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Shadow AI Could Expose Sensitive Data Before Companies Know It

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As employees adopt public AI tools faster than companies can govern them, Magna5 says mid-market organizations need secure, sanctioned AI pathways before sensitive data leaves controlled environments.

PITTSBURGH, July 6, 2026 /PRNewswire/ — Employees are adopting artificial intelligence into the workplace faster than many companies can govern it, creating a new data-security blind spot for mid-market organizations. A recent survey found that nearly half of workers (49%) admitted using AI tools at work without approval, often sharing sensitive data with free versions of popular tools such as ChatGPT. Magna5, a national managed IT, cybersecurity, cloud and compliance services provider, warns that shadow AI is becoming the next version of shadow IT, but with higher stakes. Across mid-market organizations, employees may unintentionally expose contracts, client records, financial data, employee information, proprietary data, and other sensitive business information through AI tools that were never approved.

“Employees have learned that they should not store company files in their personal email or cloud storage, but many do not think twice about uploading a contract or customer information into a personal AI tool,” said Justin Cameron, Chief Technology Officer of Magna5. “AI can feel like a private conversation, but the more comfortable employees get using it every day, the easier it is to forget that public tools are storing their inputs, may be training on them, and could potentially reuse that data for other users.”

The Adoption Gap Is Becoming the Security Gap 

Employees use tools such as ChatGPT, Microsoft Copilot, and Claude to save time, improve writing, summarize information, and answer questions. In many organizations, usage has outpaced policy, training, and security controls.

That gap creates a new challenge for executives: AI adoption cannot be managed only as an innovation initiative. It must also be treated as a governance, cybersecurity, and compliance issue.

That is where AI governance must become operational, not theoretical. The National Institute of Standards and Technology’s AI Risk Management Framework urges organizations to govern, map, measure, and manage AI risk. Many mid-market companies, however, still lack the fundamentals required to do that: visibility into where AI is being used, rules for what data can be shared, controls to limit unauthorized tools, and monitoring to ensure employees follow policy.

“A policy without enforcement is simply an expectation,” Cameron said. “Organizations need to take a two-pronged approach by giving employees access to a secure, approved AI platform and maintaining visibility into whether unsanctioned tools are being used outside of it. Without both in place, companies are ultimately relying on trust rather than control.”

Blocking Alone is Not a Complete Strategy 

Some companies may respond to AI by trying to ban public tools. Magna5 cautions this approach can backfire if employees still need to use AI but are not given an easy, sanctioned alternative to adopt. Instead, Cameron recommends giving employees a “walled garden” for AI: an approved environment where workers can experiment, learn, and become more productive without relying on unmanaged models.

“Step one is offering employees a secure system and educating them on how to use it, so they adopt company-approved tools instead of personal ones,” Cameron said. “Then companies need security controls that provide visibility into AI usage, monitor what data is being submitted, and enforce clear policy.”

For healthcare organizations, the concern may involve administrative workers uploading patient records or other protected information to help with billing, documentation, or reporting. That risk comes as the industry is under pressure from rising cybersecurity incidents: HHS says reports of large breaches increased 102% from 2018 to 2023, while the number of individuals affected increased 1,002%. More than 167 million people were affected by large healthcare breaches in 2023 alone.

For Defense Industrial Base companies, the concern is that controlled unclassified information could move into unapproved AI platforms, browser-based agents, or other tools without proper access control. “Any data entered into a free or personal AI model that has not been secured and managed by the company creates exposure,” Cameron said.

Crawl Before You Run 

Magna5 recommends that companies adopt AI through a staged approach, like a “crawl, walk, run, sprint” model, to help organizations move from basic awareness to secure, business-aligned AI adoption:

Crawl: Understand the company’s current AI footprint by identifying official and unofficial usage, surveying employees, setting acceptable-use guidelines, selecting low-risk use cases, and creating a safe environment for experimentation. This stage should also include a review of data hygiene, because AI outputs are only as reliable as the information behind them. Before enriching AI with internal knowledge, organizations need to ensure their data is current, accurate, trustworthy, and not trapped in outdated records, inconsistent documentation, or siloed systems.Walk: Expand into measurable, value-driving use cases such as customer support, sales, marketing, engineering, reporting, or internal knowledge management.Run and Sprint: Move toward deeper AI integration only after governance, training, security controls, and approved use cases are in place, allowing AI to become embedded into workflows, decision support, automation, and purpose-built agents.

“AI is already inside the business, whether leadership has formally approved it or not,” Cameron said. “The question is whether companies will govern it intentionally or discover the risk after sensitive data has already left their control.”

About Magna5

Magna5 is a national managed IT, cybersecurity, cloud and compliance services provider serving small and mid-sized businesses, mid-market organizations and regulated industries across the United States. The company helps organizations manage critical IT infrastructure, protect networks and data, support users, and strengthen operational resilience through 24/7/365 monitoring, managed security, cloud, backup, disaster recovery and compliance support. Magna5 works with security- and uptime-conscious sectors including the Defense Industrial Base, healthcare, financial services, legal, manufacturing, education, construction, government and professional services. For more information, visit www.magna5.com.

Sources:

National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0). U.S. Department of Commerce. nist.gov/itl/ai-risk-management-frameworkNational Institute of Standards and Technology. (n.d.). AI RMF playbook. U.S. Department of Commerce. nist.gov/itl/ai-risk-management-framework/ai-rmf-playbookNational Institute of Standards and Technology. (2024). Artificial intelligence risk management framework: Generative artificial intelligence profile. U.S. Department of Commerce. nist.gov/itl/ai-risk-management-frameworkU.S. Department of Health and Human Services. (n.d.). HIPAA Security Rule NPRM to strengthen the cybersecurity of electronic protected health information. hhs.gov/hipaa/for-professionals/security/hipaa-security-rule-nprm/index.htmlITPro. (2025). CISA’s interim chief uploaded sensitive documents to a public version of ChatGPT — security experts explain why you should never do that. itpro.com/security/data-protection/cisas-interim-chief-uploaded-sensitive-documents-to-a-public-version-of-chatgpt-security-experts-explain-why-you-should-never-do-that

Media Inquiries:
Karla Jo Helms
JOTO PR™
727-777-4629
Jotopr.com

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LendingTree Applauds North Carolina’s AI Strategic Roadmap, Highlights Company’s Leadership in Shaping Responsible AI Policy

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July 6, 2026

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CHARLOTTE, N.C., July 6, 2026 /PRNewswire/ — LendingTree, (NASDAQ: TREE), one of the nation’s largest online financial marketplaces, celebrates the release of Governor Josh Stein’s North Carolina AI Strategic Roadmap, marking a major step forward in establishing the state as a national leader in the responsible development, deployment, and governance of artificial intelligence.

“Artificial intelligence is already changing how we work, learn, and serve the people of our state, and North Carolina must lead with urgency and care,” said Governor Josh Stein. “This roadmap gives our state a strategy to protect people from harm, prepare our workforce for opportunity, and transform how government serves the public. Together, we can make North Carolina a place where innovation and trust move forward together.” 

LendingTree played an active role in helping inform the state’s approach to AI through the service of Sarah Bacha, Senior Vice President, Head of Strategy and Analytics at LendingTree, on Governor Josh Stein’s Artificial Intelligence Advisory Council.

The Council, comprised of leaders from industry, academia, government, and the nonprofit sector, was charged with developing recommendations to guide North Carolina’s AI strategy. Bacha’s contributions helped ensure the Council’s work reflected practical, real-world perspectives on innovation, consumer protection, transparency, and responsible deployment of emerging technologies.

“North Carolina’s AI Strategic Roadmap is a model for how states can approach this rapidly evolving technology,” said Bacha. “The recommendations reflect a thoughtful balance between fostering innovation and establishing the guardrails necessary to build public confidence. I was honored to contribute to this effort and proud that LendingTree could bring the perspective of a technology-driven company serving millions of consumers.”

For nearly three decades, LendingTree has been at the forefront of leveraging technology to help consumers make smarter financial decisions. As AI continues to reshape financial services, LendingTree has advocated policies that encourage innovation while preserving consumer choice, protecting privacy, and ensuring emerging technologies are used responsibly.

At the Fintech + Insurtech Generations conference held in Charlotte, N.C. last month, Hala Shakra, Director of AI Strategy at LendingTree, spoke on the value of governance in Artificial intelligence.

“The mindset of governance is to not think of it as slowing AI down. If done well, it can create clarity. This is what teams need to help them move faster and continue to innovate,” Shakra noted.

The final plan outlines a comprehensive framework for advancing artificial intelligence across state government, education, workforce development, economic growth, and consumer-facing industries. It positions North Carolina to compete for future investment and talent while promoting ethical and responsible AI adoption.

About LendingTree, Inc.

LendingTree, Inc. is the parent of LendingTree, LLC and several companies owned by LendingTree, LLC (collectively, “LendingTree”).

LendingTree (NASDAQ: TREE) is one of the nation’s largest, most experienced online financial platforms, created to give consumers the power to win financially. LendingTree provides customers with access to the best offers on loans, credit cards, insurance and more through its network of over 770 financial partners. Since its founding, LendingTree has helped millions of customers obtain financing, save money, and improve their financial and credit health in their personal journeys. With a portfolio of innovative products and tools and personalized financial recommendations, LendingTree helps customers achieve everyday financial wins.

LendingTree, Inc. is headquartered in Charlotte, NC. For more information, please visit www.lendingtree.com.

MEDIA RELATIONS:
press@lendingtree.com

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Arango Recognized as a Strong Performer in Multimodel Data Platforms, Q2 2026 Evaluation

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July 6, 2026

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Arango believes recognition highlights its native multimodel architecture, customer adoption, and contextual data foundation for trusted enterprise AI

SAN FRANCISCO, July 6, 2026 /PRNewswire/ — Arango, the company pioneering the live Contextual Data Layer for enterprise AI, today announced it has been named a Strong Performer in The Forrester Wave™: Multimodel Data Platforms, Q2 2026. According to the report, Arango is “well-suited to organizations seeking a contextual data foundation where multihop graph performance and verifiable reasoning are mission-critical for trusted AI.”

The recognition comes at a time when enterprises are increasingly focused on how to create and operationalize business context for AI. As organizations move beyond experimentation and into production deployments of AI agents, assistants, and applications, many are reevaluating architectures built from separate databases, vector stores, search engines, and integration layers in favor of platforms that simplify how business context is connected, governed, and made available to AI systems.

Arango believes the recognition reflects growing enterprise demand for a unified approach to multimodel data management. According to the evaluation, Arango received the highest possible scores in the criteria of adoption and unified multimodel architecture.

“As organizations move AI initiatives into production, many are discovering that the challenge is no longer simply connecting data. The challenge is creating trusted business context that AI systems can reason over consistently,” said Ravi Marwaha, Chief Operating Officer and Chief Product & Technology Officer, Arango. “Enterprises increasingly want a simpler way to build, govern, and operationalize business context across their data landscape. We believe this recognition reflects growing demand for unified platforms that help organizations create a trusted foundation for enterprise AI.”

Why It Matters

At scale, enterprise AI is fundamentally a trusted business context challenge. AI agents, assistants, and applications must understand how customers, products, policies, processes, and operational events relate to one another. Organizations are increasingly looking for ways to create this context once, govern it centrally, and make it available across AI initiatives rather than rebuilding it repeatedly.

Agentic AI systems increasingly require access to multiple forms of data, including relationships, documents, vectors, search results, and operational records. As a result, technology leaders are seeking platforms that can:

Unify graph, vector, document, key-value, and search capabilities within a single architectureReduce the need for multiple databases, synchronization pipelines, and query layersSupport governance, lineage, provenance, and explainability across connected dataScale transactional, analytical, and AI workloads with greater operational controlAccelerate the path from AI prototype to production deployment

Rather than managing separate systems for each workload, organizations are increasingly seeking a simpler foundation for intelligent applications, assistants, and AI agents.

Recognition for a Contextual Data Foundation

In its evaluation, Forrester cited Arango’s native multimodel architecture, which combines unified storage, execution, and schema propagation within a single engine. The report also noted Arango’s integrated AI capabilities, which combine graph, vector, and document data in a single retrieval path with source citations.

Arango believes these capabilities are increasingly important as organizations seek to build AI systems capable of reasoning across connected enterprise data while maintaining transparency, governance, explainablity and trust.

Built on a graph-native multimodel foundation, the Arango Contextual Data Platform unifies graph, vector, document, key-value, and search capabilities into a single distributed engine. The platform enables organizations to create a live Contextual Data Layer, a persistent, governed representation of business context that can be reused across AI systems across the enterprise.

Building Trusted AI Starts with Trusted Business Context

As enterprises expand AI initiatives across products, workflows, and business functions, data foundations must support more than performance. They must also provide explainability, governance, traceability, and operational scalability.

Arango believes multimodel data platforms play an increasingly important role in enabling organizations to build context once and reuse it across AI systems, helping reduce duplication, improve consistency, and accelerate deployment.

Resources

Get access to the Forrester WaveLearn about the Contextual Data PlatformJoin our upcoming webinar: Contextual Data Layer for Enterprise AI: 6 Requirements for Agentic AI Systems

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. This report is part of a broader collection of Forrester resources, including interactive models, frameworks, tools, data, and access to analyst guidance. For more information, read about Forrester’s objectivity here.

About Arango
Arango is pioneering the live Contextual Data Layer for enterprise AI, helping organizations transform fragmented enterprise data into trusted, reusable business context that enables AI agents, assistants, and applications to reason, decide, and act with greater accuracy, explainability, and trust at scale.

Built on the Arango Contextual Data Platform—a graph-native multimodel data foundation that unifies graph, vector, document, key-value, and full-text search capabilities with ACID guarantees—the live Contextual Data Layer enables organizations to build context once and reuse it across AI initiatives.

The platform includes more than 20 built-in AI services for contextual modeling, retrieval, orchestration, and enterprise AI development. The result is more accurate decisions, greater explainability, end-to-end traceability, faster deployment, and increased trust in enterprise AI outcomes.

Organizations including NVIDIA, HPE, Zscaler, London Stock Exchange Group, Siemens, the U.S. Air Force, NIH, Articul8, and others rely on Arango to power enterprise AI. Learn more at arango.ai.

Company: Arango

Announcement: Named a Strong Performer in The Forrester Wave™: Multimodel Data Platforms, Q2 2026

Category: Multimodel Data Platforms (MMDPs)

Target Users: Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Data Officers (CDOs) Chief Data & AI Officers (CDAOs), Chief AI Officers, Enterprise Architecture Leaders and Data Management teams

Primary Use Case: Building trusted enterprise AI with a live Contextual Data Layer that connects enterprise data, relationships, governance, and operational context

Key Differentiator: Native multimodel architecture combining graph, vector, document, key-value and full-text search capabilities in a single platform

Platform Snapshot:

Live Contextual Data Layer for enterprise AI20+ built-in AI services, including Arango AutoGraph, Arango AutoRAG and Arango Deep Search

Recognition Highlights: Strong customer adoption, customer success, customer retention, multimodel utilization, unified architecture across graph, vector, document, key-value, and search workloads, and support for multihop graph performance and verifiable reasoning for trusted AI.

Why This Matters: Organizations need trusted business context to deploy AI agents, assistants, and applications reliably, explainably, and at enterprise scale, with the transparency and governance required for trusted AI.

Source: The Forrester Wave™: Multimodel Data Platforms, Q2 2026

Media Contact
press@arango.ai 

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GTT GROUP RELEASES FIRST QUARTER PATENT TRANSACTION MARKET REPORT DOCUMENTING HIGH NPE ACTIVITY LEVELS (PTMR)

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July 6, 2026

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PORTLAND, Ore., July 6, 2026 /PRNewswire/ — Global Technology Transfer Group, Inc. (GTT Group), a world leader in strategic patent analysis, patent transaction, patent development venture capital, and patent enterprise valuation services released its First Quarter 2026 Patent Transaction Market Report and Forecast (PTMR) this morning. The report includes the Patent Market Index (PMI®) and the Patent Licensing Index (PLI®) along with sector specific patent activity.

The PMI dropped slightly in Q1, decreasing by 2.6 percent. Our opinion is that the drop does not reflect reality, as the USPTO experienced significant data-related challenges during Q1 which impacted assignment data and our patent information systems. The PLI increased by 10.4% percent, finishing the first quarter at 2,304. We expect the PLI to continue an upward trajectory throughout 2026. The PLI has outperformed the S&P 500 for 3 consecutive quarters.

Michael Lubitz, Managing Director and Founder of GTT Group added, “The first quarter saw a highly active patent market, which ultimately highlighted an immediate need for robust countermeasures. Various entities are lowering assertion costs by utilizing AI tools. We are forecasting increased expense burdens related to these matters.”

To obtain a complete copy of the report through a complimentary PTMR subscription please visit www.gttgrp.com/pmtr. GTT Group makes this information available as a courtesy to the community.

Request Your Copy of the PTMR.

About the PTMR

For more than a decade, GTT Group’s Patent Transaction Market Report has provided subscribers with key data on the health of the patent marketplace. Within the PTMR, you will find the industry’s benchmark indexes and in-depth forecasting that are essential in understanding the current market and strategizing for the future. The quarterly report includes a detailed breakdown of the PMI® (Patent Market Index), showcasing the market’s overall health and trends. The report highlights notable transactions, including applicable technical areas and the most active buyers and sellers. The report compares publicly traded licensing companies in aggregate vs. the S&P 500 via the PLI® (Patent Licensing Index). The quarterly report also provides insight regarding recent filing trends in emerging and disruptive technology areas.

About the PMI® and PLI®

The Patent Market Index (PMI®) tracks patent transaction activity and is reported quarterly in the Patent Transaction Market Report (PTMR). The Patent Licensing Index (PLI®) tracks publicly traded patent licensing companies and is also reported quarterly in the PTMR.

About Global Technology Transfer Group, Inc.

Global Technology Transfer Group, Inc. (www.gttgrp.com) is a market leader and pioneer in patent analysis, patent transaction (divestiture & acquisition), and patent enterprise value services. GTT Group is the first mover in patent equity venture capital investing via its affiliated venture capital fund, Ideaship (www.ideashipfund.com). GTT Group’s patent asset house leverages core competencies in patent analysis, valuation, and market knowledge to deliver unparalleled results. The company’s corporate headquarters are in Portland, Oregon.

Contact about this news:

Xuan Cheng-Wylie xcheng@gttgrp.com

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SOURCE Global Technology Transfer Group, Inc.

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