AI-Native Services Firms: Sell the Work, Not the Software

Think about how a growing business handles its accounts. It pays a modest subscription for accounting software, then pays far more for the accountants who actually use it to close the books each month. For the last twenty years, technology companies have competed for the smaller of those two budgets.

A new kind of company is going after the larger one. It does not sell the software. It simply closes the books.

This is the idea behind AI-native services firms. This article explains what they are, why they matter and how Avesta AgentOS helps services firms make the shift.

What is an AI-native services firm?

An AI-native services firm delivers a finished service, such as a settled insurance claim, a drafted contract, a completed tax return or a resolved customer query. AI agents do most of the work. Qualified people review it, approve it and stay accountable for the result.

The client does not learn a new tool. They simply get the work done, usually faster, more consistently and at a lower price.

How it differs from what came before

	Traditional services	Software (SaaS)	AI-native services
What the client buys	Work done by people	A tool their own team uses	Work done, mostly by AI
Who does the work	The firm's staff	The client's staff	AI agents, supervised by experts
How the client pays	Per hour or per person	Per user, per month	Per outcome delivered
How the business grows	Hire more people	Sell more licences	Add more computing, not more headcount

There was also a step in between, often called "tech-enabled services". Online platforms made it easier to find, book and pay for services such as legal documents or tax filing. But behind the website, people still did the work in the same way, so the cost of delivering it barely changed. AI-native firms are different because AI changes how the work itself gets done.

Why this matters now

The opportunity is much larger than software. Business and professional services make up about 13% of US GDP, roughly ten times the size of the software market. For every dollar spent on software, about six are spent on services. AI-native firms compete for the labour budget, not the IT budget.

The technology has also caught up. AI can now read messy documents such as scanned forms, tables and handwriting, work through the same screens and systems people use, and complete tasks that take hours rather than seconds. On standard computer tasks, AI agents improved from about 35% success to about 85% in just over a year, above the 72% human baseline.

Three characteristics of an AI-native services firm

1. Focused on outcomes

The product is the result, and the price follows it. This is already happening: Intercom charges $0.99 for each customer query its AI resolves, and EvenUp charges per legal demand package it prepares. Clients can compare the price directly with what they pay a person or firm today, so the value is easy to see.

This also gives new firms an advantage over incumbents. Traditional firms are paid for hours worked, so they have little reason to finish faster. Software vendors charge per user, so they lose revenue when AI reduces the number of users. AI-native firms have neither problem. They earn more when they deliver more.

2. Built on software economics

A traditional services firm grows by hiring. Over ten years, one of India's largest IT services firms doubled its revenue from $15 billion to $30 billion, but nearly doubled its headcount too, so revenue per employee stayed flat.

In an AI-native firm, each extra piece of work mainly costs computing power, not another salary. That allows the firm to grow faster than its headcount and move towards the healthy margins of a software company.

3. Compounding intelligence

Every job the firm completes, and every correction an expert makes, can be used to make the system better. Over time, the firm builds knowledge about how good work is done in its field, and competitors cannot easily copy that.

Improvements in AI models also work in the firm's favour. A company selling an AI tool has to worry that the next model release will turn its product into a standard feature. A company selling the work simply gets faster and cheaper with every improvement.

Where it is already working

Early success is in work that is high volume, follows clear rules and is often already outsourced:

• Legal: preparing demand packages, drafting NDAs and standard contracts. Examples include EvenUp and Crosby.
• Healthcare billing: medical coding and handling insurance denials, which follow complex but clear rules. Examples include SmarterDx and Anterior.
• Insurance: claims handling and third-party administration. Examples include Reserv and Strala.
• Accounting and tax: bookkeeping, month-end close and tax preparation. Demand is rising while the US has lost roughly 340,000 accountants in five years. Examples include Rillet and Basis.
• Customer support and outsourcing: resolving customer queries in the $300 billion business process outsourcing industry. Examples include Decagon.
• IT services: monitoring, support tickets and routine maintenance for businesses that already outsource IT.

Work that is already outsourced is the easiest place to start. The client already has a budget, already buys an outcome, and moving to a better provider is a simple change of vendor rather than a restructure.

The catch: services firms now need a serious technology platform

Delivering outcomes with AI is not the same as using a chatbot. To take responsibility for real client work, a firm needs:

• Many AI agents working together across a complete process
• Access to the right business knowledge and client systems
• Rules that stop agents from doing things they should not do
• Clear points where a person must review or approve
• Testing before clients see anything, and monitoring afterwards
• A full record of what each agent did and why
• A clear view of the cost of every outcome delivered

Building this takes a large engineering team and a lot of time. The people best placed to launch AI-native firms, such as lawyers, accountants, claims specialists and operations leaders, know the work deeply but are not in the business of building technology platforms. The same is true for established firms that want to move from billable hours to outcomes.

How Avesta AgentOS helps

Avesta AgentOS is a multi-agent orchestration platform for automating business operations end to end, with people in control. You bring the expertise and the clients. We bring the platform.

• Run the whole service, not just one task. Teams of AI agents work together across customer service, operations, finance, compliance and more.
• Keep people in control. You decide what an agent can do on its own, what needs approval and when an issue must be escalated. Start with experts approving everything, then hand over more as trust grows.
• Use your business knowledge. AgentOS connects to your CRM, ERP, support desk, databases and documents, including PDFs, images and other files.
• Prove quality before clients see it. Built-in evaluation tests agents against realistic scenarios, and MetricSense tracks accuracy and behaviour in production.
• Protect your margins. AgentOS chooses the right AI model for each task across leading providers and tracks the cost of every outcome.
• Earn client trust. Role-based access, guardrails and a full audit trail show what was done, by which agent, and who approved it.
• Reach clients where they are. Deliver through a dashboard, a website widget, WhatsApp or directly into client systems.

The platform handles the technology. Your firm's expertise, processes and client relationships remain what sets you apart.

AgentOS is a fit for:

• Founders launching a new AI-native services firm
• Established firms in accounting, legal, insurance, outsourcing or IT services moving from billable hours to outcome-based services
• Groups acquiring several services businesses that need one platform to modernise all of them

Getting started

The best first step is small and specific. Choose one high-volume service your clients already outsource, define the outcome you will price, and decide where a person must stay involved.

Our AI Kickoff does exactly this. It starts with a three-day value discovery workshop, followed by a four-week pilot on AgentOS and a plan for production. From there, Safe AgentOps helps you run the service reliably as it grows.

The firms that win this shift will not be the ones with the biggest technology teams. They will be the ones that know the work best and deliver it better, faster and more reliably than anyone else.

References

• Bessemer Venture Partners, Building Vertical AI: An early stage playbook for founders
• Bessemer Venture Partners, Owning the outcome: Bessemer's AI-Native Services evaluation framework
• Bessemer Venture Partners, Part III: Business model invention in the AI era
• Bessemer Venture Partners, Roadmap: Reinventing IT services in the age of AI
• Sequoia Capital, Services: The New Software
• Andreessen Horowitz, How AI Is Unbundling the $300 Billion BPO Industry