Alan Flower, EVP and Head of AI & Cloud Native Labs, HCLTech, on how AI is transforming entrepreneurship – enabling startups to scale faster, innovate smarter and disrupt traditional business models
AI has been around for decades, but with the recent rise of evolutions like Generative and Agentic AI, more people have access to its transformative potential. The entrepreneurial landscape is no different.
AI was primarily seen as a tool for enhancing decision-making capabilities; its ability to recognize patterns and make predictions showed early promise. Today, the focus has quickly moved onto Generative AI systems that enhance productivity, augment human capabilities and enhance the ways in which we create content, whether computer code, images or complex documentation. More recently, the emergence of Agentic AI takes the technology beyond just a helpful assistant; now it brings fully autonomous decision-making and the ability to deliver outcomes. These significant new capabilities are powering new business models and redefining how startups scale, grow and evolve.
I’ve spent considerable time observing this evolution. What once took years to accomplish can now be achieved in a fraction of the time, thanks to AI-driven tools that make entrepreneurship faster and smarter.
The Generative AI wave — enhancing human effort
With the emergence of Generative AI in 2023, enlightened professionals soon realized they had an immensely powerful research tool available that could go far beyond the traditional Google-like approach to Search. Shortly thereafter, the availability of co-pilots provided direct acceleration to content creation.
These tools were primarily focused on augmenting human productivity. AI co-pilots provided insights, automation and recommendations, but they still left the human in charge. At this stage of the journey, AI acted as a guide, helping to identify the tasks to focus on, but the human remained responsible for deciding how to approach and complete them. In other words, AI advised which nail to hit.
For startups, this meant tools like AI-driven content assistants, sales intelligence software and customer support automation systems. These products empowered entrepreneurs to operate at scale, saving time and enhancing decision-making without fundamentally changing how businesses operated. AI helped entrepreneurs work more efficiently – but it didn’t take over the job.
The second wave: Semi-autonomous AI — automating routine tasks
It didn’t take long for companies to quickly build advanced Generative AI tools themselves. Quickly, nearly anyone could build their own chatbots, often with the ability to act upon corporate data and process it using tools. This stage saw AI moving beyond simple augmentation to automate routine tasks, while still leaving humans in the loop. At this point, AI started doing more of the work, taking over specific functions like invoice processing, recruitment automation and compliance checks.
For entrepreneurs and enterprises alike, this meant a reduction in manual workloads and a boost in efficiency. Startups could streamline operations, enabling faster decision-making, reducing overheads and improving margins. In this ongoing era, AI isn’t just assisting, but performing more of the work, with humans still retaining oversight. AI is holding the nail, while the human holds the hammer.
The third wave: Agentic AI — letting AI deliver outcomes
We’re now entering the Agentic age, where AI is not just assisting or automating tasks but is taking full control of business processes. With autonomous or agentic AI, there is no need for the human to always hold the hammer; AI picks it up and hits the nail for you.
AI-driven startups are leading the charge here. Companies like Vic.ai have revolutionized the accounting space by fully automating accounts payable with very high accuracy rates.
In other words, AI is now performing entire workflows independently, eliminating human involvement in the process. This represents a fundamental shift in how startups operate, moving away from manual processes and traditional systems to fully automated, self-driving business operations.
This is where the true disruption lies. By adopting AI that can autonomously perform tasks, startups can rethink their entire operational models. And the results are impressive: AI-native startups are scaling faster than ever before, enabling rapid growth and minimizing reliance on large teams.
The power of lean: Faster failures and success
But how does this all impact startup success rates? Historically, the startup ecosystem has been rife with high failure rates. In fact, it’s often said that up to 90% of startups don’t survive past five years. While AI might not directly improve success rates, it can significantly shorten the time it takes to either succeed or fail.
New tools, such as Lovable, allow any non-technical innovator with a good idea to go from concept to executable solution in minutes. The long-standing dependency on expensive development teams to get a new product out of the door is rapidly declining. AI can be used to help you build and ship products quickly.
The key here is that AI empowers entrepreneurs to iterate, pivot and experiment much faster. With AI tools, startups can launch products more efficiently, adjust business models quickly and streamline their go-to-market strategies. As a result, the time to failure is much shorter. Entrepreneurs can test their ideas, analyze results and refine their products with lightning speed, ultimately increasing their chances of hitting on something that works.
According to the Stripe 2024 Annual Letter, AI startups are accelerating their growth rates and significantly outperforming traditional business models. In the letter, Stripe highlighted that the top 100 AI companies in 2024 reached their annualized revenue milestones in just 24 months, compared to the 37 months it took the top 100 SaaS companies in 2018.
And AI is not just speeding up the entrepreneurial cycle, it is lowering the bar. Not just in terms of capital requirements, but also the human effort to get a business started. While today the average startup has just two founders, they can achieve so much more together, delaying the time it takes before they need significant capital to hire additional employees.
AI’s role in business model innovation
The key to success, however, is not just about adopting AI, it’s about using AI to fundamentally rethink how business is done. AI-driven startups are no longer just selling Software-as-a-Service (SaaS); they are offering fully managed services through the emerging Service as Software (SaS) model which delivers outcomes, often without the need for human intervention.
This is where we see the rise of the Agentic AI models, where AI becomes an autonomous service that delivers results. AI-powered services, such as marketing automation, sales prospecting and legal automation, are already disrupting industries. Take companies like Harvey, which quickly achieved unicorn status by disrupting the legal services space with AI-powered tools that provide law firms with more efficient workflows. This is one of many examples.
By integrating AI at the core of their business models, these startups aren’t just enhancing productivity, they’re redefining what it means to deliver value to clients. With AI handling the heavy lifting, entrepreneurs can focus on building new products, engaging with customers and scaling faster.
The data advantage: Domain-specific models
One of the most critical elements for AI-driven startups is data. In the past, large companies with vast amounts of data had the upper hand. But with AI, startups are now able to compete by focusing on domain-specific language models (DSLs) trained on their own proprietary data.
This creates a competitive advantage for startups that have access to specialized data, whether it’s in the form of synthetic data or first-party data, allowing them to fine tune their models and deliver highly targeted services. Rather than relying on massive datasets, smaller startups can harness the power of niche, high-quality data to fuel their AI systems and differentiate themselves from the competition.
This focus on training domain-specific models has been enabled by the broad availability of ‘open source’ foundational models, such Meta’s Llama – a family of LLMs. Using Llama as a starting point can give entrepreneurs a head start, by allowing them to fine-tune a foundational model and generate a domain-specific model tailored to their business using unique datasets.
AI: A double-edged sword?
While the AI revolution presents immense opportunities, it also comes with challenges. The rise of Agentic AI means that entrepreneurs need to ensure that AI systems are not only effective but also accountable. As AI takes on more responsibility, the question arises: Who is responsible when something goes wrong?
If an AI system misdiagnoses a patient or sends a wrong email, who bears the blame? This is a critical issue that will need to be addressed as AI becomes more integrated into business operations. There is legal accountability to be considered, as in many jurisdictions any action taken by AI is an incumbent responsibility of the owning organization. There are no easy answers, but as AI continues to evolve, we can expect a growing emphasis on accountability and transparency.
The AI-driven entrepreneurial revolution
The bottom line is clear: AI is transforming the way we build and scale businesses. By embracing autonomous AI, entrepreneurs can unlock unprecedented levels of efficiency, reduce operational costs and accelerate growth. AI is not just a tool for the tech-savvy, it will enable anyone to build and scale innovative businesses.
As we move into this new age of autonomous AI-powered entrepreneurship, the challenge is not about having and using the hammer, it’s about knowing when it’s time for AI to take over the process and help entrepreneurs build something that can scale exponentially.
