The Next AI Breakthrough Isn’t Another App. It’s a Better-Run Organization.

Organizations have more AI than ever, so why is running a business still so hard?

AI can help people analyze information, generate reports, and explore recommendations in seconds. Yet, hospitals still face staffing pressures, retailers still contend with unpredictable labor demand, and managers still balance cost, compliance, and employee needs as conditions change.

The challenge is not simply a shortage of intelligence. It is applying intelligence to the many connected decisions that determine how an organization operates.

Despite the increased access to AI, there is still a gap between AI adoption and business transformation. Boston Consulting Group finds just 5% of organizations achieved AI value at scale in 2025, while 60% reported achieving no material value - with minimal revenue and cost gains after substantial investment.

Until now, organizations have focused on the wrong areas of opportunity for AI. Success will not come from just adding more AI. It is about connecting AI to the work and decisions that shape operating performance.

The real operational challenge is that work does not stand still

Traditional enterprise systems have been built to record, plan, and report. But workforce operations are dynamic, especially across the frontline. Employees call out. Customer demand changes. Overtime increases. Regulations and business requirements constrain the available options.

A decision that made sense in the morning may no longer be right or even relevant by the afternoon.

Those changes have real operational consequences. McKinsey & Company estimates that, for U.S. manufacturers, the cost of frontline labor challenges can range from $17,000 to $30,000 per active employee. That includes costs such as recruiting, training, shift coverage, and lost production. This scale underscores why workforce operations belong in strategic performance discussions, and not only in conversations about administrative efficiency.

Organizations need to continuously identify what is happening, evaluate the tradeoffs, and respond within the realities of their business. That calls for a shift from periodic planning and reactive problem-solving toward a more continuous way to coordinate workforce decisions.

Workforce intelligence becomes transformational when it can inform action

Better AI reasoning matters. But consequential workforce decisions require specialized operational context. Leaders must understand who is available, who is qualified, how people are scheduled and paid, which rules apply, and what consequences may follow from a decision - all in minutes, not months.

Workforce intelligence makes those relationships visible. Connected to the systems and workflows that run the business, it can help leaders evaluate alternatives and coordinate appropriate responses within established policies and permissions.

Consider a chief operating officer (COO) investigating rising labor costs across plant locations. A useful answer needs to do more than identify a trend. It should help the leader understand what is driving the increase and evaluate options in light of staffing needs, employee availability, business rules, and operational goals.

Not every decision should be automated, however. People make better, more informed decisions when trusted intelligence is connected to the realities of the work.

Extensible AI changes where - and how - work gets done

Organizations should not have to send everyone to another application to benefit from AI. Executives, managers, and employees have different needs and may work in different experiences. The real AI opportunity stems from making trusted workforce intelligence and supported actions available across those experiences, while keeping them connected to the same business logic, permissions, and governance.

An executive might explore a workforce question in an AI experience. A manager might resolve a staffing challenge within an operational application. An employee might complete an appropriate workforce task through a familiar digital or voice experience. The interfaces may vary, but the intelligence and underlying system of action remain connected.

That is the business idea behind extensible AI: AI capabilities reach more people and moments of work without becoming another disconnected layer. The value comes from extending access to the intelligence and workflows that help work move forward - not from the interface alone.

The ultimate AI breakthrough is an organization that operates better

The next measure of AI success should be more than how many employees use it or how many hours it saves. Meaningful KPIs capture how well the organization performs as a result.

• Can a business respond to staffing shortages before service suffers?
• Can the organization reduce avoidable labor expenses while accounting for employee needs?
• Can leaders provide managers with better options when conditions change?
• Can those improvements reach frontline employees - and even those who may never personally interact with frontier AI?

Those questions keep the focus on outcomes. Better workforce decisions can improve responsiveness, support managers, and shape employee experiences. But those outcomes depend on using reliable context, respecting the rules that govern decisions, and keeping people accountable for choices that require judgment.

AI's largest opportunity is to help organizations and their leaders make smarter decisions, act faster, and achieve business results at a scale no individual can alone. The ultimate AI breakthrough comes from how much better the organization operates - and how many people benefit because of it.