Mohammad Nazzal

Artificial intelligence has been celebrated for accelerating knowledge creation and improving information access. Yet new research reveals a more complex;and potentially hazardous reality. While AI and digital platforms increase the efficiency of processing and distributing information, they simultaneously undermine the economic foundations that sustain high-quality journalism, fact-based research, and the broader information ecosystem. Their dominance reduces incentives for truthful content creation, amplifies misinformation, and risks triggering a long-term “information collapse.” This article distills key insights from Stiglitz & Ventura-Bolet’s work on the evolving information ecosystem and examines why leaders, policymakers, and knowledge-intensive organizations must respond strategically to prevent a degradation of public knowledge.

Artificial intelligence holds the promise of accelerating scientific discovery, engineering breakthroughs, and productivity across industries. Yet the magnitude of its impact depends on three factors: the share of research tasks AI can perform, how productive AI is at those tasks, and the bottlenecks that limit overall progress. The paper presents a structured model showing that even extremely powerful AI produces limited gains if it operates on only a minority of research tasks. Conversely, broad automation across the research pipeline—far more than incremental improvements—determines whether AI can create transformative outcomes. The framework helps leaders, policymakers, and research organizations evaluate where AI will meaningfully accelerate progress and where constraints will sharply mute returns.

Summary: Securing investment remains one of the most substantial factors of growth for startups and established firms alike. While pitch decks, financial projections, and strategy outlines are common, one tool that consistently resonates with investors is the SWOT analysis. Despite its popularity, SWOT is often relegated to a formality and misunderstood. Consider a founder pitching in Silicon Valley growing tech ecosystem. The financials are sound, but when the SWOT slide appears, investors tune out as it lists the same generic strengths and threats they have seen dozens of times before. This article argues that by combining traditional SWOT frameworks with real-time data through artificial intelligence (AI) and machine learning (ML), organizations can unlock their full potential. This article lays out the solution: embed AI and ML into SWOT to quantify what matters, prioritize it with weighted scoring, and refresh it quarterly so the analysis stays credible.

Physical IT or IT Skills? Erik Brynjolfsson, Wang Jin, Sebastian Steffen created a novel IT measurements based on industry and firm-level demands for IT skills and occupations from 2010 until 2022. The preference preferred firm-level estimation implies that a one percent increase in IT skills is associated with a 0.009 percent increase in total sales, which translates to an average gain of $540,000 per firm.

Friend or Foe? Ginger Zhe Jin, Mario Leccese, Liad Wagman discussed interactions between top digital platforms such as GAFAM (Google, Apple, Meta, Amazon, Microsoft) and technology ventures startups across capital, labor, innovation, product markets, the potential of collaboration, and how competitive behaviors can shape the innovation ecosystem.

Junior or Senior? Erik Brynjolfsson, Danieelle Li, Lindsey R. Raymond measured the new AI tools that has the have the potential to change the way workers perform and learn, but little is known about their impacts on the job. They studied the staggered introduction of a generative AI-based conversational assistant using data from 5,179 customer support agents. The results have shown 34% improvement for novice and low-skilled workers but with minimal impact on experienced and senior workers.