As enterprise AI adoption expands, organizations are getting a clearer picture of how the technology is changing work in practice. This week’s developments show businesses using AI to reshape jobs rather than simply eliminate them, employees building thousands of specialized agents, and companies reconsidering how they reward distinctly human skills. At the same time, AI agents are creating new questions around security, oversight, and accountability as they gain greater access to business systems.
1. Businesses Are Using AI to Change Jobs, Not Eliminate Them
New research from the Federal Reserve Bank of New York offers a useful look at what AI adoption is actually doing to the workforce. More than 60% of service firms and roughly half of manufacturers surveyed said they are now using AI, a considerable increase from 2025. Despite that growth, AI-related layoffs remain uncommon. Instead, businesses are more frequently retraining employees and changing how existing jobs are performed.
The findings provide a practical counterpoint to predictions of widespread AI-driven job losses. For employers, the more immediate use case appears to be helping existing workers research information, produce content, analyze data, automate routine activities, and spend more time on work requiring experience and judgment.
Read the full story on the Federal Reserve Bank of New York
2. UKG Employees Have Created More Than 12,000 AI Agents
HR technology company UKG offers an unusually large example of employee-led AI adoption. The company’s workforce has created 387 AI tools and more than 12,000 agents as UKG encourages its approximately 14,000 employees to experiment with AI. The strategy reflects CIO Prakash Kota’s view that HR could become one of the most significant areas for practical AI adoption.
For other organizations, the example shows what can happen when employees are given the ability to build tools around their own workflows. HR teams could use specialized agents to answer policy questions, assist with onboarding, organize workforce information, and reduce repetitive administrative work, while governance determines which tasks require human involvement.
Read the full story on Fortune
3. EY Is Rewarding Employees for the Human Skills AI Cannot Replace
Ernst & Young is putting $100 million toward bonuses designed to reward employees for capabilities such as critical thinking, judgment, collaboration, and communication. The initiative reflects a growing challenge for employers: as AI takes responsibility for more routine analytical and administrative work, performance management may need to place greater value on skills that complement the technology.
The approach provides a practical workforce example for other organizations. Employees who can question an AI-generated analysis, recognize when a recommendation does not make business sense, communicate findings effectively, or apply experience to an ambiguous decision may become increasingly valuable as AI handles more of the initial work.
Read the full story on The Wall Street Journal
4. “Human in the Loop” May Not Provide as Much Protection as Companies Think
Many organizations rely on human review as an important safeguard for AI, but CIO reports that this approach can create a false sense of security when employees lack the time, expertise, authority, or context needed to meaningfully challenge an AI system’s decisions. In those situations, a person may technically be involved without providing genuine oversight.
The distinction becomes increasingly important as AI enters finance, HR, healthcare, cybersecurity, and other consequential workflows. Organizations may need to define exactly when employees should intervene, what information they need to make an independent judgment, and whether they have sufficient authority to override an AI recommendation.
5. AI Agents Are Creating a New Software Supply Chain Security Problem
As companies connect AI agents to plug-ins, skills, MCP servers, databases, and external applications, security teams are encountering a new category of third-party risk. TechCrunch reports that security companies are developing tools capable of discovering enterprise agents and continuously evaluating the software components those agents use. One provider says it currently rejects about 27% of the publicly available agent add-ons and skills it evaluates.
The issue has practical implications for companies deploying agents in finance, pharmaceuticals, customer service, IT, and other functions. An agent may be secure when initially deployed, but the external tools it relies upon can change or become compromised, making continuous monitoring increasingly important.
Read the full story on TechCrunch
6. AI Spending Is Rising Faster Than Companies’ Ability to Measure Results
Organizations continue to increase AI spending, but many executives still struggle to determine whether those investments are generating sufficient business value. The Wall Street Journal reports that companies are wrestling with how to connect growing AI usage with measurable returns, particularly as tools and models proliferate across departments.
The challenge reinforces the importance of evaluating AI at the use-case level. Instead of measuring success through the number of employees using AI or the number of agents deployed, organizations can examine whether a particular application reduces processing time, lowers costs, improves accuracy, increases revenue, or produces another measurable operational result.
Read the full story on The Wall Street Journal
7. 2026 Corporate AI Talent Study
Artificial intelligence is moving rapidly into production, but workforce readiness is not advancing at the same rate. The 2026 Corporate AI Talent Study from the AI Leaders Council examines how organizations are preparing employees for the AI era, including talent strategy, hiring, training, skills development, and workforce impact. Based on a national survey conducted between June and August 2026 with more than 300 executives across North America, the study provides a timely benchmark for how organizations are building AI capabilities within their workforce.
Why It Matters
- Growing AI adoption is changing how employees perform their jobs, but widespread AI-driven layoffs have yet to materialize among the businesses surveyed by the New York Fed.
- Employee-built agents are creating practical applications across HR and other business functions while introducing new governance requirements.
- Human judgment, critical thinking, and communication are becoming more important as AI assumes responsibility for routine work.
- Simply placing a human in an AI workflow does not guarantee effective oversight unless that person can independently evaluate and challenge the system.
- AI agents create new security risks as they connect with third-party tools, plug-ins, data, and enterprise applications.
- Leaders are facing greater pressure to measure AI according to business outcomes rather than adoption rates or the number of tools deployed.
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