Much of the media’s attention has centered on Kevin Hassett and Kevin Warsh as the presumptive front-runners to be next Fed Chair. Both are highly respected, with long track records of public service and honorable character. But whether fairly or not, their perceived weaknesses have been under a magnifying glass, creating an opening for an ascendant dark horse who is drawing growing backing from the top CEOs of the nation’s largest enterprises.

CEOs are gravitating towards that dark horse candidate, current Fed Governor Chris Waller, because while he may lack the White House network of other top contenders; he is quickly emerging as perhaps the only candidate who can cut interest rates with broad-based credibility and build broad consensus around those needed rate cuts, both at the Fed as well as across corporate America and within financial markets.

A great irony in President Trump’s jawboning of the Fed is that Trump is perhaps his own worst enemy in trying to force interest rates down. Ironically, the belief that interest rates need to come down is shared not only among economists across ideological anchoring, and not only among many top business leaders, but even many of Trump’s most vocal critics. We have previously written several publications calling for the Fed to lower interest rates, pointing out that entire sectors, such as homebuilders, are getting hammered unnecessarily from holding rates so high for so long.

CEOs care about interest rates coming down, but they care even more about Fed independence. History is clear: countries that politicize their central banks set themselves on a path towards monetary purgatory and collapse. That’s why Trump’s brazen interventions at the Fed have wreaked havoc in the markets, with bond investors in active revolt and with long-term bond yields rising by 20 basis points after some pointed commentary from Trump.

Chris Waller is perhaps the only choice for Fed Chair who can thread the needle. Unlike other top contenders, Waller’s calls for rates to come down reflect not convenient political posturing nor obsequious flattery, but genuine intellectual conviction. Waller has been incredibly consistent and correctly prescient across his entire career at the Fed; he correctly pointed to signs that the economy, and in particular employment, was softening, and has been calling for rates to come down for far longer than any of his peers at the Fed.

Yet, at the same time, Waller has emphasized and defended central bank independence time and time again, building off his own academic research which was focused on the importance of central bank independence. Indeed, prior to Waller’s public service at the Fed starting in 2009, he was a renowned academic with a long track record of groundbreaking economic research, including as professor and the Gilbert F. Schaefer Chair of Economics at the University of Notre Dame.

Financial markets have already offered a preview of how they would respond to a potential Waller nomination — decidedly positively. When CNBC broadcast live Waller’s hour-long plus Q&A with 200 top CEOs in attendance at our Yale CEO Summit last week after a moderated Q&A with CNBC’s Steve Liesman; stocks rallied and bond yields fell in real time as Waller called for rates to come down, pointing to softening employment numbers, while simultaneously pledging to defend central bank independence. No other contender for Fed Chair has sparked such a positive market reaction.

Waller is a lifelong Republican who has a knack for getting along with very different constituencies, all of whom respect his genuine expertise, personal humility and willingness to listen. Even CEOs who disagreed with certain aspects of Waller’s arguments clearly appreciated his constructive engagement, as well as his intellectual honesty and independence. When we polled the room, as reported by Nick Timiraos of The Wall Street Journal, a whopping 81% of CEOs picked Waller as their top choice for Fed Chair, building on prior polls done by CNBC showing a majority of market participants prefer Waller, as well as prominent endorsements from publications such as The Economist.

Many CEOs at our Yale CEO Summit expressed their appreciation for Waller’s long track record of partnering effectively with business leaders on challenges as well as opportunities. Take crypto innovation as one such example. As the Fed Governor who oversees the payment system, Waller was once again correctly prescient as an advocate of stablecoins dating back to before 2021, when few knew what stablecoins even were, and he convened the first ever Payments Innovation Conference earlier this year, bringing in top leaders from industry to help shape the future of stablecoin payments.

President Harry Truman lamented, “Give me a one-handed economist. All my economists say, ‘on ONE hand…’, then ‘but on the other.’” Business leaders appreciate Waller’s serious and decisive style, his systemic economic knowledge, his track record of constructive engagement, his clarity of message, and his credible presence, which transcend political or personal career agendas.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

Every CEO investing in AI faces the same problem: spending billions on pilots that may or may not deliver real autonomy. Agents seem to excel in demos but stall when real-world complexity hits. As a result, business leaders do not trust AI to act independently on billion-dollar machinery or workflows. Leaders are searching for the next phase of AI’s capability: true enterprise expertise. We shouldn’t ask how much knowledge an agent can retain, but rather if it has had the opportunity to develop expertise by practicing as humans do. 

The Testing Illusion 

Just as human teams develop expertise through repetition, feedback and clear roles, AI agents must develop skills inside realistic practice environments with structured orchestration. Practice is what turns intelligence into reliable, autonomous performance.

Many enterprise leaders still assume that a few major LLM companies will develop powerful enough models and massive data sets to manage complex enterprise operations end-to-end via “Artificial General Intelligence.” 

But that isn’t how enterprises work. 

No critical process, whether it be supply chain planning or energy optimization, is run by one person with one skill set. Think of a basketball team. Each player needs to work on their skills, whether it be dribbling or jump shot, but each player also has a role on the team. A center’s purpose is different from a point guard’s. Teams succeed with defined roles, expertise and responsibilities. AI needs that same structure. 

Even if you did create the perfect model or reach AGI, I’d predict the agents would still fail in production because they never encountered variability, drift, anomalies, or the subtle signals that humans navigate every day. They haven’t differentiated their skill sets or learned when to act or pause. They also haven’t been exposed to expert feedback loops that shape real judgment.

How Machine Teaching Creates Practice

Machine Teaching provides the structure that modern agentic systems need. It guides agents to:

• Perceive the environment correctly.
• Master basic skills that mirror human operators.
• Learn higher-level strategies that reflect expert judgment.
• Coordinate under a supervisor agent that selects the right strategy at the right time.

Take one Fortune 500 company I worked with that was improving a nitrogen manufacturing process. Our agents practiced inside the AMESA Agent Cloud, improving through experimentation and feedback. In less than one day, the agent teams outperformed a custom-built industrial control system that other automation tools and single-agent AI applications could not match.

This resulted in an estimated $1.2 million in annual efficiency gains, and more importantly, gave leadership the confidence to deploy autonomy at scale because the system behaved like their best operators. 

Why CEOs and Leaders Need Practiced AI

Practice is what drives true autonomy in agents. I invite every leader to begin reframing a few assumptions:

1. Stop thinking in terms of models and think in terms of teams. Every day interactions with systems like ChatGPT or Claude are powerful, but they reinforce a misconception that large language models are the path to enterprise autonomy.  Autonomy emerges from specialized agents that take on perception, control, planning and supervisory roles through a wide variety of technologies. 
2. Identify where expertise is disappearing and preserve it within agents. Many essential operations rely on experts who are nearing retirement. CEOs should ask which processes would be most vulnerable if these experts left tomorrow. Those areas are the ideal starting point for a Machine Teaching approach. Let your top operators teach a team of agents in a safe practice environment so that their expertise becomes scalable and permanent.
3. Recognize that you already have the infrastructure for autonomy. Years of investment in sensors, MES and SCADA systems, ERP integrations and IoT telemetry already form your organization’s backbone of digital twins and high-fidelity simulations. Success requires orchestration, structure, and leveraging the data foundation you already built.

The Payoff of Practice

When enterprises give agents room to practice before deployment, several things happen:  

• Human teams begin to trust the AI and understand its boundaries. 
• Leaders can calculate true ROI rather than speculative projections. 
• Agents become safer, more consistent and aligned with expert judgment. 
• Human teams are elevated rather than replaced because AI now understands their workflows and supports them.

Agents won’t truly perform without experience, and experience only comes from practice. The companies that invest in and embrace this framing will be the ones to break out of pilot purgatory and see real impact.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.