{"url_path":"/sec/idt/10-q/2026/item-1a","section_key":"item-1a","section_title":"Item 1A ****Risk","topic":"sec","document":{"doc_type":"10-Q","doc_date":"2026-03-12","source_url":"https://www.sec.gov/Archives/edgar/data/1005731/0001493152-26-009820-index.html","accession_number":"0001493152-26-009820","cik":"0001005731","ticker":"IDT","issuer_name":"IDT CORP","edgar_url":"https://www.sec.gov/Archives/edgar/data/1005731/0001493152-26-009820-index.html","primary_entity_key":"0001005731","primary_entity_name":"IDT CORP"},"word_count":1051,"has_tables":true,"body_markdown":"**Item\n1A.****Risk\nFactors**\n\n \n\nImportant\nrisk factors that could affect our operations and financial performance, or that could cause results or events to differ from current\nexpectations, are described in “Part I, Item 1A – Risk Factors” to the 2025 Form 10-K, as supplemented by the information set forth below:\n\n \n\n*An\nemerging component of our growth strategy involves the adoption, integration, and effective utilization of AI technologies across our\nproducts, services, and internal operations, which introduces significant and evolving risks.*\n\n \n\nWe\ncurrently incorporate AI into certain existing and planned products, as well as our internal operations. For example, some of our marketing,\ncustomer service and anti-fraud efforts are currently enhanced by AI. Further, our internal technology development efforts are utilizing\nAI in expanding ways, and other internal operational functions are beginning to use AI to improve effectiveness and efficiency. Achieving\nconsistent, secure, and compliant AI adoption across departments—including Product & Engineering, Marketing, Trust & Safety,\nCustomer Support, Finance, and Legal/Compliance—requires ongoing investment in training, governance, and change management. Failure\nby any function to adopt or appropriately use these tools or failure to monitor and control the results of the adoption of the tools\ncould reduce profitability, productivity, impair product quality, or cause compliance or security issues.\n\n \n\nAI\ntechnologies are complex, resource-intensive, and rapidly evolving. Market demand and acceptance of AI-driven customer-facing offerings,\nsuch as n2p AI Agent and n2p Coach AI, remain uncertain, and our product development efforts may not achieve widespread adoption or may\nbe outpaced by competitors. Competitors with greater financial, technical, data, or distribution resources may gain an advantage in attracting\nand retaining AI talent and in acquiring training data and compute capacity, which could impair our ability to maintain competitive AI\ncapabilities. If our AI solutions, or those of others in our industry, draw controversy due to their perceived or actual societal impact—such\nas generating biased, harmful, or misleading content—we may experience brand or reputational harm, competitive harm, or legal liability,\nwhich could slow user adoption of our products.\n\n \n\nThe\nuse of AI also raises ethical, reputational, and legal concerns. AI-based or AI-enhanced systems can generate or amplify content that\nis inaccurate, misleading, biased, discriminatory, harmful, or otherwise controversial, or be misused by third parties. If our AI tools\nproduce, or are perceived to produce, such outputs, or if we fail to implement adequate human oversight, testing, and safeguards (including\ndata governance, evaluation, and post-deployment monitoring), our brand and competitive standing could be harmed and we could face complaints,\ninvestigations, or litigation. Potential litigation or government regulation related to AI may increase the burden and cost of research\nand development, further subjecting us to reputational harm, competitive harm, or legal liability. Failure to address perceived or actual\ntechnical, legal, compliance, privacy, security, or ethical issues could undermine public confidence in AI, slowing customer adoption\nof our AI-driven products and services.\n\n \n\nLaws\nand regulations focused on the development, use, and provision of AI technologies and other digital products and services are proliferating\nin many jurisdictions around the world. Staying compliant with evolving laws, regulations, and industry standards pertaining to AI may\nimpose significant operational costs and constrain our ability to develop, deploy, or employ AI technologies profitably or at all. Failing\nto adapt appropriately to this evolving regulatory environment could result in legal liability, regulatory actions, monetary penalties\nand damage to our brand and reputation.\n\n \n\nOperationally,\nAI models depend on the quality, provenance, and security of data and on reliable third-party infrastructure. Inadequate, outdated, biased,\nor compromised datasets can produce flawed outputs and “model drift.” Our reliance on third-party models, APIs, datasets,\nand cloud providers exposes us to outages, cost volatility, performance degradation, or changes in licensing or acceptable-use terms,\nwhich could disrupt our operations if these services become unavailable or are no longer offered on commercially reasonable terms.\n\n \n\nIntegrating\nAI introduces new cybersecurity risks, including prompt-injection, data exfiltration, model poisoning, and supply-chain vulnerabilities,\nas well as the risk that employees inadvertently input confidential or personal data into external systems.\n\n \n\nIntellectual\nproperty ownership surrounding AI technologies has not been fully addressed by U.S. or foreign courts or federal, state or foreign laws,\nnor by international legal frameworks. Our ongoing development and use of generative AI tools may result in copyright infringement claims,\ndisputes over ownership and licensing, and potential patent infringement claims, among other things. These legal challenges could be\ncostly to defend against, leading to substantial financial obligations and reputational damage. The evolving regulatory environment and\nuncertain legal precedents in this field further increase our exposure to litigation risks, which could materially affect our business,\nfinancial condition, and results of operations.\n\n \n\n36\n\n \n\n \n\nAdditionally,\nlaws and regulations focused on the development and use of AI are proliferating globally and continue to evolve (for example, comprehensive\nAI frameworks in the EU and emerging federal and state guidance in the United States). Compliance may require significant documentation,\ntransparency and record-keeping, risk assessments, model governance, content provenance or watermarking, impact assessments, vendor oversight,\nand restrictions on certain use cases. Noncompliance could result in investigations, fines, injunctions, remediation obligations, or\nother sanctions. Cross-border data transfer rules, sanctions, and export controls may affect access to datasets, models, or compute resources\nin some jurisdictions.\n\n \n\nFurther,\nour use of generative AI in aspects of our platforms may present risks and challenges that could increase as AI solutions become more\nprevalent. AI algorithms may be flawed. Datasets may be insufficient or contain biased information. These deficiencies and other failures\nof AI systems could have negative impacts on our users’ experience and subject us to competitive harm, regulatory action, legal\nliability, and brand or reputational harm. Contractual indemnities from vendors may be unavailable or insufficient. We may also face\nclaims related to privacy (including the processing of personal or biometric information), publicity rights, deceptive practices, or\ncontent moderation failures. Defending such claims can be costly and time-consuming, could require changes to our products or processes,\nand could harm our reputation and financial results.\n\n \n\nFinally,\nAI-related development and inference can increase energy consumption and costs, and investor or regulatory focus on sustainability may\nimpose additional constraints. If we fail to implement robust AI governance, align employee practices with our policies, maintain sufficient\nhuman oversight, and continuously evaluate and improve our systems, the risks described above could materially and adversely affect our\nbusiness, financial condition, results of operations, and reputation."}