Helport AI Publishes White Paper on AI Labor and the Evolution of Enterprise Digital Workforces

New publication examines how AI can progress beyond task automation to execute enterprise workflows, learn from production outcomes and deliver measurable business results

Live production programs in the Philippines and Mexico reported improvements in revenue, gross margin, worker productivity and revenue per worker during the respective project periods

SAN DIEGO and SINGAPORE, Oct. 01, 2026 (GLOBE NEWSWIRE) -- Helport AI Limited (NASDAQ: HPAI) (“Helport AI” or the “Company”), a global artificial intelligence (“AI”) workforce infrastructure company providing intelligent communication software and services to enterprise clients, today announced the publication of a new white paper, “Beyond Deployment: How AI Labor Becomes a High-Performing Digital Workforce.”

The white paper examines a central challenge facing enterprise AI adoption; namely, how to move beyond AI assistants and isolated task automation toward digital workers capable of learning from expert performance, executing complete workflows across enterprise systems and improving against measurable business outcomes. Helport AI defines this operating model as “AI Labor” — the transformation of enterprise knowledge, expert experience, business processes, system execution and production feedback into deployable, governable and continuously improving digital labor capacity.

“The question for enterprise AI is no longer simply what a model can generate or what individual tasks it can automate,” said Guanghai Li, Chief Executive Officer of Helport AI. “We believe the more important question is whether AI can enter a real operating environment, perform meaningful work, learn from outcomes and become more effective over time. It is our belief that this transition — from AI as software to AI as measurable labor capacity — represents an important evolution and is supported by what we have observed in our own production deployments.”

From AI Deployment to Measurable Labor Capacity

The white paper draws on production experience from two, real-world collections programs in the Philippines and Mexico during the month of September. They illustrate two complementary paths for the development of AI Labor.

In the Philippines program, Helport AI focused on improving the quality and effectiveness of work performed by digital workers. The Company's AI Operation Platform (AOP) learning and optimization system analyzes historical interactions and production outcomes to identify high-performing methods, generate training examples, and test strategies through simulated customer interactions before broader use in live production.

During the reported project period (the month of September):

• Revenue increased 15.71%;
• Gross margin increased 29%;
• The share of calls lasting more than 60 seconds increased from 3.1% to 8.4%, approximately 2.7 times the prior level; and
• The training and production-launch cycle for digital workers was reduced by approximately 50%.

In Mexico, Helport AI focused on expanding the scope of work digital workers could perform. Using Helport AI's HyprLink cross-system execution capabilities and Unified Communication Platform (UCP) omnichannel engagement technology, digital workers were deployed across workflows involving case analysis, enterprise system interaction, customer outreach, collection-note recording and case-status updates.

During the reported project period, the program achieved 100% case-analysis and omnichannel-contact coverage and 100% collection-note accuracy, while cases handled per worker increased 30% and revenue per worker increased 40%.

Results reflect specific customer deployments and project periods, and customer identities have been omitted for confidentiality. Results may have been affected by case mix, customer composition, operating policies, market conditions and other factors, and have not been independently verified through a controlled study. They should not be interpreted as results that will necessarily be achieved in other customer environments, and should not be relied upon as a promise, projection or guarantee of the Company’s future operating performance, financial results or investment returns.

Building AI That Can Learn, Execute and Improve

The white paper describes an AI Labor architecture built around four interconnected capabilities:

• Learning and optimization: AOP uses historical interactions, simulation, automated scoring and production feedback to identify and continuously refine higher-performing operating strategies.
• Work execution: HyprLink enables digital workers to read information from and take actions within enterprise systems, maintain records and respond to operational exceptions.
• Omnichannel engagement: Helport AI's communication infrastructure coordinates customer engagement across voice, SMS, email, WhatsApp and other channels.
• Governance and feedback: Permissions, data controls, auditability, human oversight and production outcomes provide controls for deploying and continuously improving digital labor.

The Company's approach is designed to shift AI from performing isolated actions toward assuming responsibility for broader workflows, while allowing human employees to increasingly focus on supervision, exceptions, judgment-intensive decisions and operating strategy.

As digital workers assume greater responsibility, Helport AI believes governance must develop alongside capability. The white paper describes the Company's approach to compliance validation, runtime monitoring, auditability, human oversight and data classification, including an AI Data Firewall designed to control how sensitive enterprise information interacts with AI systems.

A Different Measure of Enterprise AI

The white paper argues that enterprise AI should be evaluated not simply by model benchmarks or the number of features deployed, but also by its ability to execute real work reliably and contribute to measurable operating outcomes.

“Deployment should not be viewed as the finish line for enterprise AI; it is the beginning of the learning process,” added Li. “Our objective is to create digital workers that can learn how high-performing employees work, execute across real enterprise environments and continuously improve through production feedback. We believe the defining question for AI Labor is not simply what the AI can do, but whether it can complete the work, complete it correctly, and perform it better the next time.”

The full white paper, “Beyond Deployment: How AI Labor Becomes a High-Performing Digital Workforce,” is available at: https://ir.helport.ai/static-files/a999b4e9-50c3-4ed8-9d51-5aa25a27e900

About Helport AI

Helport AI (NASDAQ: HPAI) is a global AI workforce infrastructure company providing intelligent communication software and services to enterprise clients. Its core asset is the AI Labor System, an industrial-scale platform designed to manufacture, orchestrate, and deliver AI workforce capacity based on measurable business outcomes. Through its AI workforce, Helport AI helps clients drive sales, improve engagement, and reduce costs. The Company’s mission is to transform human expertise into scalable AI labor. Learn more at www.helport.ai.

Forward-Looking Statements

Certain statements in this announcement are forward-looking statements, including, but not limited to, statements regarding Helport AI's business plans, strategies, objectives, expectations regarding the development and adoption of AI Labor, the capabilities and potential applications of the Company's technologies, and the Company's expectations regarding the future development and deployment of its products and services. Forward-looking statements in this announcement also include statements regarding the anticipated benefits, scalability, replicability or future performance of the Company's AI Labor operating model and related technologies (including AOP, HyprLink and UCP), and management's expectations and beliefs regarding the future direction of enterprise AI adoption, as reflected in the white paper and in the quotations of Company management included in this announcement. The production results described in this announcement and the accompanying white paper reflect historical outcomes from specific customer deployments during specific project periods and are not forward-looking statements, and readers should not assume that such historical results are indicative of, or a guarantee of, future or comparable results in other customer environments or periods. These forward-looking statements involve known and unknown risks and uncertainties and are based on the Company's current expectations and projections about future events that the Company believes may affect its financial condition, results of operations, business strategy and financial needs.

Investors can identify many of these forward-looking statements by words or phrases such as “believes,” “expects,” “anticipates,” “estimates,” “projects,” “intends,” “plans,” “will,” “would,” “should,” “could,” “may” or similar expressions. Actual results may differ materially from those expressed or implied by these forward-looking statements due to various risks and uncertainties. The Company undertakes no obligation to publicly update or revise any forward-looking statements to reflect subsequent events or circumstances, except as may be required by law. Investors are encouraged to review the Company's filings with the U.S. Securities and Exchange Commission for additional information regarding factors that may affect future results.

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Helport AI Limited
Email: ir@helport.ai
Website: ir.helport.ai