For decades, work followed a predictable logic. Perform well and you earn authority. If an employer disappoints you, leave for something better. If you invest through large institutions, trust that established systems will safeguard your interests. These structures were imperfect, but they provided stability and legibility. That logic is breaking down.

What follows is a close look at how power, stability, and advancement are being renegotiated in real time, often in ways workers and investors feel before they ever see them clearly explained.

Events for You:

We keep promoting people into leadership roles and then act surprised when engagement drops, teams struggle, and burnout spreads.

For decades, the logic inside organizations has remained largely unchanged. f you stay long enough and perform well enough, you earn a promotion that comes with a higher title, broader responsibility, and sometimes more money. What rarely changes is the assumption beneath that system, which is that leadership is a natural reward for tenure rather than a distinct discipline that requires preparation.

That assumption is now visibly breaking down.

Recent research from Gallup shows that supervisors promoted primarily for strong frontline performance are less engaged than those promoted for demonstrated leadership ability or prior supervisory experience. That disengagement does not remain contained at the individual level, because frontline supervisors shape the daily experience of entire teams. This is not a failure of ambition or work ethic. It is a failure of design.

What should not be assumed is that longevity or technical excellence automatically qualifies someone to manage other people’s work, performance, and careers. Managing people is a different job that requires skills many organizations never formally teach. Yet many companies still treat management as the default next step for advancement, which leaves employees facing a false choice between taking on people management or watching their compensation stagnate. Expecting someone to learn how to lead while actively leading is how burnout becomes normalized.

The deeper issue is that the concept of promotion has remained largely static despite dramatic changes in how work gets done. Many organizations still rely on vertical ladders that equate progress with authority, even though value creation increasingly comes from collaboration, specialization, and adaptability. Some companies have begun to challenge this logic.

Unilever, for example, has adopted skills-based models that allow employees to move across projects and roles based on demonstrated capabilities rather than job titles. In that system, growth is tied to skills deployed and problems solved, not to the number of people managed. Other organizations have implemented career lattices that allow for horizontal and diagonal movement, enabling employees to deepen expertise or broaden scope without being forced into people management. These models treat individual contributors and managers as parallel paths rather than hierarchical steps, with comparable status and compensation potential.

Leadership is a skill, and it should be treated with the same seriousness as any other role that determines whether people stay, grow, or leave.

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Why do we return to a place that we left? 

Why come back to people who at one time didn’t value us?

It was confirmed by CNBC in December 2025 that over a fifth of AI engineering employees at Google were people who used to work there.

“Boomerang” hires have reached its highest share of new hires in the past 7 years, according to data from ADP. 

And while the trend can be seen across many sectors, the information (technology) sector has seen the greatest increase in 2025 as compared to 2024.

While there are many factors that could affect this trend, the boomerang effect requires two forces because the path of a boomerang is essentially 2 pivots. First, there needs to be a catalyst to leave. This could have been the “Great Resignation” of 2022 and subsequent job switching period with inflated salaries to lure, in particular, tech talent. Perhaps it was the rise of AI startups over the past 3 years, with former employees realizing that there may be no better time to be a founder than now. The turning point could have also been the mass layoffs and buyouts seen over the last 18 months. 

But there also needs to be a catalyst to return. In my reading of the stock market, labor market, and sectors like technology, philanthropy, and nonprofits, the factor that unifies talent and employers is policy uncertainty. 

With the current Federal administration’s track record of decision-making and the build up towards midterm elections, there is uncertainty in policies at the Federal level. Just as important is a full understanding of the effects of Federal economic and immigration policies on local governments and economies. Policy and the local and Federal level shapes businesses and the behaviors of job seekers [who are also consumers]. If there is uncertainty in policy, there’s uncertainty in profits and purse-strings.

And so the boomerang hiring effect is largely driven by a grasp for familiarity in times of uncertainty. 

Boomerang hiring is like that comfortable blanket you reach for in the coldest of winter days—tattered, stained in some areas—that smells and feels familiar. It provides comfort and stability until there’s more daylight, more visibility—more certainty. 

So the big takeaway here is that if there’s more macrolevel stability, this trend won’t last. They will leave again and companies will seek younger [and cheaper] talent across departments while also hiring big-splash, high-end talent at mission-critical teams and roles related to AI engineering.  

But if uncertainty continues, so will the path of the boomerang. 

Most people never hear the phrase “proxy voting,” yet it quietly determines how trillions of dollars influence the companies that shape the economy.

Proxy voting is how shareholders weigh in on major corporate decisions, including who sits on a company’s board, how executives are paid, whether mergers proceed, and how management responds to shareholder proposals. Large investment firms own shares in thousands of companies on behalf of retirement savers, pension funds, and everyday investors must cast votes at a massive scale, far beyond what any individual portfolio manager could personally analyze.

For decades, proxy advisory firms filled that gap. Firms such as Institutional Shareholder Services and Glass Lewis reviewed proxy statements, analyzed governance issues, and issued voting recommendations that asset managers could use as input. Their value came from scale. They made it possible to process thousands of votes efficiently and consistently across the market.

That system is now being dismantled.

JPMorgan Chase recently announced that its $7 trillion asset-management arm is cutting all ties with external proxy advisory firms and replacing them with an internal artificial intelligence platform called Proxy IQ. Beginning this proxy season, JPMorgan will rely on AI to analyze data from more than 3,000 annual shareholder meetings and generate voting recommendations internally rather than outsourcing that judgment.

The timing is not accidental. In December, the Trump administration issued an executive order directing securities and antitrust regulators to scrutinize proxy advisory firms, citing concerns about conflicts of interest and excessive influence over corporate governance. Corporate executives have raised these complaints for years, arguing that a small number of firms effectively shape voting outcomes across the market without sufficient accountability.

Artificial intelligence has removed the core advantage proxy advisors once held. Modern AI systems can ingest proxy filings, analyze historical voting behavior, compare compensation structures, and identify governance risks faster and at lower cost than external firms offering standardized recommendations. For large asset managers, outsourcing judgment no longer makes strategic sense when internal systems can deliver more tailored, data-driven decisions.

This shift is already forcing adaptation. Glass Lewis has announced it will phase out its broad benchmark voting recommendations by 2027, moving toward more customized guidance. That decision reflects a broader reality: generic governance frameworks lose value when clients can generate their own analysis at scale.

The deeper impact, however, is not on proxy advisors themselves but on the balance of power within asset management. Large firms can afford to build proprietary AI platforms trained on decades of internal voting data and stewardship philosophy. Smaller firms often cannot. Proxy advisors once leveled the playing field by providing shared infrastructure. As that layer disappears, governance influence concentrates further among firms with the capital, data, and technical capacity to internalize the function.

What makes this shift consequential is not that proxy voting is changing, but that it is becoming harder for everyday investors to see. Decisions that influence executive pay, board oversight, and corporate risk are moving away from shared frameworks and into proprietary AI systems controlled by the largest firms in the market. For individuals whose retirement savings flow through these institutions, the effect is subtle but real. The machinery of shareholder power is still running, but it is doing so behind fewer doors, with less visibility into how judgment is formed and whose priorities ultimately guide the vote.