Teradata Accelerates AI Innovation with More than 150 Enterprise AI Engagements in 2025

Rhea-AI Summary

Teradata (NYSE: TDC) reported completing 150+ AI-focused customer engagements in 2025, delivering its autonomous AI + knowledge platform across financial services, healthcare, manufacturing and defense.

Work included fraud and AML model deployment acceleration, large-scale customer feedback analysis, R&D productivity gains using vectorized documents and IoT data, defense object-detection tooling, and secure in-database medical image processing with patient confidentiality controls.

Positive

• 150+ AI engagements completed in 2025
• Deployments across financial services, healthcare, manufacturing, defense
• Secure, scalable in-database medical imaging processing implementation
• AI solutions implemented for fraud/AML, customer analytics, R&D

Negative

• None.

News Market Reaction

-1.73%

1 alert

-1.73% News Effect

On the day this news was published, TDC declined 1.73%, reflecting a mild negative market reaction.

Data tracked by StockTitan Argus on the day of publication.

Key Figures

AI engagements in 2025: 150+ engagements Customer transcripts: 50,000+ weekly

2 metrics

AI engagements in 2025 150+ engagements AI-focused customer engagements completed in 2025

Customer transcripts 50,000+ weekly Weekly customer interaction transcripts at a large Asian bank

Market Reality Check

Price: $29.77 Vol: Volume 1,101,640 vs 20-da...

normal vol

$29.77 Last Close

Volume Volume 1,101,640 vs 20-day average 1,224,062 (about in-line, slightly lighter). normal

Technical Price 31.74 is trading above 200-day MA at 23.43, near the 33.03 52-week high.

Peers on Argus

Peers showed mixed moves: C3.ai up 2.06%, EVERTEC up 1.64%, while Appian fell 3....

Peers showed mixed moves: C3.ai up 2.06%, EVERTEC up 1.64%, while Appian fell 3.73% and Five9 was slightly negative. With TDC nearly flat at -0.06% and no peers in momentum scanners, the setup looks stock-specific rather than a broad software/AI rotation.

Historical Context

5 past events · Latest: Jan 06 (Positive)

Pattern 5 events

Date	Event	Sentiment	Move	Catalyst
Jan 06	Analyst recognition	Positive	+1.9%	Recognized as Leader in Q4 2025 data fabric analyst report.
Nov 24	Investor conferences	Neutral	+1.7%	Announced December technology and TMT investor conference presentations.
Nov 04	Earnings update	Negative	-4.1%	Q3 2025 results with revenue declines despite modest ARR growth.
Nov 03	AI leadership hire	Positive	+3.5%	Named Chief Data and AI Officer to lead enterprise AI strategy.
Oct 28	AI services launch	Positive	+0.4%	Introduced Teradata AI Services for production-ready agentic AI use cases.

Pattern Detected

Recent news—especially AI‑related and analyst recognition—has generally seen price moves that align with the news tone, with AI announcements often skewing modestly positive.

Recent Company History

Over the last few months, Teradata has highlighted steady strategic progress. On Oct 28, 2025, it launched Teradata AI Services to turn pilots into production AI, followed by appointing a Chief Data and AI Officer on Nov 3, 2025. Q3 2025 earnings on Nov 4, 2025 showed modest ARR growth but revenue pressure. On Jan 6, 2026, Teradata was named a Leader in a major data fabric evaluation. Today’s 2025 AI engagement update extends that AI execution storyline with concrete customer activity.

Market Pulse Summary

This announcement underscores Teradata’s shift from AI pilots to production, citing 150+ AI engageme...

Analysis

This announcement underscores Teradata’s shift from AI pilots to production, citing 150+ AI engagements in 2025 across finance, healthcare, manufacturing, and defense. It reinforces earlier launches like AI Services and AgentBuilder by showcasing concrete customer outcomes. In context of prior earnings that showed modest ARR growth but revenue pressure, investors may watch how this AI work translates into ARR, cloud growth, and margin trends in upcoming results, as well as continued customer wins in data‑intensive verticals.

Key Terms

anti-money laundering, large language models, time-series, geospatial analytics, +3 more

7 terms

anti-money laundering financial

"anti–money laundering model deployment due to fragmented architecture"

Anti-money laundering are rules, checks and processes banks and other financial firms use to stop criminals from hiding or moving illegal money. Think of it like ID checks and receipts in a store that make it harder to pass off stolen goods as legitimate; for investors, strong anti-money laundering controls reduce the risk of fines, shutdowns, and reputational damage that can wipe out shareholder value.

large language models technical

"large language models were deployed for topic extraction"

Large language models are advanced AI systems trained on vast amounts of text to understand and generate human-like writing, like a very fast reader and writer that learns patterns in words and sentences. They matter to investors because they can change how companies operate—automating customer service, speeding analysis, cutting costs, creating new products—and they introduce risks around accuracy, security and regulation that can affect a firm’s revenue and reputation.

time-series technical

"time-series and geospatial analytics were utilized at scale"

A time-series is a sequence of data points recorded in chronological order, such as daily stock prices, trading volume, or quarterly revenue. Investors use time-series to spot trends, cycles, and unusual moves—like reading a company’s heartbeat over time—so they can assess momentum, forecast potential outcomes, and make decisions about timing trades or evaluating risk.

geospatial analytics technical

"time-series and geospatial analytics were utilized at scale"

Geospatial analytics uses location-based data and maps from sources like satellites, GPS and mobile devices to reveal patterns and relationships across physical space, such as customer clusters, transportation flows or resource locations. Investors use it to assess market potential, site selection, competitive positioning and supply-chain or environmental risks — like reading a heat map that turns scattered dots into clear signals about where revenue and costs will likely concentrate.

iot technical

"combined with IoT/telemetry data; time-series and geospatial analytics"

The Internet of Things (IoT) describes a network of everyday devices—such as appliances, vehicles, and equipment—that are connected to the internet and can share data automatically. For investors, IoT represents a growing trend that can drive efficiency and innovation across many industries, potentially creating new opportunities for growth and value. Its expansion influences how companies operate and compete in a digitally connected world.

ai-assisted object detection technical

"AI-assisted object detection and pattern analysis from photos"

AI-assisted object detection uses machine learning software to find, identify and mark items, people or features in images and video, then highlights those results for human review or for automated action. For investors, it matters because this capability can cut costs, speed operations and enable new products across fields like manufacturing, security and healthcare—driving revenue growth, productivity gains and potential regulatory or liability risks depending on accuracy and use.

parallel processing technical

"Leveraged parallel processing to remove and store identifying metadata"

Parallel processing is a computing approach where multiple tasks or calculations are handled at the same time rather than one after another, like a kitchen with several cooks working on different dishes simultaneously. For investors, it matters because companies that use or sell parallel-processing hardware and software can deliver faster performance, handle larger workloads, and gain competitive advantages in areas such as cloud services, data analysis, artificial intelligence, and high-frequency trading—factors that can affect revenue, costs, and valuation.

AI-generated analysis. Not financial advice.

SAN DIEGO, Jan. 13, 2026 /PRNewswire/ -- Teradata (NYSE: TDC) today announced significant momentum in delivering AI-powered solutions for global enterprises. In 2025, Teradata completed more than 150 AI-focused customer engagements, helping organizations operationalize AI at scale to solve complex business challenges and unlock measurable value.

Key Highlights

• 150+ AI engagements in 2025 across multiple industries including financial services, healthcare, manufacturing and defense.
• Teradata's AI platform for the autonomous era unified structured and unstructured data, operationalized AI/ML, and delivered real-time insights.
• Work focused on high-value use cases, including fraud detection and reduction, streamlined compliance processes, customer experience analytics to increase customer satisfaction, R&D optimization for increased innovation and efficiency, and mission-critical defense scenarios to protect high-value assets.

AI Case Studies

Industry — Retail Finance

• Customer: A large multinational bank.
• Problem: Complex, slow and expensive anti–money laundering model deployment due to fragmented architecture; regulatory pressure to improve anti-money laundering processes.
• AI Solution: Teradata's autonomous AI and Knowledge platform reduced model deployment time for ML-driven anomaly detection and automated model governance.
• Outcome: More models with faster deployment cycles — saving both time and money.

Industry — Retail Finance

• Customer: A large Asian bank.
• Problem: Massive amounts of customer feedback (50,000+ weekly customer interaction transcripts) were not being analyzed or acted upon.
• AI Solution: Customer chats were vectorized using a task-specific language model; large language models were deployed for topic extraction and sentiment detection.
• Outcome: Identification of key NPS drivers and improved customer engagement strategies.

Industry — Automotive Manufacturing

• Customer: A global auto manufacturer.
• Problem: Data integration challenges slowed R&D cycles.
• AI Solution: Design specification documents were vectorized and combined with IoT/telemetry data; time-series and geospatial analytics were utilized at scale, and a LLM was overlayed to create a language-based interface that engineers can query directly.
• Outcome: Significant increase in R&D productivity.

Industry — Defense and Security

• Customer: A European defense agency.
• Problem: Increased need for camouflage effectiveness of high-value assets (e.g., tanks, armored fighting vehicles, artillery) due to ubiquitous surveillance technologies, new, cost-effective guided weaponry, and implementation of AI in warfare.
• AI Solution: AI-assisted object detection and pattern analysis from photos uploaded via a mobile device. Leveraged Teradata's AI Services for implementation — a sprint-based delivery model that combines expert-led methodology with Teradata's suite of AI tools.
• Outcome: Rapid natural-language advice delivered in real-time to improve effectiveness in protecting people and assets.

Industry — Healthcare

• Customer: A global healthcare company.
• Problem: Needed scalable, performant, and secure processing of medical image data, including mammogram images, while ensuring patient confidentiality and integration with broader patient data.
• AI Solution: Implemented an in-database model that scales large datasets and integrates with patient data. Leveraged parallel processing to remove and store identifying metadata and applied a sophisticated temporal security model to protect confidentiality.
• Outcome: Enabled secure, high-performance processing of medical imaging data at scale, accelerating workflows and improving data accessibility for clinical and research purposes.

Why It Matters
AI adoption is moving from experimentation to enterprise scale production deployments. Teradata's autonomous AI + knowledge platform combines data integration, analytics, knowledge retrieval, and generative & agentic AI to help customers build operational AI systems with robust performance, security, and governance.

Executive Quote
"Our customers want AI that works at real-world enterprise speed and scale—not just demos. These engagements demonstrate how Teradata's autonomous AI + knowledge platform and AI services enable enterprises to integrate trusted data, apply advanced analytics, and deploy AI in production to drive real business and operational outcomes—helping organizations move faster from insight to action."
–– Mike Hutchinson, Chief Operating Officer at Teradata.

About Teradata
Teradata is the AI platform built for the autonomous era. Our AI + Knowledge Platform and multifaceted AI Services help enterprises deploy solutions with deep domain expertise and full enterprise context. Wherever data resides—cloud, on-prem, or hybrid—Teradata connects and scales to deliver the performance AI needs.

Learn more at Teradata.com.

The Teradata logo and ClearScape Analytics are trademarks, and Teradata is a registered trademark of Teradata Corporation and/or its affiliates in the U.S. and worldwide.

MEDIA CONTACT
January Machold
January.Machold@Teradata.com

View original content:https://www.prnewswire.com/news-releases/teradata-accelerates-ai-innovation-with-more-than-150-enterprise-ai-engagements-in-2025-302659508.html

SOURCE Teradata Corporation

FAQ

What did Teradata (TDC) announce about AI engagements in 2025?

Teradata announced it completed 150+ AI-focused customer engagements in 2025 using its autonomous AI + knowledge platform.

Which industries did Teradata (TDC) serve with its 2025 AI projects?

Engagements spanned financial services, healthcare, manufacturing and defense.

How did Teradata (TDC) help banks with AML and fraud in 2025?

Teradata reduced model deployment time and automated model governance for ML-driven anomaly detection to improve AML and fraud workflows.

What data-privacy measures did Teradata (TDC) use for medical imaging?

Teradata implemented in-database processing, removed identifying metadata, and applied a temporal security model to protect patient confidentiality.

Does Teradata (TDC) provide real-time AI insights for defense use cases?

Yes; Teradata deployed AI-assisted object detection and real-time natural-language advice to improve protection of high-value assets.