As artificial intelligence (AI) continues to revolutionize industries, startups are rapidly integrating AI tools into their operations. In the Startup Snapshot report 66% of startup executives reported that GenAI has significantly accelerated their startup’s operations, enabling them to deliver products and solutions more rapidly.
However, this fast-paced adoption often outpaces the development of robust AI policies, exposing companies to legal, ethical, and operational risks. To understand how startups can navigate this challenge, we sat down with legal experts Netanella Treistman and Roy Keidar, partners at Arnon Tadmor Levy, a law firm specializing in privacy, commercial, and emerging technologies law.
Why Should Startups Establish an AI Policy Early?
One of the best things a startup can do is think about AI policies early on. When companies proactively integrate AI and regulatory requirements into their product development, they position themselves for long-term success. If they wait too long, the complexity of implementing policies grows exponentially as they scale.
Startups tend to focus on the most immediate challenges, leaving AI concerns for later. However, this approach can backfire. Investors and clients increasingly conduct due diligence, including AI-related questions, during funding rounds and commercial negotiations. Without clear policies in place, startups may find themselves scrambling to comply with legal and contractual obligations at critical moments.
AI policies play a dual role: managing third-party AI tool usage and governing AI product development. If employees are using external AI tools, startups need a structured vendor onboarding process. They must document what AI tools are being used, what data is being inputted, and whether they own the rights to AI-generated outputs.
For startups developing AI models, the AI policy must cover key areas such as data sources, bias mitigation, transparency, and explainability. Jurisdictions worldwide, including the EU AI Act, are setting regulatory standards, making AI policies an essential component of compliance and risk management.
What Are the Risks of Neglecting an AI Policy?
A lack of AI policies can lead to significant risks, especially as a startup grows. Three major risks stand out:
- Intellectual Property (IP) Issues: If a startup uses third-party AI tools, there’s a risk that the generated content may not be owned by the company, potentially compromising its IP rights. For example, using AI-generated code from open-source platforms without proper licensing can create legal vulnerabilities.
- Privacy and Data Security Concerns: Startups handle sensitive data from employees, clients, and partners. If AI tools process personal data without proper safeguards, the company could face regulatory penalties and loss of trust.
- Regulatory and Compliance Risks: Even if a startup isn’t directly operating in a regulated jurisdiction, their clients might be. Many financial and healthcare organizations now require AI governance clauses in contracts, meaning startups must demonstrate compliance with industry best practices to secure partnerships
Final Thoughts
Startups thrive on agility and rapid innovation, but failing to address AI governance can create significant hurdles down the line. By establishing an AI policy early and ensuring it evolves with regulatory and business changes, startups can strike the right balance between innovation and risk management. As AI adoption grows, those who proactively integrate AI governance will be better positioned for long-term success.
For startups looking to implement an AI policy, consulting legal professionals with expertise in AI, data privacy, and technology law is essential. Netanella Treistman‘s insights highlight the importance of early-stage planning, risk mitigation, and regulatory foresight in building sustainable AI-driven businesses.
