In a Teams-as-a-Service (TaaS) model, AI can autonomously initiate, organize, execute, and review tasks. This marks a significant shift from the traditional Software-as-a-Service (SaaS) model.
While SaaS enables businesses to streamline functions such as marketing, sales, procurement, accounting, etc., it still requires a trained workforce to run the software.
Teams-as-a-Service, distinct from traditional outsourcing, refers to AI applications that are deeply integrated into organizational workflows and fine-tuned to perform specific tasks with precision.
This model allows AI to substitute human-centric functions with ‘intelligent’ software.
AI vs. Human Labor in the Knowledge Economy
The SaaS model gained widespread adoption due to its undeniable advantages: scalability, accessibility, flexibility, and multi-layered integrations that lower operating costs while increasing productivity and efficiency.
Despite the SaaS industry having clocked double-digit growth for many years, knowledge workers still constitute more than 40% of the total workforce in the U.S.
Yes, SaaS spending is significant. But, expenditure on human capital is much higher.
While U.S. businesses spend nearly $230 billion on SaaS, the expenditure on the knowledge workforce is substantially higher at about $5 trillion.
With AI, software has the potential to extend beyond merely streamlining tasks, partially automating processes, anticipating redundancies, or fostering collaboration.
It can potentially complete tasks from start to finish without requiring any supervision by the human labor.
So, the gap between the actual labor and AI-powered software functioning like labor is likely to be reduced.
Margin Expansion in the Service Sector
Successful SaaS companies typically operate with high gross margins, ranging from 75% to 90%. In contrast, U.S. service businesses have gross margins of approximately 33%.
This margin disparity presents an opportunity for a new AI worker—Teams-as-a-Service—to harness.
Service businesses could potentially increase their gross margins with TaaS AI and align more closely with the higher margins seen in the SaaS industry.
Where Teams-as-a-Service Can Excel
The Teams-as-a-Service model can thrive in business scenarios where the cost of recruiting human labor or subcontracting business functions far exceeds the cost of using AI.
TaaS can be particularly advantageous in sectors where:
- Repetitive tasks can be automated
- Human labor is expensive and impacts profit margins
- Industries experience high turnover
- Business functions are fragmented
- There is ample proprietary data to train a TaaS solution
Unit economics can further favor the Teams-as-a-Service model because it offers personalization, 24/7 availability, and the ability to eliminate fragmentation by consolidating various functions across different job roles and tools.
For instance, businesses that use Lilo no longer need to hire dedicated procurement consultants because this expertise is built into the platform. They also don’t require an extensive procurement department to manage supplier evaluation, contract negotiations, demand forecasting, purchase order approvals, reordering, expenditure analysis, and more. The result? Businesses save up to 30% on purchase costs and 80% on the time spent ordering supplies, thanks to AI-powered workflows and tools that function seamlessly in a team environment.
With the TaaS AI model, businesses can potentially expand their AI workforce and scale operations without having to proportionally increase capital or operational costs—all at the click of a button.
As seen in the hospitality industry and other sectors, AI won’t completely replace human labor; the disruption brought by AI, whether through TaaS or other models, may create entirely new roles and lead to a fusion of AI and human workforces.
In any case, the day when AI works independently in a collaborative environment, whether as an individual worker (focused on a single function) or as a team (performing a set of tasks), is not far off.