Each week, as SHRM’s executive in residence for AI+HI, I scour the media landscape to bring you expert summaries of the biggest AI headlines—and what they mean for you and your business.
1. If You Want Your Team to Use GenAI, Focus on Trust
What to Know:
A recent Deloitte study reveals that only 11% of organizations have successfully embedded generative AI (GenAI) tools into daily workflows, citing trust as a key barrier to adoption. Employees often distrust artificial intelligence due to concerns about data privacy, reliability, and the fear of job displacement.
Deloitte’s pilot program demonstrated that targeted trust-building initiatives—focusing on reliability, transparency, capability, and humanity—can significantly boost employee adoption and return on investment. Interventions such as user education, Q&A sessions, and the showcasing of success stories improved trust by 16% and increased usage metrics.
Why It Matters:
Building trust is essential for integrating GenAI into the workplace. Organizations must prioritize transparency, address employee concerns, and demonstrate the practical benefits of AI to maximize adoption and unlock the potential of these tools for productivity and innovation.
2. 2025 Edelman Trust Barometer: Trust and the Crisis of Grievance
What to Know:
The 2025 Edelman Trust Barometer reveals critical challenges for AI adoption at work, emphasizing trust as a key factor. While business remains the most trusted institution globally, public demands for ethical leadership and societal impact are rising. Employees express heightened concerns about job security due to automation and inadequate reskilling efforts; these grievances against institutions are fueling resistance to AI integration.
The report underscores the need for businesses to address misinformation, economic inequality, and systemic injustices to create a stable environment for adopting transformative technologies, such as AI.
Why It Matters:
Trust is pivotal for AI adoption in the workplace. If leaders fail to address employee fears and societal grievances, resistance to AI will grow, undermining productivity and innovation. Businesses must foster transparency, invest in workforce reskilling, and integrate AI ethically to gain employee buy-in and realize the full potential of AI-driven transformation.
3. Sam Altman and Marc Benioff Want You to See AI as Your Co-Worker
What to Know:
OpenAI CEO Sam Altman and Salesforce CEO Marc Benioff are promoting a vision of AI as a digital co-worker or “AI agent,” suggesting these tools will soon integrate deeply into workforces. Altman predicts AI agents will “join the workforce” by 2025, while Benioff envisions future CEOs managing teams of humans and AI.
However, framing AI as a “worker” raises concerns about job displacement and risks oversimplifying its role as a tool. Critics argue that this rhetoric alienates employees and misrepresents AI’s function, which, like past technologies, automates tasks rather than being a true colleague.
Why It Matters:
As businesses adopt AI, the narrative around AI as a co-worker could create distrust among workers, complicating adoption efforts. Companies should emphasize AI’s role as a tool to augment human capabilities and foster productivity rather than perpetuating unrealistic or unsettling metaphors.
4. The “First AI Software Engineer” Is Bungling the Vast Majority of Tasks
What to Know:
Cognition’s AI software engineer, Devin, touted as the “first AI software engineer,” failed in 70% of assigned tasks during a month-long trial. Despite claims of end-to-end coding capabilities, the AI consistently produced errors, became stuck in technical dead ends, and created overly complex or unusable solutions.
Researchers highlighted a key concern undermining the AI’s reliability: the inability to predict which tasks Devin would succeed in. The findings emphasize a gap between marketing promises and AI’s current practical capabilities, particularly in complex problem-solving.
Why It Matters:
While AI promises to revolutionize technical work, tools like Devin underscore the critical need for human oversight. Overpromising on AI capabilities risks eroding trust, and this trial highlights the importance of clear expectations, rigorous testing, and transparency in deploying AI in high-stakes roles.
5. AI Can Work for Us
What to Know:
In this New York Times guest essay, Reid Hoffman, co-founder of LinkedIn and Inflection AI, argues that AI has the potential to empower humanity by augmenting creativity and labor—not replacing it. Hoffman envisions a future where AI tools analyze users’ digital behaviors and provide insights to improve their decision-making, self-awareness, and productivity.
He highlights the transformative power of AI in turning passive data into actionable resources while acknowledging privacy and ethical concerns. Hoffman calls for AI design that prioritizes individual empowerment over corporate manipulation.
Why It Matters:
AI can revolutionize how we work and live by making personal data a tool for self-improvement and enhanced decision-making. Organizations that adopt AI in ways that prioritize user trust, transparency, and empowerment will unlock greater innovation and productivity.
6. The Rise of the Superworker
What to Know:
Josh Bersin’s concept of the superworker highlights individuals who leverage AI to significantly enhance their productivity and innovation in the workplace. He has identified four archetypes of the superworker:
- Empowered Superworker: Partners with AI for higher output quality, reskilling, and increased pay.
- Efficient Superworker: Uses AI for improved efficiency but experiences minimal job transformation.
- Productive Superworker: Manages AI agents to scale output and create new roles and careers.
- Superworker Manager: Oversees AI-driven systems, enabling operational productivity and workforce optimization.
The framework emphasizes integrating AI into HR systems, redesigning the employee experience, and building dynamic talent models to maximize existing workforce potential.
Why It Matters:
Companies that embrace the superworker model can redefine productivity by blending human skills with AI capabilities. To remain competitive, organizations must invest in reskilling, redesign HR processes, and empower employees to collaborate with AI for superior outcomes.
7. The Two Jobs of the AI Future: Entrepreneur and Researcher
What to Know:
As AI reshapes the workforce, two roles thrive—entrepreneur and researcher, writes Forbes. Both excel in leveraging AI to expand their capabilities. Entrepreneurs focus on solving market problems through innovative applications, while researchers tackle foundational issues to advance knowledge.
These roles allow individuals to “raise the ceiling” as tools enhance productivity, emphasizing creativity and strategic thinking. AI’s transformative power doesn’t eliminate other jobs but adds elements of entrepreneurship and research to various roles, requiring adaptability and a focus on creating value with AI tools.
Why It Matters:
The rise of AI highlights the importance of roles that emphasize creativity, problem-solving, and the leveraging of AI as a tool for innovation. Whether in research or business, the key to thriving in the AI-driven future is embracing roles that expand human potential alongside advancing technology.
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