Company: TEM
Filing Date: 2025-02-24
Form Type: 10-K
Source: 0000950170-25-025603
Chunk: 186

Company: Tempus AI, Inc.
Filing Date: 2025-02-24
Form: 10-K
Item: Item 1
Chunk 186
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 such incidents or to estimate the amounts or ranges of potential loss, if any, that could result therefrom. If we cannot successfully resolve a security incident or contain any potential loss, it could materially impact our business, financial condition and results of operations. 

In addition to experiencing a security incident, third parties may gather, collect, or infer sensitive information about us from public sources, data brokers, or other means that reveals competitively sensitive details about our organization and could be used to undermine our competitive advantage or market position. Additionally, sensitive information of the Company or our customers could be leaked, disclosed, or revealed as a result of or in connection with our employees’, personnel’s, or vendors’ use of generative AI technologies. Any sensitive information (including confidential, competitive, proprietary, or personal data) that we input into a third-party generative AI/machine learning platform could be leaked or disclosed to others, including if sensitive information is used to train the third parties’ AI/machine learning model. Additionally, where an AI/machine learning model ingests personal data and makes connections using such data, those technologies may reveal other personal or sensitive information generated by the model. Moreover, AI/machine learning models may create flawed, incomplete, or inaccurate outputs, some of which may appear correct. This may happen if the inputs that the model relied on were inaccurate, incomplete or flawed (including if a bad actor “poisons” the AI/machine learning with bad inputs or logic), or if the logic of the AI/machine learning is flawed (a so-called “hallucination”). We may use AI/machine learning outputs to make certain decisions. Due to these potential inaccuracies or flaws, the model could be biased and could lead us to make decisions that could bias certain individuals (or classes of individuals), and adversely impact their rights, employment, and ability to obtain certain pricing, products, services, or benefits. If such AI/machine learning-based outputs are deemed to be biased, we could face adverse consequences, including exposure to reputational and competitive harm, customer loss, and legal liability. 

Item 1B. Unresolved Staff Comments.

None.

Item 1C. Cybersecurity. Risk Management and StrategyOur business depends on our continued ability to collect and safeguard vast amounts of personal and sensitive business information, including, among other types of data, protected health information (PHI), employee information, credit card information, insurance information, proprietary and confidential information about our business, financial information, trade secrets, intellectual property, and the sensitive and