Each week, as SHRM's executive in residence for AI+HI, I scour the media landscape to bring you expert summaries of the biggest artificial intelligence headlines — and what they mean for you and your business.
This week shows the tension between AI's promises of productivity and the uneven reality of adoption, measurement, and deployment. McKinsey & Company offers hard lessons from the trenches, Anthropic warns of widening inequality, the Brookings Institution tempers the hype with history, and Goldman Sachs says the economic boost isn't even showing up in GDP data. Meanwhile, the tools keep coming — including Indeed's agents for job seekers and ServiceNow's vibe coding for enterprises.
1. One Year of Agentic AI: Six Lessons from the People Doing the Work
What to Know:
McKinsey reviewed more than 50 agentic AI deployments and identified six lessons for success. Value comes from redesigning workflows, not just building agents. Agents aren't always the best fit; simpler automation can work better in standardized processes. Poor outputs erode trust, so companies must "onboard" agents like they do employees — with evaluations and continuous feedback. Tracking performance step by step is essential, and the reuse of agents prevents redundancy. Humans remain critical for oversight, judgment, and edge cases, though roles and headcount will shift.
Why It Matters:
Agentic AI can streamline work, but only when paired with workflow redesign, trust-building, and human collaboration. Companies that ignore these lessons risk wasted investment, low adoption, and hidden failures.
2. Anthropic Data Shows Uneven AI Adoption
What to Know:
Anthropic analyzed about 1 million Claude conversations from August 2025 and found that AI adoption is spreading unevenly. California, Washington, D.C., and Utah have the highest per capita use, while southern and plains states are underrepresented. Usage varies by task: Hawaii shows high tourism-related use, D.C. emphasizes job searches and writing, and California centers on coding. Globally, Israel, Singapore, and Canada lead in per capita adoption, while India and Nigeria lag.
In terms of how AI is being used, Anthropic has found that highly skilled workers benefit from using Claude to augment tasks; it also found that lower-income countries lean toward automation rather than augmentation.
Why It Matters:
Anthropic warns that these patterns may concentrate productivity gains in already-rich regions, potentially reversing decades of global growth convergence. Without intervention, AI adoption risks deepening both workforce and geographic inequality.
3. Generative AI at the Crossroads: Light Bulb, Dynamo, or Microscope?
What to Know:
A Brookings working paper says generative AI (GenAI) shares features of two technology types with lasting economic impact. As a general-purpose technology, like the dynamo, it can spread widely, enable new goods and services, and improve continually. As an invention of a new method of invention, like the microscope, it can make research and development more efficient by enhancing observation, analysis, and communication.
Together, these traits suggest that GenAI will raise productivity levels and foster ongoing innovation. Still, the authors caution that the integration of revolutionary technologies into the economy has historically been slow, and adoption patterns will determine how quickly we see any gains.
Why It Matters:
The paper tempers both hype and skepticism. GenAI is positioned to be more than a one-time boost but less than an instant revolution. Its economic benefits will unfold over years, not quarters, requiring patience from policymakers and investors.
4. AI's Economic Boost Isn't Showing Up in GDP, and Goldman Says That's a $115 Billion Blind Spot
What to Know:
Goldman Sachs estimates that AI has lifted U.S. economic activity by $160 billion since 2022, about 0.7% of GDP, but only $45 billion is reflected in official data. The gap comes from how the U.S. Bureau of Economic Analysis treats semiconductors as intermediate inputs, excluding much of the country’s AI investment.
Why It Matters:
Official GDP data is missing most of AI's impact, masking both the scale of corporate investment and productivity gains already underway.
5. Indeed Unveils AI Agents for Job Seekers and Recruiters
What to Know:
Indeed launched Career Scout for candidates and Talent Scout for employers. Career Scout helps with career paths, resumes, applications, and interview prep. Talent Scout sources candidates, integrates with major applicant tracking systems, and uses contextual data to match jobs to potential candidates.
Why It Matters:
By embedding AI agents into both sides of hiring, Indeed aims to improve job market efficiency — but risks adding noise if quality control falls short.
6. ServiceNow Brings Vibe Coding to Enterprise Workflows, Collapsing App Development from Weeks to Minutes
What to Know:
ServiceNow's Zurich release adds vibe coding, letting users build enterprise apps from plain English prompts. The Build Agent auto-tests, handles compliance, and deploys apps in minutes. New AI security consoles monitor APIs, protect sensitive data, and treat AI agents as distinct identities.
Why It Matters:
ServiceNow is betting that enterprises will trade vendor flexibility for integration speed. By collapsing development cycles and tightening governance, it challenges Microsoft and Salesforce in the enterprise AI platform race.
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