Operational Excellence (OPEX) Insight – Thursday January 29, 2026: 57% Of U.S. Small Businesses Invest In AI — But Internal Trust Isn’t Keeping Up.
Góc Nhìn Vận Hành Xuất Sắc – Thứ Năm, Ngày 29/01/2026: 57% Doanh Nghiệp Nhỏ Mỹ Đã Đầu Tư AI – Nhưng Niềm Tin Nội Bộ Chưa Theo Kịp.
Welcome To Operational Excellence (OPEX) Insight Article For The Paid Subscriber-Only Edition.
This is the bilingual post in English and Vietnamese. Vietnamese is below.
Đây là bài viết song ngữ Anh-Việt. Tiếng Việt ở bên dưới.
English
PART 1 – OFFICIAL INFORMATION
The 2026 Small Business AI Outlook Report shows that the adoption of artificial intelligence (AI) among small businesses in the United States has entered a new phase: AI is no longer experimental, but is increasingly becoming an integral part of day-to-day operations. According to the report, 57% of U.S. small businesses have already invested in AI, with the rate of regular use — including daily or weekly usage — continuing to rise throughout 2025 and into early 2026.
Surveyed businesses report that AI is primarily used in activities such as content creation, customer service, basic data analysis, marketing, administrative process optimization, and operational decision support. For many small businesses, AI is viewed as a tool to compensate for limited resources, particularly in a context of rising labor costs and increasing competitive pressure.
From the perspective of business owners and managers, the report identifies a clear trend: most leaders believe that AI is improving work efficiency, saving time, and reducing workload pressure on lean teams. Many respondents stated that without AI, their businesses would face greater difficulty in maintaining customer response speed, handling administrative tasks, and scaling operations.
However, the report also highlights a notable finding: the gap in perception and trust between management and employees is becoming increasingly evident. While business leaders tend to evaluate AI positively and see it as a competitive advantage, employees express a more cautious attitude. A significant proportion of workers report that they do not fully trust AI-generated outputs and feel the need to review, edit, or assume additional responsibility when using AI in their work.
According to the report, this difference does not stem from employee resistance to technology, but rather from real-world usage experience. Many employees shared that AI helps them work faster at the initial stage, but at the same time creates new responsibilities, such as quality control, error detection, context validation, and ensuring customer-appropriate outputs. As a result, the time-saving benefits are not always felt as clearly as initially expected.
The report further emphasizes that trust in AI is a critical factor for long-term effectiveness. In organizations where employees receive clear training on how to use AI, understand the limitations of the tools, and operate within well-defined control processes, AI adoption rates are significantly higher. Conversely, in environments where AI is deployed rapidly without guidelines, output standards, or clear responsibility boundaries, employees are more likely to view AI as a source of risk rather than support.
Another important finding of the 2026 Small Business AI Outlook Report is that investing in AI does not automatically lead to productivity improvements. Businesses that report clear and measurable benefits are typically those that combine AI adoption with changes in work practices, rather than merely adding new tools. This includes clarifying the role of AI in specific tasks, defining final accountability, and adjusting performance expectations to align with operational reality.
Taken together, the data in the report present a dual-sided picture: AI adoption among U.S. small businesses is broader than ever, yet the gap between management expectations and employee experience remains unresolved. This is not merely a technology issue, but one that is directly tied to how businesses design work, manage people, and integrate AI into everyday operational systems.
