In 2025, media and entertainment companies cut 17,163 jobs, roughly 15% more than the year before, per Challenger, Gray & Christmas data. Most of those reductions weren’t driven by automation. They came from consolidation, cost pressure, and org redesign as streaming shifted from growth theater to margin discipline.
As layers keep getting cut, the amount of work doesn’t change. What changes is who’s allowed to make decisions.
Directors and senior managers keep getting removed while the responsibilities they handled remain embedded in the system. Decisions that used to get resolved inside teams now escalate upward, pushing routine trade-offs to VPs and then further up to execs. Response times stretch because approvals compete with earnings prep, board meetings, investor calls, and external messaging that always takes priority.
To keep work moving under these constraints, companies rely on measurement inside the decision path. Output targets, velocity tracking, utilization metrics, and tool adoption benchmarks become the mechanism by which work advances. These systems don’t accelerate decisions. They replace the people who used to make them.
Headcount shrinks, and rework rises.
Flattening concentrates decision-making
Middle managers handle decisions that require context and speed rather than senior authority. They set priorities when teams conflict, force scope and timeline calls before launches slip, and stop work heading toward legal, brand, or quality problems.
As those roles disappear, the decisions don’t disappear with them. They accumulate.
Teams escalate questions they previously resolved on their own. Cross-functional issues wait for senior input that arrives late or inconsistently. Work continues without answers when responses don’t arrive in time, and corrections move later into the process where fixes require more people, more coordination, and more time.
Decision volume rises at the top of the organization, while decision throughput stays flat.
Measurement allocates effort
Measurement systems now determine what counts as progress, which quietly reshapes how teams behave.
Instead of managers sequencing work based on downstream constraints, teams chase preset delivery targets that ignore dependencies. Instead of humans trading off scope across functions, throughput metrics define success. Instead of pausing work to resolve risk early, teams push forward to avoid missing reported goals.
Behavior follows incentives.
Work gets subdivided so progress stays visible. Risk mitigation shifts later because it slows delivery. Cross-team coordination drops because it isn’t tracked. Rework increases because early judgment never gets applied.
Reported output stays high, while finished work degrades.
AI shortens timelines without removing steps
AI changes planning assumptions without changing the underlying workflow.
Leadership shortens timelines based on expected tooling gains, raises output expectations, and holds staffing flat or lets it decline. The steps don’t disappear. They compress.
Managers still deal with reviews, approvals, legal constraints, partner requirements, and rework, and they adjust schedules to account for those realities. Those adjustments carry less weight because teams get evaluated against expectations derived from tooling assumptions, not observed workflows.
The manager’s role narrows. Instead of making trade-offs, managers enforce delivery against fixed constraints they didn’t set and can’t renegotiate.
Senior leadership absorbs routine decisions
Media businesses require decisions close to the work because outcomes depend on timing and coordination across functions.
As middle layers thin, decision load moves upward. Execs handle issues without sufficient context and without enough time to respond consistently. Guidance changes by meeting. Decisions arrive late. Teams work around missing answers and push projects forward without alignment, correcting course later through rework.
To compensate, organizations add meetings, documentation, and tracking. Execution costs rise as coordination overhead expands, while decision quality declines because fewer calls get made early.
Lean structures raise failure costs
Media operations require constant trade-offs across creative, legal, revenue, brand, and operational constraints. Those trade-offs are cheapest when they happen early.
Measurement systems report performance after execution. They surface problems only after commitments are locked and costs are already sunk.
When judgment disappears from the middle of the org, problems surface later in the cycle. Fixes require more coordination, more approvals, and more expense. Teams stay active and busy while outcomes deteriorate.
The Streaming Wars Take
This operating model persists because it protects execs while pushing consequences downstream.
Cutting managers lowers payroll immediately, often at the expense of people who were solving problems every day and didn’t create the cost pressures driving the cuts. Measurement scales cheaply and creates audit trails for boards. Tool adoption gives leadership something tangible to point at when execution slips.
What disappears is early decision authority.
Without people empowered to stop, slow, or redirect work near the source, companies discover problems late and pay more to fix them. Projects don’t get killed early. They get dragged forward until sunk cost forces action.
AI raises output expectations without removing coordination steps. Measurement rewards activity instead of resolution. Together, they lock companies into a system that looks controlled and operates poorly.
Execs who believe this is efficiency are confusing cost reduction with control. Control comes from decisions made early, not metrics reviewed after damage is done.
What actually works instead
Media companies that avoid this trap do a few unglamorous things consistently.
They reassign real decision-making authority to managers close to the work, with explicit scope and limits, rather than treating them as throughput enforcers.
They measure where work breaks, not just how fast it moves, and treat rising rework as a management failure, not a team failure.
They cap escalation, forcing decisions to resolve within defined layers unless financial or legal thresholds are crossed.
They treat AI output as draft labor, not schedule compression, and plan timelines around review and coordination, not tool demos.
None of this looks exciting on an earnings call. All of it reduces late-stage failure costs.
Companies running the current model spend less on payroll and more on cleanup. They miss timelines, burn talent, and normalize preventable failures as execution issues.
This isn’t a talent gap, but rather an org design choice leadership keeps making.
One more thing
We’re releasing The Streaming Wars Guide to the Future of Media Jobs soon.
It breaks down what’s actually driving layoffs, how AI is being used as justification rather than cause, and where media jobs are becoming more fragile or more protected as organizations continue to flatten. If you’re trying to understand what’s happening to the labor market or get ahead of the next restructure instead of reacting to it, this guide is for you.
Make sure you’re subscribed to the TSW newsletter so you don’t miss it when it drops. We’ll just ship it when it’s ready.
