TQA Targets Enterprise AI Gridlock with New Agentic Focus

AUSTIN, TX – February 20, 2026 – Intelligent automation firm TQA today announced a strategic rebrand and an expanded set of technology partnerships aimed at tackling one of the biggest challenges in the corporate world: the failure of most artificial intelligence projects to deliver tangible business value. The company is pivoting to an "Agentic AI" focus, forging deeper alliances with Microsoft and ServiceNow to complement its long-standing expertise with UiPath.

The move comes as enterprises pour billions into AI, only to see a vast majority of initiatives stall in the experimental phase. Citing research that suggests up to 95% of AI projects fail to reach production or improve financial performance, TQA is positioning itself to bridge this critical "production gap."

The AI Production Paradox

Despite widespread enthusiasm and significant investment in Generative AI, a growing body of evidence reveals a stark disconnect between experimentation and enterprise-wide impact. Industry reports consistently highlight a chasm between pilot projects and scalable, production-ready solutions. Research from firms like McKinsey and Deloitte indicates that while most large companies are using AI, fewer than a third of generative AI experiments move into production, and over 80% of organizations see no tangible impact on their earnings.

This "production paradox" stems from a complex set of deeply rooted operational challenges. Poor data quality and fragmented data infrastructure are primary culprits; AI models are only as effective as the data they are trained on, and many companies lack the robust data engineering pipelines necessary for success. Another major hurdle is the difficulty of integrating sophisticated AI models with aging, complex legacy systems.

Furthermore, many projects fail when attempting to scale from a controlled proof-of-concept to a live, enterprise-wide deployment due to inadequate cloud infrastructure and a lack of clear business objectives from the outset. "We are seeing a massive production gap," said Tom Abbott, Founder and Chief Revenue Officer at TQA, in a statement. "Enterprises are struggling because they are trying to 'bolt on' AI to processes. We are here to solve this problem; we help clients to reinvent their processes and build AI solutions to create a true agent-enabled workforce."

From Automation to Autonomy: The Rise of Agentic AI

TQA's new identity centers on Agentic AI, a term representing the next evolutionary step beyond content-generating models. While Generative AI excels at creating text, images, and code, Agentic AI uses these capabilities as a "brain" to autonomously perform actions, make decisions, and complete complex tasks. In simple terms, if Generative AI creates, Agentic AI does.

These intelligent agents are designed to perceive their digital environment through APIs and databases, reason about the information they gather, and then execute multi-step plans to achieve specific goals with limited human supervision. This shift from task automation to goal-driven autonomy is capturing significant market attention.

The global agentic AI market, valued at over $5 billion in 2024, is projected by analysts to explode to nearly $200 billion by 2034, reflecting a compound annual growth rate of over 40%. This rapid expansion is driven by the demand for more sophisticated automation and intelligent decision-making in sectors from finance to healthcare. TQA's strategy aims to harness this trend, moving clients beyond simple automation toward a future where an "agent-enabled workforce" enhances every action and outcome.

A 'Best-of-Breed' Strategy for a Multi-Platform World

To deliver on this vision, TQA is formalizing a multi-platform strategy that combines the strengths of several technology giants. The company believes no single platform can solve the complex integration and governance challenges of enterprise AI, instead opting for a "best-of-breed" approach.

The expanded partnership with Microsoft places Azure AI, Power Platform, and Copilot at the core of its enterprise solutions. TQA will leverage Microsoft's secure and scalable infrastructure to build and deploy agents, using tools like Copilot Studio to embed AI capabilities directly into the productivity applications employees use daily, such as Teams and Outlook. This approach addresses key enterprise concerns around security, governance, and user adoption.

Simultaneously, TQA is now a consulting and implementation partner for ServiceNow, specializing in its Workflow Data Fabric and AI agent capabilities. This allows the firm to help clients modernize legacy workflows and orchestrate complex processes that span multiple departments and systems, a critical step in moving from siloed AI experiments to cohesive, enterprise-wide transformations.

While expanding its ecosystem, TQA is reaffirming its commitment to UiPath, where it has been a premier Diamond Partner for over six years. UiPath's platform, which is evolving from robotic process automation (RPA) to "agentic automation," provides the crucial connectivity to legacy systems and the robust execution engine for AI-driven tasks. The synergy is clear, with bi-directional integration allowing UiPath automations to be called from Microsoft Copilot, and Microsoft agents to be used within UiPath workflows, creating a seamless bridge between modern AI and existing enterprise infrastructure.

Building on Proven Expertise to Deliver Real-World Results

By combining these platforms, TQA aims to create cohesive agentic architectures that can be deployed in complex, real-world production environments. This strategy directly counters the "bolt-on" approach that has led many AI initiatives to fail. The company's focus is on fundamentally reinventing business processes to be driven by autonomous, outcome-led agents.

With a team of over 200 specialists and a history in intelligent automation since its founding in 2020, TQA argues it has the proven engineering and operationalization skills that separate it from newer AI startups. Its heritage in automation provides a deep understanding of the practical challenges of integrating new technology into established enterprise environments.

"Our promise is simple," Abbott continued. "It's to deliver AI-powered agents that actually work - in the real world, for real business challenges, building on our heritage and expertise in automation." By focusing on measurable efficiency gains and tangible financial impact, the company intends to provide a clear path for clients to finally translate the immense promise of AI into a real operational advantage.