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Driving Startup Growth Through Artificial Intelligence
Artificial Intelligence (AI) technologies are rapidly advancing, but the high compliance costs have become a significant financial burden for AI startups. These start-ups already operate on tight research & development (R&D) budgets and face complex regulatory processes that vary across the globe. As a result, well-established technology firms have an advantage over resource-constrained start-ups, potentially leading to a monopoly on AI technologies. In this article, we will explore how compliance costs hinder start-ups’ ability to compete with larger tech firms in AI commercial operations.
Financial Vulnerability
Compliance costs have a significant impact on start-ups’ operating margins, unlike tech giants. A financial statement simulation reveals that start-ups are more vulnerable to compliance costs, with their operating margin dramatically affected when compliance costs increase. On the other hand, tech giants experience only a minor dip in their operating margin under similar circumstances. Furthermore, compliance costs may be hidden in financial reports, leading to underestimations of the true costs. Current estimates of AI compliance costs are often insufficient due to the concealment of these costs.
The Compliance Trap
The lack of a standardized AI regulation framework creates challenges for start-ups. Unlike R&D budgeting, there is no standard method to budget for AI compliance costs due to varying regulatory frameworks across the globe. Even with an AI compliance budget, the actual costs may deviate significantly from the budget as start-ups encounter new compliance issues during the commercialization process. Additionally, varying AI regulations introduce indirect costs, such as engineers spending time on regulatory issues instead of product development.
A Field Deployment Perspective
To gain a deeper understanding of compliance costs, we examine the experience of PerceptIn, an AI start-up in the autonomous driving space. PerceptIn faced a range of regulatory obstacles in different countries, falling into the compliance trap. For example, in China, the company had to develop its own testing plan to obtain deployment approval due to the lack of relevant regulations. This resulted in significant costs for testing and demonstration purposes that were not included in the original budget.
Similarly, in Europe, PerceptIn was asked to prepare a risk mitigation plan for 40 different scenarios, which required a shift in focus for the R&D team and led to increased costs. In Japan, the company had to invest in marketing campaigns to gain the confidence of the regulatory body and accelerate autonomous driving operation permits. These examples highlight the additional compliance costs start-ups face when operating in different countries.
Deviation from Compliance Budget
The lack of a standardized AI regulatory framework makes it difficult for start-ups to budget for compliance costs accurately. Start-ups often encounter new compliance issues as they progress through commercialization, resulting in deviations from their initial compliance budget. Regulators’ inspection of AI products also introduces opportunity costs as delays in commercial deployments occur. These factors further contribute to the financial vulnerability of start-ups.
Indirect Costs
Varying AI regulations introduce indirect costs for start-ups. Engineers often have to shift their focus from product development to dealing with regulatory issues, such as responding to compliance technical inquiries. These costs are categorized as R&D costs in financial reports, making it difficult to accurately assess the impact of compliance costs on start-ups’ financial health.
Silver Linings
The lack of a standardized AI regulatory framework and the resulting compliance costs create challenges for start-ups. However, there are potential solutions to mitigate these challenges. One proposed solution is the adoption of a new business model called Compliance-as-a-Service (CaaS). CaaS specializes in dealing with varying AI regulatory frameworks and helps amortize compliance costs across different start-ups. By providing an interface to compile legal terms into technical and operational plans, CaaS reduces the friction between regulatory bodies and start-ups.
References
- Wu, W. and Liu, S., 2021. Dilemma of the Artificial Intelligence Regulatory Landscape.
- PricewaterhouseCoppers, 2022. Illustrative IFRS consolidated financial statements.
- Renda, A., Arroyo, J., Fanni, R., Laurer, M., Sipiczki, A., Yeung, T., Maridis, G., Fernandes, M., Endrodi, G. and Milio, S., 2021. Study to support an impact assessment of regulatory requirements for artificial intelligence in Europe. European Commission: Brussels, Belgium.
- Fukuoka City conducts demonstration test of compact self-driving car by US company PerceptIn, Inc.. Nikkei, accessed 2023-01-05.
- List of Proposal Sectors and Private Companies, etc. In Seeds proposal for realization of smart island. Japanese Ministry of Land, Infrastructure, Transport and Tourism, accessed 2023-01-05.
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