For venture investors, companies adopting LLMs have brought renewed attention to previously overlooked sectors, recasting them as prime targets for opportunity. As we continue to see capital pouring into AI-driven startups, we’re witnessing the emergence of what we call “Service as Software.” This model blends AI automation with human expertise to create scalable, high-margin service businesses poised to disrupt traditional service providers and capture investors’ attention.
Historically, venture investors have sought higher margins than those typical of service-based businesses.
In the past, service-based businesses such as law, accounting, and consulting firms have not commonly raised much venture funding due to their capital-intensive nature. These companies relied heavily on human capital, often needing to add more people to scale, which resulted in lower profit margins that paled in comparison to SaaS businesses. The same is true of managed services in spaces like information technology (IT), cybersecurity, and software implementation. Although managed service providers successfully blend software and labor to provide their services, they still fail to improve their financial profiles to resemble highly attractive SaaS metrics and often require significant capital to scale. Characterized by billable-hours business models and repetitive workflows, these businesses struggled to achieve the growth and profitability that venture investors seek.
GenAI transforms service businesses into exciting opportunities.
The advent of GenAI is dramatically changing this landscape. Repetitive workflows that involve document handling, unstructured data usage, manual tasks, and analytical decisions are now prime candidates for automation. While previous attempts at automating services through Robotic Process Automation (RPA) and legacy vertical software companies have made some headway in driving efficiency for service-based sectors, GenAI is already delivering a level of automation that was previously unattainable. Software used to digitize and enhance human work and services, but with GenAI, software is now taking on the role of decision-makers.
We’ve already started to see how AI is impacting the delivery of services:
- Law firms are now using vertical generative AI applications like Spellbook and Casetext for more efficient contract review, due diligence, and legal research.
- Accounting firms are leveraging companies such as Materia for faster and more efficient delivery of their services by augmenting accountants with tools that automate tasks.
- Solopreneurs are using Collective (an Ardent portco) for AI-powered bookkeepers and accountants instead of using tools like Quickbooks, reducing the time and cost it takes to manage their books.
- Outsourced software development firms are currently using co-pilots and will soon be able to use platforms like Opendevin and Codeium for autonomous software development, bug detection, and testing to lower their COGS.
As various new workflows become automated, the financial profiles of service providers will transform, becoming much more attractive to venture investors. We’ll see higher profit margins and the potential to scale upwards without adding significant headcount.
“Service-as-software”
In the future, nearly all service-based businesses that rely on knowledge workers will leverage both AI and software, as well as human expertise to provide services at scale. Their business models will shift from hourly billings to subscription models.
We see two paths to creating these next-generation service providers:
- De novo AI-first companies will be built from the ground up with savvy talent that is equipped to produce services in tandem with automated workflows. While they must win customers from established players, they have the advantage of a clean slate to implement AI-driven processes fully with lean teams and little tech debt.
- Roll-ups of existing firms, on the other hand, provide an existing client base but will require significant change management to retrain staff and restructure operations. Industries that are heavily fragmented, such as accounting or legal services, are ripe for this strategy.
Looking Ahead
This transformation will not happen overnight. We are still in the early stages of generative AI adoption by the enterprise, just starting to see it deployed around the edges of the business and focused primarily on individual worker productivity. Organizations will face significant challenges when transforming core workflows and business processes to those that are AI-enabled as they will require significant amount of trial and error to fully re-imagine.
With new efficiency gains, some companies may keep pricing the same as they have and simply deliver more services to more clients. Others might decide to pass some of the cost savings on to customers. Nonetheless, as they gain traction, we anticipate seeing many new service providers focus solely on delivering the newly automated services. For example, imagine a legal tech startup that specializes in only research-heavy, hyper-specific litigation cases and leverages GenAI to find similar and relevant precedents.
Meanwhile, traditional service providers that remain will likely specialize in workflows that cannot be easily automated, such as high-level, client-facing work or complex problem-solving. These firms will likely outsource more routine tasks to AI-powered specialty tools.
It is evident that the puck is moving this way for service firms. All firms will use GenAI, everyone is thinking about this. As investors, we spend a lot of time thinking about who and what it will take to be the breakout company. What will be that key success factor?
At Ardent, we’re excited about the potential of AI-powered service-as-software business models. We’re actively seeking startups building anew in this space and invite entrepreneurs with innovative ideas in this realm to reach out.
