Earnings release
PNC results filing filed 15 Jul 2026
SEC EDGAR
Reporting period ended 15 Jul 2026
No explicit AI or machine-learning disclosure was found in this results document.
Results intelligence · Bank · North America
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PNC
PNC
A reporting-period timeline of the company’s AI and machine-learning disclosures, grounded in official investor materials and exact source excerpts.
Risk and governanceAI strategy
Reporting history
AI disclosures by reporting period
Documents with no explicit AI/ML evidence are shown as such. Silence is not interpreted as inactivity.
Primary source
Quarterly report
PNC quarterly report filed 5 May 2026
SEC EDGAR
Reporting period ended 31 Mar 2026
No explicit AI or machine-learning disclosure was found in this results document.
Earnings release
PNC results filing filed 15 Apr 2026
SEC EDGAR
Reporting period ended 15 Apr 2026
No explicit AI or machine-learning disclosure was found in this results document.
Annual report
PNC annual report filed 20 Feb 2026
SEC EDGAR
Reporting period ended 31 Dec 2025
PNC is continuing to invest in technology, including artificial intelligence and machine learning, to automate manual processes and enhance the customer experience. While AI and machine learning models are increasingly used for internal automation and customer engagement, they currently represent a minority of PNC's total models. The bank highlights that these technologies introduce complex risks, including reduced explainability, strict regulatory compliance demands, operational data dependencies, and increasingly sophisticated cyber threats powered by generative AI and deepfakes.
Risk and governanceExpanding
AI and machine learning models present interpretability and regulatory challenges
PNC is increasingly employing AI and machine learning algorithms for internal process automation and customer operations. Though these currently represent a minority of PNC's overall models, they are less interpretable than traditional models and face complex regulatory constraints across intellectual property, privacy, and consumer protection laws.
“Although it currently impacts a minority of the overall number of models that we use, we increasingly use models related to how we do business with customers and for internal process automation that leverage AI/machine learning algorithms. These models can be more predictive, but because of the complex way in which the many variables in AI/machine learning models interact, the results of these models are often less interpretable than traditional statistical models.”
Context: Risk Factors, PNC 2025 Form 10-K
AI strategyExpanding
PNC invests in artificial intelligence and machine learning to drive automation
PNC is expanding its technology investment in response to changing customer expectations and competitive pressures. The bank identifies the expanded use of artificial intelligence and machine learning as a key element of the rapid technological change occurring across the financial services industry.
“Examples include expanded use of cloud computing, artificial intelligence (AI) and machine learning, biometric authentication, voice and natural language, data privacy and security enhancements and increased online and mobile device interaction with customers, including innovative ways that customers can manage their accounts.”
Context: Risk Factors, PNC 2025 Form 10-K
Risk and governanceDirection not stated
Generative AI and deepfakes escalate cyber security threats
PNC warns that cyber attacks and security breaches targeting both the bank and its customers are growing rapidly in sophistication, driven specifically by malicious uses of generative AI and deepfakes.
“The techniques used in cyber attacks and breaches change rapidly and are increasingly sophisticated, including through the use of generative AI and deepfakes, and we expect in the future through the use of quantum computing, and we may not be able to anticipate cyber attacks or other data security breaches.”
Context: Risk Factors, PNC 2025 Form 10-K
Risk and governanceContinuing
Automation and AI mitigate human error but introduce data quality dependencies
PNC utilises machine learning, AI, and robotic process automation tools to decrease risks associated with human error. However, these systems depend heavily on high-quality training data, as poor or anomalous data can negatively impact their operations.
“We use automation, machine learning, AI and robotic process automation tools to help reduce some risks of human error.”
Context: Risk Factors, PNC 2025 Form 10-K
Earnings release
PNC results filing filed 16 Jan 2026
SEC EDGAR
Reporting period ended 16 Jan 2026
No explicit AI or machine-learning disclosure was found in this results document.
Earnings release
PNC results filing filed 7 Nov 2025
SEC EDGAR
Reporting period ended 7 Nov 2025
No explicit AI or machine-learning disclosure was found in this results document.
Quarterly report
PNC quarterly report filed 3 Nov 2025
SEC EDGAR
Reporting period ended 30 Sept 2025
No explicit AI or machine-learning disclosure was found in this results document.
Quarterly report
PNC quarterly report filed 1 Aug 2025
SEC EDGAR
Reporting period ended 30 Jun 2025
No explicit AI or machine-learning disclosure was found in this results document.