Adi Prakash is Founder and CEO of Sentient Ventures, an AI-native firm helping companies scale smarter with AI as the multiplier.
We’re almost halfway through 2025, and there’s a common pattern I’m seeing across the board: Business leaders are overwhelmed by the pace of AI change and aren’t seeing the impact of their AI investments. The problem isn’t effort or intent. The instinct is to chase tools, pick a product and move as fast as possible to keep up. But I believe that’s the wrong approach.
Access to AI is no longer the challenge. In fact, it’s the opposite. There are more AI products than most businesses know what to do with. We’ve got natural language models, computer vision platforms, predictive and forecasting engines and everything in between. What’s missing isn’t availability. It’s integration.
Winning in this next phase of AI isn’t about having the right tools. It’s about orchestrating the right flywheel by bringing into harmony three things: partners, capital and ecosystems. I’m talking about creating a system that reinforces itself over time, moves businesses forward and turns experiments into outcomes.
Partner Orchestration
When it comes to technology implementation, partnerships abound. We have infrastructure partners like AWS or Azure, tech vendors, solutions experts … the list goes on.
The partners I’m talking about are true integration partnerships that help you make the right tool and platform decisions and then embed those technologies into your existing business. Most organizations aren’t starting from scratch. They’re in motion, which means they need someone who can work across legacy systems, business logic and workflows to make AI useful today, not tomorrow when it’s too late.
That’s why orchestration is key. Without the right partner to help you integrate what you adopt, all you’re doing is buying more software. You’re not solving for value.
Capital As A Strategic Lever
Whether you’re a customer trying to adopt AI or a startup building AI tools, capital is part of the flywheel. But it needs to be smart.
For customers, the biggest shift is rethinking capital allocation. This isn’t a one-and-done investment. The market’s evolving too fast for that. Instead of betting everything on a single solution, companies need to adopt a stage-gated approach—small, fast-moving investments that let them test, learn and scale. That might mean revisiting budget cycles, embracing more flexible structures like venture debt or revenue-based financing, or finding a partner who can help you build a case for capital midyear, when traditional approvals are already locked.
For startups, the need is different. They don’t just need capital. They need distribution. They need validation loops. They need feedback that helps them evolve. Traditional venture funding doesn’t always offer that. What these companies need is an ecosystem that gives them access to customers, data and advisory support—alongside capital.
That’s what I mean by smart capital. Money that moves in the right direction, backed by real insight and demand.
Ecosystems Make AI Work
AI runs on data, but not just any data. You need the right data from the right sources in the right format. That’s why operating in a silo doesn’t work anymore. AI requires systems to talk to each other. It requires multiple dimensions of information. It requires domain expertise to make sense of what matters.
Think about autonomous vehicles. In addition to technologists who build sensors, who can understand and analyze sensor data, you need automobile experts, people versed in breaking down crash scenarios, regulators who know how cars behave in the real world and developers who can process all that input in real time. That’s orchestration. And it only happens in an ecosystem.
Some ecosystems already exist. NVIDIA’s is a great example. They’ve built support for developers, hardware makers and others who rely on their chips. But most companies aren’t in a well-structured ecosystem yet. Or they’re in one that’s too narrow. The question you need to ask is: Does my ecosystem give me access to top-tier partners, capital that moves with me and the knowledge I need to evolve?
If the answer is no, it’s time to make a change.
Creating The Flywheel
The truth is, many companies are stuck in the middle. They’ve made early investments. They’ve run some pilots. But they haven’t moved the needle. What they need is orchestration, even if they don’t know it yet. It’s the missing link between experimentation and scale.
Monday Morning Checklist:
1. Map your flywheel. Do you have named owners for partner, capital, and ecosystem lanes?
2. Stage-gate your spend. What 90-day experiment will unlock the next tranche?
3. Stress-test your ecosystem. Which external data or distribution nodes are missing?
Orchestrate these three, and see how AI shifts from line item to growth engine.
More than just a metaphor, the flywheel is a practical model for navigating the dizzying pace of AI. Partners help you deploy your capital wisely. Capital helps you access better partners and expand your ecosystem. A strong ecosystem brings you new insights, smarter options and long-term resilience. That’s the flywheel. Once it starts turning, each part strengthens the next.
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