It’s true: Leaders using AI are Winning. From the 1980s through the early 2010s, people constantly warned that robots would take our jobs. Then, it was computers. Now, the fear is AI. While I’m no fortune teller, history suggests that the doomsayers may once again be wrong. AI is certainly different—it will transform our world—but not in the ways we expect. Let this article serve as a call to action for organizational leaders.
I recently participated in a monthly call with over 40 executives. The purpose of the call was to provide a platform for senior leaders to discuss best practices, challenges, and organizational issues while supporting one another. As I looked around the virtual room, I noticed that most participants were in their 50s to 70s—seasoned executives with decades of experience. The facilitator posed a simple yet revealing question: “How are you all using AI?” Silence.
This aligns with a McKinsey report from January, which found that executive leaders are slower to embrace AI than their employees. The hesitation is understandable, but it’s also a missed opportunity.
In my consulting work, I don’t simply advise organizations or fix their problems—I teach them how to solve their own. This approach takes a little longer but yields lasting results, equipping teams with valuable skills and tools. AI is one such tool, and I incorporate it into every engagement. Below is a roadmap of how I do so. This is my “secret sauce,” and I’m sharing it because I believe in modeling the behavior I want to see in the world. There is no “us versus them” when it comes to AI. We all rise with the tide.
How I Use AI in My Work
- Writing Proposals – AI helps me develop customized templates, proofread for grammar and spelling, and enhance clarity. (When was the last time Microsoft Word had a meaningful update—ten years ago?)
- Researching Trends and Best Practices – AI assists in identifying emerging issues, considerations, and approaches to proposals and projects.
- Summarizing Notes – I take notes during calls, interviews, and site visits using Excel. Then, I upload them to ChatGPT for concise summaries that would take me hours to craft manually.
- Identifying Blind Spots – AI helps me consider factors, circumstances, and nuances I might have missed in my initial assessment of a problem.
- Refining Reports – I write my reports, then run them through AI for improved clarity and conciseness.
- Empowering Clients – I often show clients how to leverage AI. For example, a nonprofit leader can upload their IRS Form 990 to ChatGPT and ask for benchmarking and analysis—saving hours of manual effort.
By now, you get the idea. I’m not an AI power user, but I am a strong advocate for using tools that enhance the quality and efficiency of work.
A Parting Gift
To demonstrate AI’s creative potential, I took 30 seconds to ask ChatGPT to write a song about my business. Then, I pasted the lyrics into Suno (look it up). The result? A promotional song that’s surprisingly good. Listen to it HERE.
AI is not the enemy—it’s an asset. Leaders who embrace it will gain a competitive edge. The question isn’t whether AI will shape the future of work; it’s whether you’ll be leading that change or struggling to keep up.
A Second Parting Gift
An AI summary of a free report published by a big 4 consulting firm in January:
Detailed Summary of “Superagency in the Workplace: Empowering People to Unlock AI’s Full Potential”
Introduction
The report examines the transformative role of AI in the workplace, drawing parallels to historic technological revolutions like the steam engine. Despite significant investment—92% of companies plan to increase AI funding over the next three years—only 1% of business leaders consider their companies mature in AI deployment. The central challenge is not employee readiness; rather, leadership is failing to act swiftly enough to integrate AI effectively.
Key Insights and Findings
1. AI is a Transformational Force in the Workplace
AI has the potential to redefine work by automating not only routine tasks but also cognitive functions. The development of large language models (LLMs) by companies like OpenAI, Google, and Meta signifies a new era of information technology. The report cites McKinsey’s research, estimating AI could contribute up to $4.4 trillion in productivity gains across industries. However, this opportunity remains untapped due to a slow rate of adoption and integration.
2. Employees are More Ready for AI than Leaders Expect
A major finding is the disparity between employee enthusiasm for AI and leadership perceptions:
- Employees use AI three times more than leaders estimate, with many already incorporating it into at least 30% of their daily tasks.
- Millennials (aged 35-44) are AI’s strongest advocates, demonstrating higher familiarity and confidence compared to other generations.
- Employees want training and support—48% cite training as the most important factor for AI adoption, yet many feel they receive minimal organizational support.
- Leaders underestimate AI’s impact on work—47% of employees believe AI will change at least 30% of their tasks within two years, compared to only 20% of leaders who think the same.
3. The Speed vs. Safety Dilemma in AI Deployment
Leaders struggle to balance the rapid adoption of AI with concerns about security, accuracy, and regulation:
- 47% of C-suite executives believe their companies are developing AI too slowly, citing talent skill gaps as a primary barrier.
- Employees trust their companies more than other institutions to get AI right—71% of workers have faith in their employers’ ethical deployment of AI, compared to 61% who trust large tech companies.
- Top employee concerns about AI include cybersecurity (51%), inaccuracies (50%), and data privacy (43%). These fears contribute to cautious implementation despite the pressure to innovate.
4. Bold Ambitions are Needed for AI to Deliver Value
Many organizations struggle to scale AI beyond pilot projects:
- Only 1% of companies have reached AI maturity, where AI is fully integrated into workflows and driving substantial business outcomes.
- Industry differences in AI investment—Technology, healthcare, and media lead in AI spending, while consumer goods, energy, and logistics lag behind.
- AI has not yet delivered substantial ROI—Only 19% of executives report a revenue increase of more than 5% from AI, though 87% expect AI to boost revenues significantly in the next three years.
- Some industries remain skeptical—Public sector employees, as well as those in aerospace and defense, show the least optimism about AI’s workplace impact.
5. Leadership and Organizational Challenges
The report highlights that AI’s biggest obstacles are not technical but managerial:
- Leadership misalignment slows execution—Many companies lack a clear AI roadmap, with only 25% having a fully defined AI strategy.
- Cost uncertainty complicates scaling—While initial AI pilots are relatively inexpensive, scaling AI enterprise-wide introduces unpredictable costs.
- Workforce planning is a major challenge—Leaders are unsure how many AI specialists they need or how to reskill existing employees.
- Supply chain risks—AI’s development depends on a complex global supply chain, making companies vulnerable to regulatory, geopolitical, and technological disruptions.
- Demand for AI transparency and explainability—Most AI models function as “black boxes,” limiting trust and adoption in sensitive areas like finance and healthcare.
6. The Need for a Strategic Approach to AI Integration
The report calls for a “rewired” approach to AI adoption, emphasizing six pillars of transformation:
- A Business-Led AI Roadmap – Leadership must align on a clear vision for AI and its value proposition.
- Scalable Activation – Companies need robust change management strategies to move AI from pilots to enterprise-wide solutions.
- Talent Development – Upskilling employees is critical, as 46% of executives cite skill gaps as a major AI adoption barrier.
- A New Operating Model – AI should be embedded into workflows, requiring cross-functional collaboration.
- Advanced Data & AI Infrastructure – Companies need high-quality data to train AI models effectively.
- Governance & Benchmarking – AI performance and ethical considerations should be continuously monitored using third-party benchmarks.
Conclusion: Meeting the AI Future
The report concludes that AI presents a rare and powerful opportunity, but its success depends on bold leadership, strategic investment, and workforce empowerment. Organizations that fail to act decisively risk falling behind competitors who successfully harness AI’s full potential.
Final Takeaways
- AI adoption is inevitable and will fundamentally reshape industries.
- Employees are eager for AI, but leadership must step up to accelerate deployment.
- Companies need to balance speed with safety, ensuring AI’s ethical and effective use.
- Strategic ambition and execution are key—businesses must rethink workflows, invest in training, and build AI governance frameworks to maximize impact.
The message is clear: The risk isn’t thinking too big about AI—it’s thinking too small.