Earlier this month Open AI made headlines when it introduced “Swarm,” an experimental framework designed to coordinate networks of AI agents. Though not an official product, Swarm provides developers with a blueprint for creating AI systems capable of autonomous collaboration on complex tasks.
What most people don’t realize is that teams of AI agents- known as Agentic AI- already have the ability to take over entire departments, replacing – and outpacing -white collar workers, says Simon Torrance, the London-based founder and CEO of two advisory firms: ‘AI Risk’ – a research, strategy and innovation network focused on developing and deploying AI effectively and safely -and ‘Embedded Finance & Insurance Strategies’ , which helps leaders across multiple sectors leverage fintech and insurtech to create new value and growth.
Torrance cites the following example: A year ago the entire operations team of a small European insurance brokerage left the company after being poached by a competitor. The CEO asked a friend, a successful insurtech entrepreneur and computer scientist who had just sold his predictive analytics business for advice. The friend- who prefers to remain anonymous for now – had some spare time to help and decided to try something radically new: re-designing the whole operations function using AI alone, with tools that already existed and were readily available.
While the company used some freelancers and other staff as stop gap measures the friend analyzed all the job tasks and workflows and, within three months, created a new ‘team’ comprised exclusively of AI agents that took on the roles of a commercial manager, an actuarial and underwriting function, an accountant, customer care managers and IT staff for the insurance brokerage. The brokerage’s data was not prepared for AI but many of these roles and processes are quite generic and Large Language Models (LLMs) could replicate them quite easily, says Torrance. That said, the friend in charge of the project had to very carefully map out the processes and then use other human colleagues and LLMs to enhance and develop them.
Once they were unleashed the Agentic AI outperformed its claims ratio objective by a factor of two, says Torrance.
Operating expenses plus claims costs typically determine net profit in the insurance industry, and human salaries, benefits and payroll taxes often make up around 65% of total operating expenses for a broker. By replacing humans and improving the claims ratio the AI team reduced those costs for the European brokerage to zero, says Torrance.
Typically, insurance underwriting generates a net profit (premiums minus claims costs and operating expenses) of around 5% in a good year. The Agentic AI team helped to generate insurance net profits of roughly 45% which was “completely unheard of and also unethical,” says Torrance, so tweaks had to be made.
Ethical, legal and safety guardrails clearly need to be put into place, but the European brokerage’s results give a glimpse of what is possible now, he says. The potential upside for enterprise is so great that Torrance and the computer scientist that built the Agentic agents for the insurance brokerage are in the process of creating a company that will offer corporates a no code product to create and manage teams of digital workers that are capable of autonomous decision-making, executing complex tasks with minimal human intervention, collaborating with other systems and people and dynamically adapting to changing conditions.
“Companies will be able to increase profitability by hiring an almost infinite number of ‘assistants’ and even workers at relatively zero cost” says Torrance.
For example, recently, Nvidia CEO Jensen Huang shared his vision of a future where, by roughly 2030, his company employs 50,000 human workers (up from 30,000 today) aided by 100 million ‘AI assistants’, notes Torrance. “In terms of ‘AI agents or ‘digital co-workers’ undertaking knowledge worker tasks end-to-end either independently or as parts of hybrid human-digital teams I would say that Nvidia could increase its ‘workforce’ (humans + digital) by 50%. So, by 2030, it might have 50,000 human workers, 25,000 digital workers (autonomous agentic workers) and 100 million AI assistants. That’s for a super tech company. Normal companies could perhaps increase their ‘headcount’ by 10 or 20%, without incurring the costs associated with human employees.”
“The digital Agentic workers are often better than human workers because they are not constrained by human biases about what’s possible or not, and when you give them a task they can keep going, they don’t need to take time to take lunch, drive home or sleep,” says Torrance. “What is key here is that we are not talking about single agents doing one thing. These workers are not assistants for humans. Agentic AI is made up of a diverse set of workers that can collaborate to get things done.”
Agentic AI will have a big impact on enterprise because it directly impacts three of the foundational pillars of a corporate’s competitive advantage: operational efficiency, scalability, and agility in decision-making, says Torrance.
Gartner predicts by 2028, 33% of enterprise software applications will include Agentic AI, up from less than 1% in 2024, enabling 15% of day-to-day work decisions to be made autonomously. The firm has named it a top strategic technology trend in 2025.
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