Beyond the Assembly Line: Vertical AI as the Next Wave of Intelligent Automation
Empowering Work with Smart Assistants
As founder of a startup building Smart Assistants for the modern enterprise, I spend a great deal of time considering how we can liberate talented professionals from the grind of repetitive tasks.
The future of work isn’t just getting people to do boring work faster and better. It’s about freeing them to think, create, and innovate. That’s why the shift from rules-based Robotic Process Automation (RPA) to genuinely intelligent automation stands out as a defining trend for the next decade.
According to a16z, we’re witnessing the end of traditional RPA and the rise of intelligent automation - solutions powered by advanced AI that can handle complex tasks, understand context, and adapt as conditions change. This transformation moves us beyond automating simple workflows toward building solutions that can learn, reason, and deliver insights that inform strategic decisions.
To achieve this drive towards vertical AI - the practice of tailoring intelligent automation tools for specific industries - is emerging as a critical differentiator. Rather than deploying generic solutions, vertical AI hones in on the unique challenges of fields like financial services, SaaS, consulting, and even more traditional sectors that have historically relied on legacy technology stacks.
As Bessemer Venture Partners (BVP) noted in their “Future of AI is Vertical” essay, deeply specialised AI solutions have a stronger value proposition than one-size-fits-all platforms. They fit seamlessly into industry-specific workflows, understand niche terminology, and deliver recommendations that feel native, not bolted-on.
But what does this mean in practical terms? Consider financial services. Instead of using a generic AI tool that struggles to parse compliance rules or risk parameters, vertical AI solutions are trained on relevant datasets, regulatory frameworks, and market conditions. The result: automated agents that can quickly verify documentation, analyse risk, and recommend next best actions tailored to that environment. It’s like having a specialised team member who never sleeps, never tires, and constantly adapts to evolving markets.
We’ve started this journey by building a Smart Research Assistant to handle the repetitive and routine task of gathering, synthesising and presenting research reports for busy sales teams ahead of their sales meetings. By automating the process for pre-sales research, we’re freeing up 8 hours per person each week and reclaiming up to $20,000 per person every year in lost productivity.
(Sign-up for a free access to the beta version at here.)
Looking ahead, we see a clear roadmap for the deployment of swarms of smart assistants to complete a sequence of tasks simultaneously.
A recent discussion on a Y Combinator podcast suggested that the market potential for vertical AI agents could surpass SaaS by a factor of ten. This is a bold claim, but it makes sense. Traditional SaaS applications often give you a toolset, but you still have to do the work. Vertical AI agents deliver outcomes. They learn from data, pivot strategies on-the-fly, and help you tackle challenges that previously required a cadre of human analysts. This outcome-oriented paradigm shifts technology investments from mere efficiency plays to strategic imperatives and significant value creation.
Of course, implementing intelligent automation is not without complexities. Leaders must ensure data privacy, maintain compliance, and guide employees through changes in their workflows. Training and change management are critical. Employees should understand that these tools are not replacements but enhancements - partners designed to handle routine tasks, freeing them to focus on strategic, high-level work. This approach not only improves productivity but also elevates job satisfaction, giving professionals more opportunities to do what humans do best: solve complex problems creatively.
The transition from RPA to intelligent automation and the rise of vertical AI isn’t just another trend. It’s a structural change in how organisations operate and points to the future of work. Instead of automating at the surface level - moving digital widgets from one column to another - companies can now build AI agents that deeply understand their business contexts. By doing so, they stand to achieve breakthroughs in efficiency, quality, and agility while empowering their people to do more of what they love in their jobs, which enhances job satisfaction and engagement.
As we look ahead, the question for leaders isn’t whether to adopt intelligent automation, but how best to implement it. By selecting industry-specialised, context-aware AI solutions, organisations not only unlock efficiency gains but also redefine what’s possible in their markets. The era of generic, mechanical automation is coming to a close. The future belongs to those willing to harness the power of Smart Assistants