It is easy to blame “big bad pharma” for everything that is wrong with healthcare. It is worth remembering that prescription drugs represent only one piece of the total healthcare-cost equation.

To many, it is just as easy to blame the doctors, nurses, technicians, administrators, and thousands of other employees working inside large healthcare systems.

Healthcare is expensive. It is complicated. There are egos, inefficiencies, mistakes, long waits, confusing bills, aging facilities, staffing shortages, and dozens of other things that make healthcare providers easy targets for criticism.

Until you need them. Then it becomes a very different story. I recently had the opportunity, although “opportunity” probably isn't the word I would have chosen,  to experience the healthcare system from the other side. And it caused me to rethink something I have been teaching for decades.

 Short, AI-powered business simulations that prepare teams for real customer conversations. 

The modern customer has fundamentally changed the way they buy and behave, forever changing the sales process.

The new customer no longer needs sales professionals to explain product specifications, compare features, or provide information that can be found in seconds with an AI assistant. Before the first meeting ever takes place, customers have already researched your company, evaluated your competitors, read analyst reports, explored your competitors' websites, and formed opinions about the solutions available to them.

What they cannot easily find is someone who understands their business.

Someone who appreciates the financial pressures they face, the strategic initiatives consuming their leadership team's attention, the operational challenges limiting growth, and the difficult trade-offs they make every day.

That is why the definition of a great salesperson is changing.

The most successful commercial professionals are no longer simply product experts. They are business advisors. They create value by helping customers solve business problems, not by explaining product features.

The question for commercial leaders is straightforward:

If you asked 100 people in the United States today who was responsible for the recent Cyclospora outbreak linked to Taco Bell restaurants, I suspect that almost all of them would answer, "Taylor
Farms."

The challenge is that the story became much more complicated.

Just one day after announcing that lettuce supplied by Taylor Farms de Mexico had tested positive for Cyclospora, the FDA issued an update stating that its laboratory experts had re-reviewed the results and concluded that the finding was actually a false positive. As of July 19, there were no confirmed positive product samples for Cyclospora. The investigation into the outbreak continued, but the initial laboratory finding that dominated the headlines had been withdrawn.

Unfortunately, corrections rarely receive the same attention as the headline-grabbing original story.

By the time the clarification was released, millions of consumers had already formed an opinion. For many, the damage to the brand had already occurred.

That should concern every business leader.

I have a prediction.

Over the next decade, AI won't just change the way we work. It will fundamentally change what we expect from one another at work.

And in doing so, it will redefine the concept of emotional intelligence.

That may sound strange coming from someone whose career has been built around developing business leaders through digital, hands-on business simulations and role-plays to build emotional intelligence. After all, emotional intelligence has long been considered one of the defining characteristics of effective leadership. The ability to read the room, adapt your communication style, build trust, navigate conflict, and motivate different personalities has become the foundation of a multi-billion-dollar leadership development industry.

Those skills are still incredibly important. But I believe we're about to add another dimension to emotional intelligence, one that AI is quietly teaching us every day.

Wasted energy, resources, time, or cash will eventually destroy even the best business strategy.

Every dollar spent on unnecessary work, every hour lost to poor coordination, and every decision delayed by incomplete information creates friction inside the organization. Over time, that friction compounds, reducing profitability, slowing innovation, frustrating customers, and ultimately diminishing shareholder value.

The antidote is operational efficiency.

When most leaders hear the term "operational efficiency," they immediately think about cost reduction. They picture lean operations, lower headcount, tighter budgets, and squeezing expenses wherever possible.

But the most successful organizations understand something different.

Operational efficiency is not simply about lowering costs. It is about creating a system where people, processes, technology, and resources work together to deliver maximum value to customers. When done well, operational efficiency improves quality, accelerates innovation, strengthens customer relationships, increases profitability, improves cash flow, and creates sustainable competitive advantage.

In other words, operational efficiency is one of the most important enablers of business strategy.

And today, artificial intelligence is rapidly becoming one of the most powerful tools available to improve operational efficiency across the enterprise.

Based on our recent work helping organizations build business acumen and leadership skills in the age of AI, here are five practical ways AI can improve operational efficiency while supporting the execution of business strategy.