noise. 3. Use the tools yourself, read the research papers, listen to podcasts, engage in conversations.
Akash Mohan
3w
Hey Nitin Aggarwal how do we identify the real experts versus the charlatans 😊
Can't agree more. A deeper dive is the key. I have seen tons of experiments, POCs, POTs, POVs, some had good potential and some had good depth. But what is the customer looking for, is altogether a different story. I mean, they were impressed with any such disruptive tech in the past as well, weren't they? But that is not enough; I think what will really sell is a very strong combination of Thought Leadership as Nitin said and ability to churn out local LLMs quickly. After all we need to give them a vision with all sorts of security. This Combination is key to success for me. Thoughts??
I am not an AI academician nor an engineer but was thrown into the deep end of NL back in 2007. My work is to explain what AI can do and what the returns will be and what I can offer. That is my livelihood. So I keep it simple. The use cases and outcomes are what matter. People need to look for things, provide feedback, get support, engage. They want recommendations, advice and guides. All of these translate into commercial opportunities. Then there's detection, inference, prediction, simulation beyond people and into the monster known as a firm. The firm may be an SME or a large corporate or a small branch of a large corporate or a big branch of a small company. So simple use cases and complex use cases. What is the data base in use. How is it set up for use. What is the learning model in each case. Where are the algorithms applied. What is the implication from a user experience and benefits being passed to the client-and hence do they get the returns AI promises. So I will sit with the tech expert and understand what needs to be done on the engineering side and what that means. Lay people need to be persuaded beyond the hype. That was true long before AI. I have product and delivery capability. Clarity and honesty help too.
Eliot Amal
3w
Keep your basics right and Foundations strong. Build an environment for your team members where they are comfortable. Bring in cross skilling and encourage collaboration among other team members. Build a trust and lead by example that you are also aware of things happening in this AI space. Learn and grow with zero egos. I really like the second paragraph “Making AI Engineers and others as your best friends” very true the moment they are your friends you can unlock their true potential and help them achieve what they really wanted and you learn a lot after that. These are from my experience being a thought leader in AI/ML space.
I agree that to hold a leadership position, one must possess a strong foundation of knowledge in their field and lead by example for other team members...
Nitish K.
3w
I completely agree that developing practical skills and understanding the basics of AI is crucial for leaders to become true thought leaders in GenAI. Reading and analyzing patterns and trends, as well as building relationships with AI engineers, software engineers, and data scientists, can help leaders elevate their tech acumen and effectively envision and execute strategies. It's important to not dismiss AI as just another tool and to embrace the challenge of understanding its complexities
True thought leaders in AI are like zen monks who can also code: serene, wise, and incredibly rare. Navigating the GenAI landscape demands more than just a title; it requires a deep, practical understanding. It's not about knowing how to code; it's about knowing what to code. Think of it like the ikigai formula—finding the perfect balance between what you love, what you're good at, what the world needs, and what can get you paid. So, ditch the Flintstone cart and aim for a Tesla! Embrace the challenge, invest in understanding, and lead with vision.
Sandip Singh
3w
Great point. Nitin Aggarwal. The rapid evolution of GenAI indeed creates a knowledge gap, but this gap isn’t just at the leadership level - it permeates throughout organizations. successful GenAI adoption cant be a top-down initiative led by a few ‘experts.’ Instead, it requires an all-hands-on-deck approach, where every employee becomes an active participant in the AI journey.
Chief Scientist, Co-founder, Author
3wTo be a thought leader, people should know what they are doing. To know what they are doing, they must do, not just discuss. When they do, they will almost immediately realize that generative AI is not needed for most things. And then they will spend their time learning something that actually does get them praise and promotions, and some will become thought leaders in those domains. There are already many gen AI thought leaders. They were doing it long before chatGPT. They are not hard to find. I know a bunch, and one with a record deal making music w AI. Do people want a generative AI thought leader or a chatgpt thought leader?