In an AI-powered world, one principle remains unchanged: Execution matters more than the business model itself.
While technical expertise and innovative ideas are valuable, they alone do not secure investment. Investors prioritise founders who can execute—who can take an idea, bring it to market, scale effectively, and navigate inevitable challenges with resilience and strategy.
This is why execution-driven teams often succeed even when their business models aren’t fully refined.
A strong team with a less-than-perfect model can still create significant investment value.
On the other hand, even the most well-crafted business model will fail if the team lacks the ability to execute.
At its core, startup success isn’t about having the “perfect” plan—it’s about having the agility to execute, adapt, and scale in a constantly evolving market. In an era where AI is revolutionising industries at an unprecedented pace, the ability to implement and iterate will separate the true innovators from those who simply follow the trend.
AI is reshaping the startup landscape
AI is no longer a distant future—it is actively transforming the way startups operate. What once required a large team of executives—CTO, CBO, COO—can now be managed by a lean founding team leveraging AI-driven automation.
Today, startups can scale from prototype (MVP) to revenue-generating businesses with fewer resources than ever before. AI-powered tools are enabling:
CTOs to handle a larger scope of coding tasks with fewer engineers.
CEOs to manage marketing, pitch decks, product design, and proof-of-concept (PoC) validation independently.
This shift allows startups to operate in a leaner, more agile, and cost-efficient manner.
Beyond startups, businesses across industries are embracing AI-driven automation to streamline operations and reduce workforce dependency. In the U.S. and Europe, companies are rapidly moving away from manual workflows toward AI-powered efficiency strategies.
AI isn’t just an enhancement—it’s a fundamental transformation that is redefining how businesses scale, innovate, and compete.
Winning in the AI-driven market: Strategy over hype
As AI continues to reshape industries, startups that go beyond simply adding AI features to existing products are the ones capturing long-term value. Rather than treating AI as an enhancement, the most forward-thinking startups are redesigning their businesses with AI at the core.
This shift requires a fundamental rethinking of problem-solving strategies. Instead of asking, “How can we integrate AI into what we already do?”, successful startups are reframing the question:
“How can AI completely transform the way we operate and create value?”
Even within the same industry, companies are leveraging AI to drive deep innovation and differentiation, rather than just small, incremental improvements. The key is to move beyond surface-level AI adoption and use it as a catalyst for reimagining business models, automating decision-making, and unlocking new market opportunities.
Ultimately, success in the AI-driven market isn’t about merely adopting AI—it’s about strategically redefining how AI can drive real impact and industry-wide transformation.
What investors are looking for
Investors have become increasingly discerning about AI startups and how they leverage the technology. Today, they distinguish between:
AI-native startups → Companies that build their business model around AI from the start, using it as a fundamental component of their strategy and product.
AI-enhanced businesses → Companies that add AI to existing products but haven’t fundamentally changed their approach. These businesses often struggle to prove AI’s core value to their model.
Investors are no longer simply looking for startups that use AI—they are asking how AI creates real, scalable value.
For startups seeking funding, the focus should not be on just incorporating AI but on leveraging AI to drive fundamental innovation and competitive advantage.
The pitfalls of AI integration
Many startups attempt to retrofit AI into existing products in an effort to make their business seem more cutting-edge. However, without a strategic approach, this can backfire.
Superficial AI adoption – Some industries have little natural synergy with AI, yet companies within them are adding AI features simply to position themselves as “AI startups.” Investors, however, quickly see through these shallow attempts.
Forcing AI into the business model – Startups eager to follow AI trends sometimes integrate AI in ways that don’t enhance their core offering, leading to unnecessary complexity without meaningful value.
For AI to be a true differentiator, it must enhance both the business model and the product itself.
Simply adding AI for the sake of rebranding rarely translates into long-term success.
The fear of AI: Resistance or reluctance?
History has shown that people often resist change, especially when it threatens familiar ways of working. In 19th-century Britain, the Luddites famously opposed industrialisation, going so far as to destroy machinery they believed would replace their jobs.
Fast forward to today, and we see a similar unease surrounding AI. Many fear that AI will disrupt industries, eliminate jobs, and render certain skills obsolete. However, much of this fear doesn’t stem from an actual inability to adapt, but rather from a reluctance to engage with and learn about new technology.
Innovation has always driven progress, and AI is no exception. Throughout history, technological advancements have eliminated some jobs but created entirely new industries in their place. The real challenge is not AI itself, but how individuals and businesses choose to respond to its rapid evolution.
A willingness to learn and adapt is more crucial than ever.
Those who embrace innovation often gain a competitive edge, while those who resist risk being left behind.
Also Read: Philippine VC Kaya Founders backs AI, fintech, and B2B innovators in 2025
Human-machine communication: A critical skill in the AI era
As AI rapidly advances, the way humans interact with machines is evolving. Modern AI, powered by natural language processing (NLP), no longer requires complex coding skills to operate. Instead, users can communicate with AI using everyday language, making human-machine interaction more intuitive than ever.
This shift is not just about convenience—it’s about accessibility and efficiency. AI systems are becoming faster, smarter, and easier to use, and this trend will only accelerate. Those who can effectively interact with AI will gain a competitive advantage, while those who struggle to adapt may find themselves at a disadvantage.
The misconception that AI is too technical or difficult to use is becoming obsolete. While a deep understanding of AI models like Large Language Models (LLMs) is valuable, the reality is that AI tools are being designed for broader accessibility—even for those without technical expertise.
Rather than viewing AI as a complex system, individuals and businesses should actively engage with it in practical ways.
Even basic familiarity with AI can provide a significant competitive edge in an increasingly AI-driven world.
In an era where AI is no longer optional but essential, the ability to communicate effectively with machines is becoming just as important as traditional digital literacy. Those who embrace AI as a tool for problem-solving and productivity will be at the forefront of the next wave of innovation.
Special thanks to Genya Smagin, Senior Manager, AI Strategy & Partnerships at SK Telecom for his valuable contributions to this article.
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