ONE // AI Is Reshaping the Economics of Expertise

For centuries, expertise has been expensive and scarce. AI is beginning to change that. AI tools like ChatGPT’s Deep Research challenge the idea that human insight is scarce.

Why It Matters

Organizations are still treating AI as a cost-cutting tool rather than a strategic asset for driving innovation. While many companies use AI for automating customer support, few leverage it for high-value functions like R&D, market strategy, and product development.

Between the Lines

• AI's impact mirrors past revolutions in knowledge distribution—from the printing press to the internet. Each time, productivity and innovation soared.

• Early AI skeptics dismissed large language models as “stochastic parrots,” but recent advances in reasoning models now rival human PhDs in complex problem-solving.

• AI is shifting from automating routine tasks to accelerating high-value decision-making, enabling companies to fail faster, iterate quicker, and refine strategies with machine-speed intelligence.

The Bottom Line: AI is removing long-standing constraints on expertise, making advanced problem-solving faster and more accessible. Companies that look beyond automation and cost-cutting, using AI to enhance decision-making and drive innovation, will have a clear competitive advantage.

Source: Bloomberg

TWO // AI Reshapes Hiring and Skills, Forcing Workers to Adapt

Predictions of mass AI-driven unemployment have been circulating for over a decade, yet history tells a different story. From the Industrial Revolution to the Internet, technological advances have increased productivity, shifted job roles, and created new opportunities. With AI, the real question isn’t just how many jobs it might replace, but how businesses, workers, and policymakers will adapt.

By the Numbers

• 40% of global jobs are “exposed” to AI, per the IMF.

• 300 million jobs could be “lost or degraded,” per Goldman Sachs.

• 19% of U.S. workers have jobs in AI’s most exposed category, per Pew Research Center.

The Big Question

Despite the hype, only 5% of U.S. businesses currently use AI in production, and the scale of job displacement will depend on when, where, and how companies adopt it—factors that remain uncertain. Still, AI is already reshaping the workforce. It played a role in the sweeping tech layoffs of the past two years, and some CEOs have privately indicated plans to restructure and reduce engineering teams as AI takes on a larger role in production. While public forecasts remain mixed, behind closed doors, many business leaders are bracing for a major shift.

Why It’s Complicated

• Exposure vs. Displacement: Just because a job is "exposed" to AI does not mean it will disappear. Adoption is expensive, and companies must see a clear return on investment.

• The Firm Factor: Businesses, not individuals, drive automation. If AI adoption is slow, the feared job losses may not materialize.

• Price Elasticity Wildcard: Automation could lower costs and spur demand, creating new jobs—just as it did in manufacturing.

The Bottom Line: AI will reshape work, but predictions of mass unemployment may be overstated. Rather than resisting change, businesses and policymakers should focus on retraining workers and fostering innovation-friendly policies to ensure AI becomes a tool for economic growth—not a job killer.

Source: Fortune [hybrid paywall]

THREE // Corporate Speak Goes AI: Machines Takeover Business Communication

A comprehensive study by Stanford and the University of Washington reveals that AI-driven text generation is now deeply embedded in corporate and institutional communication. From press releases to job postings, businesses and governments are increasingly relying on generative AI (LLMs) to draft content. However, after an initial surge following ChatGPT’s release in late 2022, adoption rates have plateaued, suggesting that either market saturation or improved AI sophistication is making machine-generated text harder to detect.

By the Numbers:

• 18% of financial consumer complaints are now AI-assisted.

• 24% of corporate press releases contain LLM-generated content.

• 10-15% of job postings, particularly from small and young firms, are AI-assisted.

• 14% of United Nations press releases show signs of AI modification.

The Macro View: The findings highlight a shift in how organizations produce written content, with cost and efficiency driving adoption. Yet, the study raises questions about trust, authenticity, and the homogenization of corporate messaging. While AI-generated text enables faster content production, it may also reduce the perceived credibility of business communication.

What’s Next: Companies and regulators may soon need to define transparency guidelines around AI-generated content, particularly as consumers and investors demand clarity on whether they are engaging with human-crafted or machine-generated messaging.

The Bottom Line: AI-generated content is becoming a fixture in corporate communication, improving efficiency but raising concerns about trust and authenticity. As machine-generated text becomes harder to detect, businesses will need to balance automation with transparency to maintain credibility.

Source: Liang, W., Zhang, Y., Codreanu, M., Wang, J., Cao, H., & Zou, J. (2025). "The Widespread Adoption of Large Language Model-Assisted Writing Across Society."

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