AI Advisor | Author “From Data To Profit” | Course Instructor (Data & AI Strategy, Product Management, Leadership)
It’s better to be directionally correct than strategically perfect. Businesses that fail to understand this fail at AI and won’t be around much longer. Strategy finds the right direction. Execution iterates toward perfection. Getting the direction right means nailing two key factors: ✅ Customer Value. The AI feature or product must do something for people that wasn’t possible before to be directionally correct. We’ve seen that customers don’t pay enough for incremental improvements to offset the high costs of delivering AI products and features. ✅ Technical Feasibility. AI must meet people’s expectations for functionality and reliability to be directionally correct. Customers quickly abandon products that hallucinate or fail to integrate into their workflows. An impressive demo isn’t enough anymore. But if you strategize until perfection, the business will start too late. Companies that are afraid of mistakes will watch the competition iterate imperfection into a best-in-class AI product. I’m giving the opening keynote at Packt’s Generative AI conference about how to be directionally correct. People who guide their firms in the right technical and value directions are worth their weight in gold. Businesses, even current market leaders, that don’t have cross-domain expertise will be forced to close up shop in the next 5 years. #AIStrategy #ArtificialIntelligence #GenAI
Striving for perfection is the silent killer of growth. For companies to merely survive right now, leaders need to ask: Are we positioning ourselves to learn fast, or are we paralyzed by the pursuit of flawless strategy? High-performing leaders often arrive at the top by demanding excellence, but that mindset must evolve. In AI and beyond, speed of iteration and resilience to mistakes are essential to staying relevant. In my coaching practice, I've found that those executives who embrace directional clarity over perfection create exponential value because they make bold moves, adapt quickly, and don’t get trapped by analysis paralysis.
You need to work out where the world is going and move toward it. Your answers won't be perfect - if you wait for them to be perfect you'll still be sitting there when everyone else has moved on.
Vin, the significance of cross-domain knowledge in cutting-edge technologies is often underestimated when addressing strategic questions. It's crucial to return to the basics and pose relevant questions. Do I comprehend AI and its responsible applications? The time for mediocrity has passed.
AI and data are technologies that demo well are rarely very useful. It takes a little bit of awareness to know the difference between what demo is worth it and what is not.
That’s the factor that technical expert should most evaluate before joining a company. Otherwise they might end up being awesome in the wrong path and that gotta suck 😬
Ease of use, High accuracy can be also considered for directionally correct...
Vin Vashishta, you're spot on. Striking that balance between direction and execution is crucial. Aiming for perfection can lead to missed opportunities while competitors zoom past. What do you think makes companies hesitate to innovate?
Being directionally correct is such a crucial mindset in the fast-paced world of AI. How do you think businesses can best strike the balance between moving quickly and ensuring enough technical feasibility to avoid losing customer trust?
Nailing customer value and technical feasibility truly sets the stage. It'll be fascinating to see how your insights spark new ideas at the conference. What’s your favorite example of a directionally correct strategy in AI?
Dog dad | Data Science, AI, ML, Semantic Knowledge Graphs, Computer Vision
3wDepends on the industry. You need to be both directionally and strategically correct in healthcare and defense. With that being said, this advice probably only applies to things within general business domains like sales, loyalty, marketing, personalization, retail supply chain etc.