In today’s edition…

Some large enterprises are finally moving beyond pilot programs, with early adopters proving that executive oversight and structured deployment drive real results. Meanwhile, Highmark Health is training thousands of leaders in AI prompt engineering, signaling a shift from passive adoption to full workforce integration. At the same time, AI-powered employee monitoring is expanding, with businesses using AI to track productivity, assess sentiment, and even inform layoffs—sparking debates over privacy, fairness, and regulation.

Let’s dive in. 👇

ONE // AI at Scale: How Enterprise Early Adopters Are Moving Beyond Pilots

Large organizations are redesigning workflows and governance structures to fully realize generative AI’s benefits. A McKinsey survey finds 75% of large firms actively pursuing an AI strategy have deployed AI in at least one business function, with executive oversight linked to bottom-line impact.

Why It Matters

AI's impact is most profound when organizations rethink operations, governance, and talent strategies. Early adopters are proving that executive leadership and structured deployment drive measurable outcomes. Companies that fail to move beyond pilot programs risk losing competitive ground to those embedding AI at scale.

By the Numbers

• 75% of surveyed firms use AI in at least one business function.

• 30% of AI-deploying firms have CEOs overseeing governance.

• 21% have redesigned workflows to embed AI.

What to Watch

Scaling AI across an enterprise requires structured governance, clear KPIs, and workforce reskilling. Few companies have fully implemented these elements. Hiring and reskilling efforts are growing, but workforce readiness remains uneven. Enterprises will need to move beyond pilots to see meaningful business impact.

The Bottom Line: AI adoption is advancing, but scaling remains the critical challenge. Early adopters offer a roadmap, but few firms have turned AI investments into measurable returns. Success will come to those that invest in governance, workflow transformation, and workforce readiness.

Source: McKinsey

TWO // Large Healthcare Company Trains Thousands of Leaders on AI Prompt Engineering

Highmark Health, a large Pennsylvania-based healthcare company, is pushing AI adoption across its operations, training thousands of employees—including every director and above—on prompt engineering to accelerate generative AI integration. The goal is to embed AI into daily workflows, making it a natural extension of the workforce.

The Details

• Enterprise-wide AI adoption – Highmark deployed Sidekick to 50,000 employees, with 10,000+ active users and 1M+ prompts submitted. Every director-level leader and above is trained in prompt engineering to integrate AI into workflows.

• Improving efficiency in healthcare – Ambient listening AI, tested with 500 clinicians, is reducing documentation time, while agentic workflows are automating routine tasks.

• Scaling with flexibility – A 2020 Google Cloud partnership supports secure AI expansion, while an open AI ecosystem ensures adaptability to new technologies.

Why It Matters

Highmark’s approach provides a roadmap for non-tech companies looking to integrate AI into daily operations. Rather than limiting AI to a small group of specialists, the company is training leaders and employees at all levels to use generative AI effectively.

The Bottom Line: Highmark’s AI strategy is a case study in how businesses can move beyond experimentation and embed AI into everyday operations. The company is training leaders at scale, ensuring employees become fluent in AI-assisted work. This signals a shift from passive AI adoption to active workforce transformation, a move other businesses should consider.

Source: Becker’s Health IT

THREE // AI-Powered Bossware: A New Era of Employee Surveillance

AI-driven employee monitoring software is evolving beyond basic tracking. Companies are integrating AI to analyze productivity, detect sentiment, and even assist in layoffs, raising concerns about privacy, fairness, and workplace trust.

The Details

• AI-driven tracking – Software logs keystrokes, emails, and activity, while sentiment analysis scans communications for stress or dissatisfaction. Some platforms use biometrics to track attendance.

• Shaping employment decisions – AI categorizes activities, flags policy violations, and predicts behaviors like quitting or underperformance. Some companies use this data in layoff decisions.

• Regulatory and employee pushback – Workers are finding ways to bypass tracking, while states like California, Illinois, and New York push for stricter AI monitoring laws.

Why It Matters

AI-driven monitoring is reshaping workplace dynamics, raising concerns about transparency, fairness, and trust. Employees need clarity on how data is collected and used, especially when it influences promotions or layoffs. Without safeguards, AI can misinterpret behavior, leading to biased decisions and legal risks. Poorly managed surveillance can also erode morale and drive employees away. Companies must balance efficiency with responsible implementation to avoid unintended consequences.

The Bottom Line: AI-powered bossware is redefining how companies manage employees, shifting from simple tracking to deeper evaluation and decision-making. Businesses adopting these tools must weigh efficiency against the risks of overreach. Thoughtful implementation that prioritizes trust will determine whether AI drives performance or fuels unwanted turnover and legal challenges.

Source: Computerworld

Extra Credit

For the overachievers: These are the stories that didn’t crack the top three but are too important to ignore—quick hits on what’s happening and why it matters.

Hybrid Intelligence and the Future of Human-AI Collaboration

Key Takeaway: The future belongs to those who blend human intuition with AI’s analytical power. Hybrid intelligence creates new opportunities for leadership, decision-making, and innovation by combining the best of both worlds.

Why It Matters: AI systems reflect the values and priorities of their creators. Leaders who develop expertise in both human psychology and AI’s capabilities will set the standard for responsible innovation. Organizations that embrace this approach will unlock new levels of efficiency, creativity, and impact.

Source: Psychology Today

AI Personalization to Reshape Workplace Productivity Apps

Key Takeaway: AI-powered personalization is set to transform workplace applications, tailoring digital tools to individual work habits and increasing efficiency. By 2028, one in five workplace applications will incorporate adaptive AI algorithms to streamline workflows and improve user satisfaction.

Why It Matters: Employees perform best when digital tools match their needs, yet only 23% express full satisfaction with current workplace applications. AI-driven personalization has the potential to bridge the gap between consumer and enterprise software, offering automated workflows, tailored recommendations, and adaptive interfaces.

Source: Tech Monitor

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