Seven Independent Studies Confirm AI Agents Fail 70–95% of the Time. A New Book by VectorCertain’s CEO Shows Why—and What To Do About It.

South Portland, Maine (Newsworthy.ai) Monday Feb 16, 2026 @ 7:00 AM Eastern —

As Carnegie Mellon’s TheAgentCompany benchmark reveals that the best AI agents fail nearly 70% of real-world office tasks, MIT reports that 95% of enterprise AI pilots deliver zero measurable return, and Gartner predicts more than 40% of agentic AI projects will be canceled by 2027, VectorCertain LLC founder and CEO Joseph P. Conroy has published The AI Agent Crisis: How To Avoid The Current 70% Failure Rate & Achieve 90% Success—the first book to synthesize these findings into a proven implementation framework for enterprise leaders.

Available now on Amazon, the book presents a systematic analysis grounded in Carnegie Mellon University’s TheAgentCompany research, identifying the seven critical barriers that cause AI agent deployments to fail and providing a 12-month implementation roadmap for overcoming them.

THE CRISIS: CONFIRMED BY EVERY MAJOR RESEARCH INSTITUTION

The AI agent failure crisis is no longer a debate. It is the most thoroughly documented failure pattern in enterprise technology, confirmed independently by seven institutions across three continents:

Carnegie Mellon University (TheAgentCompany, 2024–2025): Tested 10 leading AI agent models across 175 real-world tasks. The best performer—Google’s Gemini 2.5 Pro—completed just 30.3% of tasks. Claude 3.7 Sonnet achieved 26.3%. GPT-4o managed only 8.6%. Common failures included fabricating data, renaming users to fake task completion, and what researchers called a fundamental absence of “common sense.”

MIT NANDA “The GenAI Divide” (2025): Based on 52 organizational interviews, 153 senior leader surveys, and analysis of 300+ public deployments, MIT found that 95% of enterprise AI pilots deliver zero measurable financial return.

RAND Corporation (2024–2025): Concluded that more than 80% of AI projects fail—twice the failure rate of non-AI IT projects—after interviews with 65 experienced data scientists and engineers.

S&P Global (2025): Found that 42% of companies abandoned most of their AI initiatives, up from 17% the prior year—a 147% year-over-year increase.

Gartner (June 2025): Predicted that over 40% of agentic AI projects will be canceled by end of 2027, and found that only approximately 130 of thousands of agentic AI vendors offer genuine agentic capabilities—the rest are “agent washing.”

“Most agentic AI projects right now are early-stage experiments or proof of concepts that are mostly driven by hype and are often misapplied. This can blind organizations to the real cost and complexity of deploying AI agents at scale.”

— Anushree Verma, Senior Director Analyst, Gartner

THE BOOK: FROM CRISIS DIAGNOSIS TO IMPLEMENTATION FRAMEWORK

The AI Agent Crisis doesn’t merely document the problem. Drawing on Conroy’s 25+ years building AI systems for mission-critical applications—including neural network optimization platforms that became EPA regulatory standards—the book presents the first comprehensive framework for achieving sustained AI agent success in production environments.

Key contributions of the book include identification of seven critical barriers driving AI agent failures, from communication success rates as low as 29% to navigation failure rates of 12%; an integrated ROI methodology demonstrating how properly governed AI agents can deliver 73% revenue increases and 702% annualized returns; production-validated approaches achieving 97% communication success, 90%+ navigation reliability, and 85% cost reduction; and industry-specific implementation playbooks with a 12-month deployment roadmap.

“The 70% failure rate isn’t random—it’s predictable. After two decades building AI systems for the EPA, DOE, and DoD, I discovered that catastrophic failures cluster in statistical tail events that conventional approaches ignore entirely. This book codifies the framework that VectorCertain was built to solve.”

— Joseph P. Conroy, Founder & CEO, VectorCertain LLC

WHY NOW: A SECURITY CRISIS THAT PROVES THE BOOK’S THESIS

The urgency of the book’s message was underscored in dramatic fashion in January and February 2026, when a cascade of AI agent security failures validated precisely the governance gaps the book identifies.

OpenClaw, the open-source AI agent framework with over 160,000 GitHub stars and more than one million users, became the center of the most significant AI security incident of 2026. Researchers discovered 1.5 million exposed API authentication tokens, 42,900 vulnerable control panels across 82 countries, and Bitdefender Labs found that approximately 17% of all OpenClaw skills exhibited malicious behavior including crypto-stealing malware and reverse shells.

Meanwhile, OpenAI published a candid acknowledgment that prompt injection in AI agents “may never be fully solved,” and Meta research found prompt injection attacks partially succeeded in 86% of cases against web agents. On February 3, 2026, the International AI Safety Report—chaired by Turing Award winner Yoshua Bengio and backed by 30+ countries—warned that the gap between AI advancement and effective safeguards remains a critical challenge.

“When something goes wrong with agentic AI, failures cascade through the system. The introduction of one error can propagate through the entire system, corrupting it.”

— Jeff Pollard, Principal Analyst, Forrester

These are not hypothetical risks. They are the real-world manifestations of the governance failures that The AI Agent Crisis was written to address.

FROM RESEARCH TO PRODUCTION: INTRODUCING SECUREAGENT

While the book provides the diagnostic framework, VectorCertain is not standing still. The company is preparing to launch SecureAgent—an open-core AI agent security platform that translates the book’s principles into production-grade infrastructure.

Built through 22 consecutive development sprints with zero test failures across 7,229 automated tests, SecureAgent represents one of the most rigorously validated enterprise software platforms ever constructed. The platform encompasses 615 source modules, 91,849 lines of production code, and 123,573 lines of test code—a test-to-source ratio of 1.34:1 that exceeds industry benchmarks.

SecureAgent’s architecture directly addresses every failure mode identified in the book, including a patented multi-layer governance engine with four validation tiers; a bidirectional security envelope that inspects every AI agent action before execution; multi-model consensus verification using ensemble architectures that achieve 97%+ accuracy; cryptographic audit trails for full regulatory compliance; and enterprise-grade SSO, SLA enforcement, and role-based access controls.

“Value doesn’t come from launching isolated agents. 2026 will be the year we begin to see orchestrated super-agent ecosystems, governed end-to-end by robust control systems.”

— Swami Chandrasekaran, Global Head of AI and Data Labs, KPMG (January 2026)

SecureAgent is designed to be that robust control system. Details on availability, pricing, and early access will be announced in the coming weeks at vectorcertain.com.

MARKET VALIDATION: THE CATEGORY HAS ARRIVED

The enterprise market has spoken clearly about the demand for AI agent governance. Cisco acquired AI safety company Robust Intelligence for approximately $400 million and expanded its AI Defense product line in February 2026. F5 Networks acquired CalypsoAI for $180 million and launched F5 AI Guardrails. WitnessAI raised $58 million in January 2026 specifically for AI agent security. And Galileo AI, which achieved 834% revenue growth in 2025, launched a dedicated Agent Reliability Platform.

Gartner projects that 40% of enterprise applications will integrate task-specific AI agents by end of 2026—up from less than 5% in 2025. Yet Deloitte’s 2026 State of AI survey found that only 21% of enterprises have a mature model for agent governance. That gap—between deployment velocity and governance readiness—is the precise market VectorCertain was built to serve.

THE REGULATORY CLOCK IS TICKING

The EU AI Act’s full enforcement of high-risk AI system requirements begins August 2, 2026, with penalties up to €35 million or 7% of global revenue. In the United States, 38 states passed AI legislation in 2025, with California, Texas, and Colorado laws taking effect January 1, 2026. NIST published its first Federal Register request specifically targeting AI agent security in January 2026.

Forrester predicts that an agentic AI deployment will cause a publicly disclosed data breach in 2026. The question for enterprises is not whether AI agent governance is necessary, but whether they will have it in place before the inevitable incident.

ABOUT THE AUTHOR

Joseph P. Conroy is the Founder and CEO of VectorCertain LLC, a Delaware corporation developing AI safety and governance technology for mission-critical applications. With 25+ years building AI systems for federal agencies including the EPA, DOE, DoD, and NIH, Conroy pioneered the ENVAPEMS predictive emissions monitoring system that became codified in EPA regulations. He and his team were also the first to use AI to predict electricity futures on NYMEX in 2001. He holds 19+ provisional patent applications across AI ensemble systems and multi-model consensus technologies, and developed VectorCertain’s Micro-Recursive Model architecture enabling safety coverage in statistical tails where catastrophic events occur.

Conroy is available for speaking engagements and expert commentary on AI agent reliability, AI safety, and enterprise AI governance.

ABOUT VECTORCERTAIN LLC

VectorCertain LLC is an AI safety and governance technology company headquartered in Maine. The company’s mission is to make AI systems mathematically provable for mission-critical applications across regulated industries including financial services, healthcare, autonomous vehicles, defense, and energy. VectorCertain’s patent-pending architecture combines ultra-compact Micro-Recursive Models (71–1,500 byte models operating at sub-millisecond latency), multi-model consensus verification, and the forthcoming SecureAgent enterprise governance platform.

Learn more at vectorcertain.com.

BOOK DETAILS

Title: The AI Agent Crisis: How To Avoid The Current 70% Failure Rate & Achieve 90% Success: Based on Carnegie Mellon University’s TheAgentCompany Research & Proven Implementation Strategies

Author: Joseph P. Conroy

Publisher: VectorCertain LLC

Available: Amazon — https://www.amazon.com/dp/B0FXN4Y676

Company: https://vectorcertain.comhttps://www.amazon.com/dp/B0FXN4Y676

FOR MEDIA

Review copies, executive interviews, data fact sheets, and high-resolution author photos available upon request. Contact [email protected].

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