Talent as Capital in Tech, Media and Entertainment
Why private equity boards now govern talent with the same rigor as capital to drive returns.
In tech, media and entertainment (TME), talent strategy now drives returns as much as capital strategy. Boards that treat talent as a system — designed, priced and governed with the same rigor as M&A — outperform.
The Moment We’re In
Consider this scenario: A portfolio CEO sits in a board meeting. Revenue is up. Product velocity is strong. Yet three senior engineers just resigned. One left to start an AI-first company with two friends. One joined a lab that pays three-times market. One is building an agent that will replace part of her own role.
This is the reality across TME today. PwC’s recent report, “Global M&A Trends in Technology, Media and Telecommunications,” points to three clear trends:
AI is reshaping value creation across telecom, media and tech.
Growth depends on speed, data and operating model change.
Returns now hinge on execution, not just entry multiple.
For private boards, this changes the job. You no longer govern only strategy, capital and risk. You now govern the talent system that turns capital into returns.
Why Talent Is Now a Board-Level Value Lever
Private equity playbooks evolved in an era where talent was abundant and tools were scarce. Today, tools are cheap. Talent is scarce.
In AI-heavy businesses, compensation has split into tiers:
AI labs and frontier teams command up to 300% premiums.
AI-enabled firms pay closer to 10% above market.
Many roles sit at standard market medians.
This spread matters. It shows where real scarcity lives. It also shows a risk boards must manage: overpaying broadly instead of paying surgically. When capital is mispriced, returns suffer. The same is now true for people. At the same time, boards face a new competitor for talent: the employee themselves. With AI tools, a single skilled operator can now generate seven- or eight-figure income. A high-frequency trader with AI can clear $20 million in a strong year. A product lead can spin out a software as a service (SaaS) product in months. Your portfolio company is no longer competing only with peers. It competes with solo founders and, soon, AI agents.
The New Talent Threat Model
Boards should update their threat model. It now includes:
Solo founders who do not need your platform.
AI agents that will take on service-like work.
Global talent markets where pay bands fragment by skill depth.
Down rounds and valuation resets that strain equity narratives.
It shows up in three board-level risks:
Flight risk at the top. The best people have the most options.
Overpay risk in the middle. Premiums drift into roles that do not create edge.
Narrative risk during valuation corrections. Equity loses its pull if the story breaks.
Boards that ignore these risks treat talent as an HR issue. Boards that manage them treat talent as a return engine.
The Talent Playbook
High-performing private equity boards now run a talent playbook across five moves.
Segment roles by value creation, not titles. Job titles no longer map cleanly to value. “Senior engineer” can mean 10 different things in an AI firm. Boards should push management to segment roles by value to the growth engine.
A simple framework:
Core value roles. Roles that drive revenue, product edge or data advantage.
Scale roles. Roles that help the business grow faster once product-market fit is clear.
Support roles. Roles that sustain operations.
Only the first group merits sustained premium pay and equity leverage. This keeps burn in check and concentrates capital where it compounds.
Board action: Ask for a quarterly talent map that shows which roles link to growth drivers and how pay bands align.
Use precision pay, not blanket premiums. The AI talent bubble created a reflex to overpay. That reflex now hurts returns.
Smart boards back precision pay.
Pay market median for most roles.
Pay above market only for scarce, value-creating skills.
Tie outsized upside to clear value milestones.
This mirrors how you price assets. You do not pay peak multiples for every acquisition. You pay up for the asset that creates the edge.
Board action: Approve pay exceptions only with a clear link to value creation. Track return on investment on premium hires.
Build internal founder tracks to compete with solo founders. If your best people want to build, help them build inside your platform. Some AI firms now run internal founder hubs. They fund moonshot teams. They offer salary continuity. They grant equity in both the spin-out product and the parent company.
This solves two problems at once:
It keeps founders inside the ecosystem.
It creates optionality for new growth engines.
Boards often hesitate to allocate budget to experiments. Yet a 20% allocation to moonshots can deliver a 20-times return if even one hits.
Board action: Set aside a defined innovation budget. Treat internal ventures like a portfolio, not a side project.
Stress-test equity narratives before valuation drops. Valuations move. People stay or leave based on belief. After 2021, many companies faced down rounds. The lesson was clear: You cannot fix morale with math alone. You fix it with a credible story.
Boards should demand equity stress tests.
What happens to retention if valuation drops 30%?
Who needs refresh grants to stay?
How much pool burn can we afford for one year to stabilize talent?
Some firms raise equity burn from 3% to 5% for a single year to protect critical roles. Then they normalize. This buys time. The harder work is narrative. Leaders must explain why the company can still grow two times, four times or eight times from here. Without that story, equity loses meaning.
Board action: Run annual downside scenarios on equity strategy. Coach CEOs on narrative discipline during resets.
Redesign skills, not just head count. AI replicates tasks. It does not replace judgment. Across portfolios, clients report the same gap: decision-making under pressure. The skill to pick the right call when 10 signals compete. The skill to rally teams when the path is unclear. These skills compound returns. They reduce wasted spend. They speed time to value.
Boards should push for targeted leadership development in:
Decision-making under uncertainty.
Persuasion and alignment.
Operating with AI agents, not against them.
As agents take on service work, humans will shift into quality control, strategy and judgment. That transition needs training.
Board action: Ring-fence learning budgets for leadership skills tied to execution speed.
What About Paying AI Agents?
As AI agents take on service-like work, firms will face pricing choices. A simple rule from SaaS helps: Software often prices at roughly one-tenth the cost of human service.
Boards should plan for:
Lower marginal cost of output.
New intellectual property (IP) questions as human expertise trains agents.
New roles in quality assurance over agent output.
The value shifts from doing the work to owning the system that does the work.This changes how equity links to value creation. When multiple experts train one agent, ownership claims blur. Boards should get ahead of IP policy now.
Board action: Ask for an IP and agent governance framework before agents scale across functions.
The Operating Model Shift in TME
PwC’s deal trends highlight that winning in TME now requires operating model change. AI, data and platform plays blur sector lines. Telecommunications companies act like tech firms. Media firms become data platforms. Tech firms become content owners. This convergence puts pressure on leadership teams. The old org chart breaks. The old role definitions fail. Boards should expect friction. Structures will lag reality. That is normal. The risk is over-fitting to old frameworks. Rigid role bands slow innovation. Over-specified job ladders repel frontier talent.
Board action: Allow flexibility in roles and compensation for frontier teams. Use structure to frame problems, not to constrain solutions.
The One Metric Boards Should Watch
If you track only one talent metric, track this:time to value from critical hires.
How long does it take for a premium hire to move the growth needle? 30 days? 90 days? 180 days?
If time to value stretches, returns compress. Speed is now a core driver of internal rate of return.
This metric forces discipline.
It ties pay to output.
It surfaces weak onboarding.
It highlights where operating friction lives.
Board action: Add time-to-value to your value creation dashboard.
The Board’s New Mandate
In TME, the board’s job is no longer just to approve strategy. It is to design the system that turns talent into returns.
That system includes financial engineering, applied to people.
How you price scarce skills
How you retain founders inside the tent
How you protect equity narratives in downturns
How you train leaders to decide under pressure
How you govern AI agents and IP
Call to Action
Before your next board meeting, ask three questions.
Which five roles create the most value in the next 12 months?
Are we paying premiums only for those roles?
If valuation drops 30%, do we have a retention plan and a story people will believe?
If you cannot answer these in one page, your talent system is under-designed. Design it with the same rigor you apply to deals. Your returns will follow.
About the Author(s)
Sabrina Hannam is chair of Boardswell, advisory board member of Opal Group, and a guest lecturer at The Wharton School of the University of Pennsylvania and a lecturer at Columbia University School of Professional Studies.
