Should Firms Outsource AI Agent Development? Incentives, Risk and Switching Costs

Outsourcing AI agent development makes sense when a firm lacks the specialist skills in-house and can manage the information gaps, incentive problems and switching costs that come with hiring an outside developer. AI agents are moving quickly from trial to everyday use, and the sums involved can be large. Economics helps firms choose between building and buying and shows how to structure the contract if they buy.

When Should Firms Outsource AI Agent Development?

An AI agent is software that does more than answer questions. It works towards a goal by deciding which steps to take, using other business systems and checking the results. Building one requires skills in data preparation, model configuration, system integration and testing that many firms do not have in-house.

Economists frame this as a make-or-buy choice. A firm keeps an activity inside the organisation when that is cheaper than buying it in the market. When a project requires only one agent, it may make much more sense to hire an outside developer because an outside developer works with multiple clients. Conversely, if a company plans to deploy many agents over several years, building them in-house may become more cost-effective.

How to Choose an AI Agent Development Company

The market for AI agent services is crowded, and quality is hard to see before a contract is signed. Gartner estimated in June 2025 that only about 130 of the thousands of agentic AI vendors are real. It warned that many vendors were rebranding chatbots and simple automation tools as agents.

This is a case of asymmetric information: the vendor knows far more about its own capabilities than the buyer does. If buyers cannot tell strong providers from weak ones, they may be unwilling to pay for quality, which makes the market less attractive to the best developers.

Vendors can narrow the gap by signalling, through case studies, references from live deployments and a clear account of each phase of work. A buyer comparing proposals can then ask what an AI agent development company service actually includes, from discovery and data checks to testing and monitoring, rather than relying on the label alone.

AI Development Contracts and the Principal-Agent Problem

When a business hires a developer, it becomes the principal, and the developer is its agent. The principal-agent problem arises because the two may want different things. A developer paid by the hour has little reason to finish quickly, while one paid a fixed fee may cut corners on testing, which the buyer cannot easily observe.

Defining payments around anticipated results and setting clear guidelines for when an AI agent can act independently rather than refer decisions to a human can simplify the monitoring of developers' activities.

Reducing AI Project Risk: Proof of Concept and Sunk Costs

Money spent on a failed project cannot be recovered. Economists call this a sunk cost and warn against continuing a project simply because so much has already been spent. The risk is real: in the same release, Gartner predicted that over 40% of agentic AI projects will be cancelled by the end of 2027, citing rising costs, unclear business value and weak risk controls.

Splitting the work into stages limits that exposure. A proof of concept is a small test to determine whether an agent can perform the task before the firm commits to building the entire system. Each step is treated as an option; pay some money to find out more and continue only if the results warrant additional investment.

How Much Does an AI Agent Cost to Run?

Unlike most traditional software, an AI agent can cost money every time it runs, because each task uses model processing that providers charge for. The marginal cost of an agent, the extra cost of completing one more task, therefore matters as much as the build price.

When agents process supplier invoices, a useful cost comparison can be made between the cost per invoice processed by the agent and the cost per invoice handled by the staff. Proposals that only include the development fee leave out a growing cost based on the volume of processed invoices.

How to Avoid Vendor Lock-In and High Switching Costs

Once an agent is connected to a firm’s systems, changing the developer or model provider can be expensive. Staff have been trained, integrations built and data organised around one design. This creates vendor lock-in, which weakens the buyer’s bargaining position when contracts come up for renewal.

Firms can reduce switching costs by asking for full documentation, ownership of the code and a design that can work with more than one model provider. While initial expense may be raised due to certifications, certification provides suppliers with greater opportunity or chance to compete; therefore, if the anticipated value will be realised at a future point in time, then yes, it could be a positive benefit to the company using this model.