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.
AI now touches every layer of work. It is changing how expertise is defined, how leaders spend their time, how companies hire, and how people connect. The question is no longer how to use it, but how to stay human while doing so. The first shift is in how we define knowledge and value.
What to Know:
Ravikiran Kalluri, assistant teaching professor at Northeastern University, argues that AI is democratizing knowledge and forcing a redefinition of expertise. With generative AI (GenAI) tools providing instant access to information once reserved for specialists, the value of experts is shifting from knowing facts to exercising meta-expertise — the ability to synthesize insights across domains, ask better questions, and make creative, ethical decisions.
As organizations flatten hierarchies and embed AI into workflows, roles are evolving toward orchestration rather than accumulation of knowledge. Kalluri warns of "cognitive outsourcing," where overreliance on AI erodes judgment and creativity, and calls for preserving "cognitive sovereignty" through deliberate human thinking, cross-disciplinary learning, and ethical reasoning.
Why It Matters:
In an age of abundant information, human advantage lies not in access but in discernment. The leaders who will thrive are those who cultivate teams that pair AI efficiency with uniquely human skills: curiosity, creativity, and moral judgment.
As expertise evolves, leadership itself is being redefined.
What to Know:
The authors of this Harvard Business Review article argue that GenAI can help rebuild trust and engagement by freeing leaders to focus on the human side of management. Employee trust and engagement are at decade lows, and only 16% of leaders demonstrate strong "human leadership" skills such as empathy, communication, and self-awareness.
The authors highlight IBM's approach: using AI to automate administrative HR tasks and redirect leaders' time toward coaching, feedback, and connection. IBM now measures leaders on "people" behaviors such as authenticity, courage, and care, supported by 360-degree feedback and new AI-enabled learning tools. GenAI is also used as a coaching resource to help leaders prepare for conversations and reflect on bias without replacing genuine presence.
Why It Matters:
AI can either distance leaders from their teams or create space for deeper connection. Companies that treat time saved through automation as an investment in human leadership — not efficiency — will build trust, retention, and stronger cultures.
The next change is visible in the labor market, where the definition of talent is shifting as fast as the tools themselves.
What to Know:
More than 70% of early-stage founders are increasing their AI spending, a trend that is reshaping both startup operations and hiring. John Dearie of the Center for American Entrepreneurship says that founders are automating energy- and human-intensive tasks such as sales, marketing, and operations to stay lean.
Some founders, including Productions.com CEO Carolyn Pitt, now use AI in place of interns, letting the tech handle entry-level work. While this reduces early-career hiring, startups are also recruiting workers fluent in AI tools — especially younger employees who use AI naturally. The "ideal" hire is now a senior professional who can manage AI systems and apply creative judgment. Meanwhile, the rise of contract work continues as founders hedge against rapid AI change, using flexible talent instead of permanent staff.
Why It Matters:
AI is redrawing the labor map of entrepreneurship — compressing entry-level roles while increasing demand for experienced, adaptive workers. The startup economy that once expanded opportunity may now be concentrating it among those who can both command and complement AI.
As work gets reorganized around technology, the question turns personal: What happens to meaning and connection when machines start to simulate care?
What to Know:
Adam Grant, an organizational psychologist at Wharton, argues that AI chatbots are designed for emotional gratification, not genuine connection. Seventy-two percent of teens have used AI companions, and nearly one-third find them as satisfying as — or more satisfying than — human interaction. Grant says the real flaw isn't that AI over-validates users but that the relationships it simulates are one-sided.
Humans need to feel they matter — to add value, not just receive it. Healthy relationships depend on reciprocity and care, yet AI has no needs, no growth, and nothing for users to give. Even the 1990s Tamagotchi offered more feedback, he notes — it thrived or died based on human action. AI companions may be useful for practice or support, but they cannot provide mutuality or the moral work that makes friendship meaningful.
Why It Matters:
As AI begins to fill social and emotional roles, the risk isn't dependency — it's disconnection. By removing reciprocity from relationships, AI companionship could erode empathy and the human capacity to care.