People Judge Users of ChatGPT as Less Warm, Not Just Distrusting the AI
Research from eight studies shows that people who use ChatGPT or similar AI tools for advice are judged as colder or less personable. This judgment affects workplace dynamics, including hiring decisions and openness to adopting AI technology.
Bridging the Gap: Why Data Science Alone Falls Short Without Decision Science
Many data science projects fail because they focus on predictions without addressing the real business decisions managers face. Decision science bridges this gap by modeling actual managerial choices, aligning analytics with business goals, and providing actionable recommendations. Integrating decision science with data science enhances problem framing, data relevance, and metrics that matter, helping organizations transform data insights into impactful business decisions. Leaders should foster collaboration between these fields to drive ROI and strategic success.
Bridging the Gap: Why Boards Need Both AI Expertise and Effective Oversight
The rise of AI as a business risk highlights a gap in board expertise and oversight. Fewer than 3% of directors have AI knowledge, yet boards must oversee complex AI risks across multiple domains. Recruiting experts alone isn’t enough; effective AI governance requires distributed oversight, measuring actual director actions, and ensuring minimum competency standards across the board. Boards must build depth and shared accountability in key AI areas to protect companies and manage AI responsibly.
When AI Stumbles, Who Steps Up to Fix the Fallout?
As AI takes on more complex tasks, employees may gradually lose the skills required to step in when AI fails, creating a latent risk. The shift from active work to oversight changes accountability and capabilities, demanding organizations rethink training and governance to maintain critical human judgment for when AI reaches its limits.
Preserving Human Judgment in the Age of Advanced AI: The Key Challenge for Responsible AI Design
A global panel of AI experts highlights the critical challenge of responsible AI: preserving human judgment amid increasingly capable AI systems. While AI offers speed and scale, human judgment provides essential context, wisdom, and accountability, especially in high-stakes situations. Experts caution against overreliance on AI, which can erode critical thinking and ethical decision-making skills. They recommend designing human-machine collaboration systems that deliberately preserve opportunities for human judgment through thoughtful system design, targeted training, and continuous feedback. The goal is to maintain trusted human agency and oversight where it matters most, ensuring AI complements rather than replaces human decision-making.
When Employees Bring Their AI Agents to Work: The Hidden Dangers and What Leaders Must Do
Personal AI agents, now widely adopted, boost productivity but pose significant risks when connected to company systems—data leaks, unauthorized control, and security breaches are common threats. Business leaders must immediately identify AI tool usage, set strict access rules, require human oversight on critical actions, and practice secure disconnection. Without proactive policies, companies face growing vulnerabilities as AI agents become everyday workplace tools.
The Crucial Role of a Pacer in High-Performing Leadership
High-performing leaders, much like elite athletes, benefit massively from having a pacer to help regulate their pace—slowing down, speeding up, or maintaining the right tempo. A pacer assists leaders in making better decisions, sticking to strategy, and managing team energy, which prevents burnout and disengagement. Research shows many leaders lack such support, leading to pace-related issues that hurt performance. The right pacer is trustworthy, knowledgeable, and context-aware, coming from various roles depending on leadership needs. Ultimately, pacers help leaders develop internal pacing, enabling sustainable, effective leadership.
Navigating Brand Presence and Precision in the Era of AI-Driven Search
As AI-driven search reshapes digital discovery, companies face new challenges in ensuring their brand's visibility and accuracy in AI-generated answers. Research highlights common pitfalls like outdated content and organizational inertia. Generative Engine Optimization (GEO) emerges as a strategic practice requiring brands to make content AI-friendly, monitor AI responses rigorously, and manage both owned and third-party digital presence. By adopting systematic audits and new metrics, businesses can safeguard their reputation, turning AI visibility into a competitive edge as search evolves beyond clicks to accurate brand representation.
Redefining Leadership in the Age of AI-Driven Companies
As AI takes on more operational decisions, leadership shifts from managing tasks to setting clear objectives and trade-offs for adaptive systems. Leaders become architects of company governance, balancing priorities and fostering culture to guide AI optimization. This new leadership role focuses on defining what truly matters and steering organizational purpose amid continuous learning and change.
Why a Supportive Manager Outweighs Remote Work in Job Satisfaction
Research indicates that good relationships with managers have a stronger impact on job satisfaction than whether employees work remotely or in the office. Supportive leadership, clear communication, and fair pay are key to happier, less burned-out employees. While remote work offers flexibility, it can also increase social isolation and does not automatically improve satisfaction without strong workplace support.
Rebuilding Trust in HR: Why Leadership Must Take Charge of Employee Well-Being
Trust in HR to advocate for employees is low because HR is often caught between employee interests and tough business decisions. To improve well-being, companies need senior leaders with real authority to own the issue, use frequent pulse surveys for timely feedback, and hold managers accountable. HR should manage the system, while leadership drives outcomes. Prioritizing well-being as a core business focus fuels better leadership and a stronger workplace culture.
Starbucks CEO Brian Niccol’s Leadership Revival: Back to Core Values for Company Success
Starbucks’ CEO Brian Niccol drives the company’s comeback by focusing on its foundational strengths—better coffee, faster service, inviting stores, and strong employee support. His leadership highlights the importance of simple, core business principles and investing in staff to enhance customer experience, resulting in renewed growth and momentum.
When Compliance Workarounds Fail: Lessons from Algorithmic Business Models
This article examines how minimal compliance workarounds in algorithmic businesses, like Glovo’s response to Spain’s Rider Law, can fail and lead to costly redesigns. It identifies four warning signs—tightening legal rules, visible harm, increased scrutiny, and rising complexity—that signal when limited fixes are insufficient. Drawing on cases including Deliveroo, Airbnb, Uber, and Meta, it highlights the need for durable compliance through product integration, meaningful human oversight, and continuous monitoring. Leaders should carefully evaluate regulatory demands, test impacts, and prepare for potential redesigns to maintain strategic control and avoid escalating costs.
Understanding Why Digital Projects Often Miss the Mark: Key Insights for Leaders
Digital projects often fail due to confusion between data quality and system usability, which affect user cognitive load in distinct ways. Research shows that good data promotes deep engagement necessary for quality decisions, while good system design reduces mental effort caused by poor navigation and alerts. Addressing only one leads to frustration and subpar results. Leaders must evaluate digital tools by how well they support cognitive processes, focusing on eliminating data redundancies, clear data lineage, essential data fields, and smart alert thresholds to improve user experience and decision outcomes. This approach is crucial for successful AI integration and overall digital investment returns.
Rehearsing Crisis Readiness with Digital Twins: Unlocking Rehearsal Intelligence
The article examines the urgent need for organizations to use digital twins—not just for operations but for continuous crisis rehearsal—to prepare for unforeseen disruptions. Highlighting costly failures in 2024 and a lack of crisis simulation adoption among security professionals, it argues traditional exercises and AI alone are insufficient. A five-step framework is offered to help companies transition from reactive plans to anticipatory crisis management, improving resilience, decision-making, and risk response. Successful examples include BMW and Walmart, emphasizing leadership's key role in enabling this strategic shift.
Establishing a Clear AI Performance Scoreboard for Strategic Business Impact
Companies must move beyond basic AI tasks to strategic use by establishing clear, continuous evaluation focused on real business outcomes rather than outputs. Effective AI optimization needs precise goals and feedback loops, similar to AlphaZero's learning through trial and error. CEOs should ask what the AI optimizes and how it improves the business to ensure meaningful impact.
Trump Appoints Jay Clayton as White House AI Czar Amid Growing AI Concerns
Donald Trump has named Jay Clayton, director of national intelligence, as the White House AI czar. Clayton, who oversees the US intelligence agencies, has acknowledged AI's transformative potential and risks. He has also served as Manhattan's top federal prosecutor and headed the SEC during Trump's first term.
Why AI Alone Can't Fix Broken Business Processes
AI is powerful for automating tasks and detecting problems quickly, but it can't fix a business with broken or inefficient processes. Successful transformation starts with optimizing workflows before implementing AI technologies.
Rising Pressure on CMOs as Their Tenures Shorten and Responsibilities Grow
A recent study reveals that CMOs are under increasing pressure as their average tenure decreases and job demands multiply. Notably, new marketers tend to have stronger AI skills than longer-serving CMOs, indicating a shift in the expertise required in marketing leadership roles.
Ryan Roslansky Steps Down from Leadership Roles at Microsoft and LinkedIn
Ryan Roslansky, having served nearly 18 years at LinkedIn and Microsoft, is leaving after leading LinkedIn and heading Microsoft Office and Teams. His departure has sparked leadership changes, with CEO Satya Nadella acknowledging Roslansky's role in strengthening the company's product and design foundations.