The process of artificial intelligence development can entail a significant number of costs related to employee labour, computing infrastructure, and software. The ability to track expenses is critical for claiming Scientific Research and Experimental Development (SR&ED) tax incentives in Canada as it will enable a company to assess expenditures associated with experimental work. This procedure should happen simultaneously with development to ensure that every expense is accounted for and there are no misunderstandings regarding its nature. Simultaneously, it might be informative for a firm to assess how much money it will need to devote to specific undertakings to find solutions to technological bottlenecks.
Identifying Eligible Development Activities
Since artificial intelligence (AI) development can include a range of different undertakings, it is advisable to separate experimental work from other activities. Efforts to conduct trials and come up with a workable solution through iteration and analysis can be viewed as experimental research and development as long as certain conditions are met. The remainder of a firm’s AI development efforts should be classified as non-qualifying work, including activities that do not involve technological uncertainties or systematic methods. It is essential to note down the specifics of each type of work to ensure the appropriateness of the category and its relevance to eligible research and development.
Establishing Project Boundaries
It is also important to outline the perimeters of the projects and tasks to help classify further expenses. In relation to AI development, it is helpful to break down the effort and expenditures needed to conduct data labelling, test the created models, experiment with the architecture, and implement the developed application in production. In turn, the company will be able to identify the activities that might need to be eligible for subsidies. Moreover, it becomes possible to prepare more comprehensive project documentation outlining the rationale behind the created solution, sources of technological uncertainties, and methods that have been analyzed. Notably, defining the perimeters of the projects aids firms in reducing the need to identify them at the stage of a claim.
Tracking Employee Time and Labour Costs
The most common expenses that AI development firms encounter include labour costs, infrastructure, and software. From these, tracking the time spent by employees can be both useful and complicated. Ideally, a firm should invest in an appropriate time-tracking tool that allows its IT team to allocate specific hours to each project and activity. It is better to specify what exactly was being done by which employee(s). For example, a research group working on finding the most stable AI architecture might document that someone spent 20 hours testing the models’ accuracy instead of using general concepts like ‘development’.
Connecting Financial Records With Technical Evidence
By completing previous steps, a firm will build the backbone of its eligibility documentation for SR&ED tax incentives. A firm looking for more opportunities to strengthen its claim for eligibility subsidies could consider SR&ED consulting. At this stage, it is essential to review these records and ensure that they support the information concerning specific, qualifying experiments a company conducts.
For instance, it might be important to keep additional notes that explain what exactly was attempted with reference to a specific project goal. This information will become crucial when it comes to explaining how exactly the firm has allocated its monetary resources, namely, to which degree such expenditures were related to qualifying research and development efforts. Crucially, it is necessary to provide consistent and traceable project-specific information on all expenses, for example, by using the same label for invoices and time logs.
Maintaining Supporting Employment Records
In this step, the mentioned time logs are supported by additional employment documents, including the staff’s contract, payroll, description of positions, and other papers that confirm the hours, salary, and overall status of the workers. The most complex situations occur when employees work on other tasks during the same time and there is a need to specify how much effort was devoted to AI experimental projects. In this case, it is critical to utilise the documentation tool for allocating a proportionate amount of time and labour for each activity based on an objective standard. At the same time, managers and specialists will have opportunities to correct the inaccuracies while there is still time. As will be seen during the claim process, it becomes much easier to track this particular category of expenditures.
Documenting AI Infrastructure Costs
Since AI development often requires extensive training of intricate models, much of a firm’s spending in this area will likely be infrastructural. In this case, it is essential to keep the corresponding invoices and documents that evidence the amount of resources utilized, namely, cloud storage and processing power, additional computers and equipment, or any other items that the company has invested in to improve its operations. If such infrastructure is used for multiple purposes, another firm-generated standard applies, one that specifies the proportion of time, cost, or other resources. At the time of calculating the claim, it will make it easier to review each invoice and compare it to the AI project details specified earlier instead of considering all infrastructural costs as eligible for subsidies.
Reviewing Software and Data Expenditures
Finally, it is necessary to list software and related expenses since AI development requires several tools apart from cloud storage and processing facilities. Subscriptions, costs for data labelling and processing, and expenses for external resources and products are some of the examples of items that a firm can consider. Once again, there must be documentation that supports the relevance of this category of expenditures for the current projects. Crucially, such an assumption does not automatically entitle a firm to receive subsidies; rather, it helps a company understand how its expenses fit into the existing parameters of the SR&ED program. It is advisable to keep these costs and infrastructure expenses separated and document every detail to avoid incorporating irrelevant items.
Reviewing Records Throughout Development
A separate team of auditors and project managers should have the opportunity to review expenditures in tandem with experiments since this procedure will enable them to understand how the project has allocated its resources at present.
By analysing the firm’s documentation, a SR&ED consultant will be able to confirm or deny its eligibility. At the same time, they can advise on the potential scope of the SR&ED claim and the relevance of certain categories of expenditures. In this way, a consultant will be in a better position to evaluate qualifying work and align expenditures accordingly.
Conclusion
Keeping an accurate track of how much it costs to develop new AI is essential. It makes it possible to prepare a reliable SR&ED claim. To do that, the company should record all the financial inputs and expenditures regularly. Moreover, the business should document all the relevant research and experimental efforts and make sure that they match the expenses to get proper tax benefits.
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