245,000 Tech Workers Were Laid Off in 2025. AI Hiring Grew 88%. The Companies That Win Next Are Hiring for the Shift, Not the Headline.
The technology industry is executing the most dramatic workforce restructuring since the dot-com correction. Nearly a quarter-million tech employees were displaced in 2025 while AI-related hiring surged at the fastest rate in history. Companies are simultaneously cutting roles that AI can automate and desperately competing for executives who can deploy AI at enterprise scale, defend against threats that now evolve autonomously, and translate technical capability into business value. The 4.8 million-position cybersecurity workforce gap continues to widen. CIO hiring is accelerating as boards demand leaders who can move from AI experimentation to production. Chief AI Officer appointments have increased 70% year over year. The technology executive who can navigate all of this, the layoffs, the talent war, the regulatory complexity, and the board-level pressure to show AI ROI, is the most consequential hire your company will make this year.
The Market Reality
The Industry Is Not Shrinking. It Is Reorganizing Around AI at a Speed That Breaks Traditional Hiring.
The narrative that technology is in decline is a misreading of the data. What is actually happening is far more complex and far more consequential for executive hiring. The technology industry is executing a simultaneous restructuring: cutting roles that AI can automate while desperately competing for the leaders who can deploy AI at enterprise scale. In 2025, approximately 245,000 tech workers were displaced globally, averaging 674 per day. At the same time, AI-related hiring grew 88%, unique AI job titles increased 50%, and compensation for AI specialists carried a 28% premium over traditional tech roles.
This is not a hiring freeze. It is a talent reallocation of historic proportions. Forrester predicts that half of AI-attributed layoffs will be quietly rehired, but offshore or at significantly lower salaries. Meanwhile, 55% of employers who laid off workers for AI already report regretting it, having bet on capabilities that do not yet exist. The companies that made thoughtful, strategic leadership decisions during this transition are pulling ahead. The ones that cut indiscriminately are scrambling to rebuild the institutional knowledge they destroyed.
At the executive level, the restructuring has created an acute paradox. Boards are demanding AI transformation at a pace that exceeds the available supply of leaders who can actually deliver it. CIO hiring is accelerating as organizations move from AI experimentation to production deployment. Chief AI Officer appointments have surged 70% year over year. CISO reporting lines have shifted dramatically, with 42% now reporting directly to the CEO, triple from the prior year. The technology leadership landscape of 2026 looks nothing like it did even 18 months ago, and the executives who thrived in the previous era may not be the right ones for what comes next.
What We Are Seeing
The Great AI Talent Inversion
Entry-level tech roles have declined 73% as companies automate the tasks that junior employees traditionally performed. At the same time, demand for senior AI leadership has never been higher. LinkedIn ranked AI Engineer as the fastest-growing job title in the U.S. Nearly 90% of CIOs and CTOs report creating new AI-related positions, but a majority still worry about workforce shortages. The talent pool for production-ready AI engineers is narrow, competition is fierce, and the cost of unfilled roles is measured in delayed product launches and lost market position. Companies are paying AI specialists 30-50% premiums over generalist engineering salaries, and the gap continues to widen.
Cybersecurity Has Become a Board-Level Function
The global cybersecurity workforce gap stands at 4.8 million unfilled positions, with 90% of organizations reporting critical skills shortages. But the real shift is structural: cybersecurity is being reclassified from an IT subdomain to a business control function. 42% of CISOs now report directly to the CEO, and 41% of boards address cyber issues monthly, a cadence previously reserved for critical enterprise risks. IBM found that breaches involving unsanctioned AI cost significantly more and take longer to detect, creating demand for security leaders who can govern automated decision flows without stifling innovation. The CISO who only understands firewalls is obsolete. Boards want security executives who can articulate risk in business terms and hold decision rights that influence product roadmaps.
The CIO Role Has Been Redefined
The CIO was once the executive who kept systems running. In 2026, the CIO is the executive who determines whether the company can compete. Cybersecurity and risk management is the top CIO priority for the fourth consecutive year, followed by delivering measurable AI value and data analytics. Executive recruiters describe a shift from operational oversight to what they call "architects of agility" -- CIO leaders who can transition from AI experimentation to full-scale production. Compensation is rising accordingly, with variable pay and performance bonuses increasingly tied to digital and AI transformation milestones. The CIO is being asked to make AI happen, and boards are willing to pay significantly for the ones who can.
Chief AI Officer Is Now a Permanent C-Suite Position
What started as an experimental title at a handful of forward-thinking companies has become a corporate imperative. About 60% of organizations globally now have a dedicated AI executive. Among the FTSE 100, nearly half have a CAIO or equivalent, with 65% of those appointments made in the past two years. Compensation packages routinely reach $350K to $650K+, with equity at high-growth companies pushing total compensation into seven figures. But the talent pool is dangerously thin: current CAIOs typically come from data science (50%), consulting (21%), or engineering (17%). Few leaders combine the technical depth, business acumen, ethical governance capability, and board-level communication skills the role demands. High-readiness organizations are appointing CAIOs who report directly to the CEO and control governance, standards, and adoption. When those conditions are absent, the role becomes symbolic.
The AI Readiness Gap Is Widening
Only 16% of individual workers had high AI readiness in 2025, according to Forrester, projected to reach just 25% by 2026. Organizations are not investing in training: only 23% of AI decision-makers offered prompt engineering training. Employees are largely teaching themselves. Meanwhile, the workers with the highest AI readiness, Gen Z at 22%, are being systematically shut out of the workforce by the elimination of entry-level positions. The irony is structural: companies are cutting the cohort most capable of working with AI while struggling to find AI-fluent leadership. 54% of technology skills are expected to undergo deep transformation from generative AI adoption, and the executives who can manage this transition while maintaining productivity are defining the next generation of technology leadership.
Roles We Place
Technology Leadership for the Restructuring That Is Already Underway
Every role below exists at the intersection of AI transformation, cybersecurity risk, and the most competitive executive talent market in a generation. We place leaders who can build, defend, and scale technology capabilities that translate directly into business outcomes.
Chief Information Officer / Chief Technology Officer
The CIO/CTO role has absorbed more strategic responsibility in three years than in the previous twenty. This executive now owns AI deployment strategy, enterprise data architecture, cybersecurity governance, and digital transformation, simultaneously. Boards are hiring what recruiters call "architects of agility": leaders who can move from AI experimentation to production while maintaining security posture and managing the workforce transition. Compensation is rising with the scope, including retention bonuses tied to AI milestones and digital transformation deliverables. The best CIOs combine deep technical fluency with the business model knowledge to articulate how technology creates competitive advantage. The ones still managing infrastructure as a cost center are being replaced by the ones who treat it as a revenue driver.
Chief AI Officer
The CAIO is the newest permanent addition to the C-suite, responsible for enterprise-wide AI strategy, governance, implementation, risk management, and measurable value creation. This executive bridges the gap between what AI can do technically and what delivers actual business outcomes. Total compensation packages range from $350K to $650K+ at large enterprises, with equity at high-growth companies pushing into seven figures. The role demands a rare combination: technical depth sufficient to evaluate AI architectures, business acumen to build ROI cases for the board, ethical governance capability to manage responsible deployment, and leadership skill to build and retain AI teams in the most competitive talent market in technology. More than 60% of CAIOs have been at their current company for less than two years, indicating these are predominantly external hires, not internal promotions.
Chief Information Security Officer
The CISO has undergone the most dramatic elevation of any technology executive role. With 42% now reporting directly to the CEO and boards addressing cyber issues monthly, this executive has moved from IT advisor to enterprise leader with decision rights that influence product roadmaps and capital allocation. The 4.8 million global cybersecurity workforce gap means every CISO is operating with an understaffed team, making the ability to build, retain, and develop security talent a core leadership competency. AI-driven insider threats, unsanctioned AI usage, cloud security complexity, and zero trust architecture all compete for attention and budget. The modern CISO must articulate minimum viability during crisis, lead cleanroom recovery strategies, and govern AI security risks that did not exist three years ago. Organizations are seeking CISOs who can define what security is authorized to decide, not just what it recommends.
VP Engineering / SVP Product Development
Engineering leadership is being reshaped by AI in ways that go far beyond code generation tools. The VP Engineering now manages teams where AI copilots handle routine development tasks while human engineers focus on architecture, system design, and the judgment calls that algorithms cannot make. This executive must rethink team structures, redefine what productivity means when AI multiplies individual output, and navigate the tension between moving fast with AI-assisted development and maintaining code quality, security, and technical debt management. The best engineering leaders are building development cultures that treat AI as infrastructure rather than a novelty, embedding it into workflows so naturally that the competitive advantage becomes invisible to competitors still treating it as a separate initiative.
Chief Product Officer / VP Product
Every product roadmap in technology now includes an AI component, whether the market demands it or not. The CPO must distinguish between AI features that create genuine user value and AI features that exist because the board read an article. This executive owns the intersection of technical possibility and commercial viability: which AI capabilities to build, which to buy, which to defer, and how to price products where AI dramatically changes the cost structure. AI Product Managers command premiums of $180K+ base with total compensation at leading companies reaching well above $500K. The CPO who can translate AI capability into product-market fit, recurring revenue, and defensible competitive position is the most valuable product leader in the market.
Chief Data Officer / VP Data & Analytics
AI runs on data, and the CDO owns the foundation that determines whether AI initiatives succeed or fail. This executive manages enterprise data architecture, governance frameworks, quality standards, and the data infrastructure that AI models depend on. With CIOs ranking data and analytics as their third-highest priority, the CDO has moved from a compliance-oriented role to a strategic enabler. The challenge is that most organizations have plenty of data but cannot extract the expected value. The CDO who can build the governance frameworks, pipeline architecture, and organizational data literacy that turn raw information into AI-ready assets is solving the bottleneck that stalls more AI initiatives than any technical limitation.
VP Security Engineering / Director Cloud Security
Below the CISO, security engineering leadership is where strategy becomes execution. The VP Security Engineering embeds security directly into the technology fabric, partnering with the CTO to ensure that every product launch, cloud migration, and AI deployment has security built in rather than bolted on. Cloud security, identity and access management, and zero trust architecture are the fastest-growing security specializations, reflecting where the attack surface has expanded most dramatically. IAM architects and access governance specialists are in acute demand as hybrid work environments and third-party integrations have turned identity into the new perimeter. Cybersecurity hiring at this level requires architectural fluency, not just certification, because the problems have outgrown checkbox compliance.
VP AI/ML Engineering / Head of AI
This executive builds and manages the teams that turn AI strategy into production systems. With AI engineer salaries averaging $206K in 2025 (a $50K increase from the prior year) and specialized roles in deep learning, LLM fine-tuning, and MLOps commanding 30-50% premiums, retaining AI talent is as challenging as recruiting it. The VP AI/ML Engineering must build teams in a market where top candidates evaluate opportunities based on the full package: equity, remote flexibility, the quality of the AI team, access to compute resources, and the opportunity to work on genuinely challenging problems. This leader owns model development, MLOps infrastructure, responsible AI implementation, and the translation of research capability into production-grade systems that deliver measurable business value.
CRO / VP Sales / VP Customer Success
Technology sales has been transformed by AI on both sides of the transaction. Buyers are more informed, sales cycles are more complex, and the shift from perpetual licenses to consumption-based pricing has fundamentally changed how revenue is generated and retained. The CRO in a technology company now manages a revenue engine where AI-powered tools handle prospecting and qualification while human sellers focus on enterprise relationships and complex deal architecture. Customer success has become a revenue function, not a support function, as net revenue retention determines company valuation more than new logo acquisition. The revenue leader who understands both the technology being sold and the technology reshaping how it is sold commands a significant premium in this market.
Where We Place Technology Leaders
Across Sectors Where Technology Is No Longer a Department. It Is the Business.
The distinction between "technology companies" and "companies that use technology" has collapsed. Every industry needs technology executives. The question is whether they need ones who understand SaaS metrics, regulatory technology, operational technology, or consumer platforms. We place leaders who know the difference.
Enterprise SaaS
Platform architecture, subscription economics, product-led growth, enterprise sales cycles
Cybersecurity
Threat detection, identity management, cloud security, compliance automation, AI security
AI / Machine Learning
Foundation models, applied AI, MLOps platforms, AI governance, autonomous systems
FinTech
Digital payments, lending platforms, RegTech, blockchain, embedded finance, open banking
HealthTech
Electronic health records, telehealth, clinical AI, medical devices, health data interoperability
Cloud / Infrastructure
Hyperscale operations, multi-cloud management, edge computing, DevOps tooling, observability
E-Commerce / Marketplace
Platform operations, payments, logistics technology, personalization, marketplace dynamics
Data & Analytics
Data platforms, business intelligence, analytics engineering, data governance, data mesh
Industrial / OT Technology
Manufacturing automation, SCADA/ICS security, digital twin, IoT platforms, smart operations
Telecommunications
Network infrastructure, 5G deployment, edge computing, unified communications, carrier services
GovTech / Defense Tech
Federal IT modernization, cleared environments, FedRAMP compliance, defense systems integration
Climate / Clean Tech
Energy management platforms, carbon accounting, grid technology, sustainability analytics
Why Technology Executive Hiring Is Different
The Resume Says "AI Transformation." The Question Is Whether They Led It or Watched It.
Technology executive hiring has a credibility problem. Every technology leader's resume now includes AI, cloud transformation, and digital strategy. The language has become so standardized that the resume of the executive who led a company's entire AI deployment reads nearly identically to the resume of the executive who sat on the steering committee and attended the vendor demos. Distinguishing between the two requires a level of technical fluency and operational scrutiny that most generalist recruiters cannot provide.
The problem is compounded by the restructuring. 245,000 technology professionals were displaced in 2025, and a significant number of them are senior leaders whose roles were eliminated not because of performance but because of strategic shifts, acquisitions, or AI-driven reorganizations. These executives represent an extraordinary talent pool of proven implementers who are available through no fault of their own. But accessing them requires understanding which ones thrived because of the environment they were in and which ones will thrive in any environment. That distinction is the difference between a placement and a mis-hire.
Technology compensation has also become considerably more complex. AI specialists command premiums, but the range varies dramatically by specialization, company stage, and geography. A CAIO at a Fortune 500 company and a CAIO at a Series C startup may carry the same title but operate in entirely different compensation structures. Variable pay is increasingly tied to transformation milestones rather than traditional revenue metrics, and equity structures differ substantially between public companies, PE-backed firms, and venture-funded startups.
AI Implementation Verification
We separate executives who led AI deployments from executives who participated in them. Did they champion the business case, select the platform, manage the implementation, secure the data pipeline, drive adoption, and measure ROI? Or were they a stakeholder on a project led by someone else? In a market where every candidate claims AI experience, we verify what they actually built, what scale it operated at, and what business outcomes it produced. The difference between "I was part of an AI initiative" and "I deployed AI across four business units and generated $30M in operational savings" is the difference between a committee member and a leader.
Cybersecurity Governance Assessment
With CISOs now reporting to CEOs and holding board-level decision rights, the role demands a completely different assessment approach than even three years ago. We evaluate whether security leaders can translate technical risk into business language, whether they have governed AI-related security risks (not just traditional threats), and whether they have operated with genuine authority or merely advisory influence. The CISO who managed a stable security environment is a different profile from the CISO who navigated a breach, rebuilt trust with the board, and redesigned the security architecture while the company continued to operate. We identify the difference.
Restructuring Context Intelligence
The technology layoffs of 2024-2026 have displaced extraordinary executive talent. But not all displaced leaders are equal. Some were eliminated because their role was redundant in a reorganization. Some were eliminated because their function was outsourced or automated. Some were eliminated because leadership changes brought in new teams. Understanding the context of displacement is essential because it determines whether the candidate is available due to circumstances that have no bearing on their capability or because the market has evolved past their skill set. We invest the time to understand the full story behind the transition.
Technical Depth Without Technical Myopia
The best technology executives are deeply technical and deeply commercial simultaneously. We assess whether candidates can explain complex systems to a board, build business cases that CFOs approve, partner with revenue teams to translate technology into competitive advantage, and manage the organizational change that technology transformation demands. The CIO who can architect a multi-cloud environment but cannot explain to the CEO why it matters to revenue is an incomplete leader. The one who can present to the board in the morning and debug architecture decisions in the afternoon is the leader that builds technology organizations that drive enterprise value.
Displaced Executive Identification
Artemis specializes in finding "implementers": high-performing executives displaced from major companies due to organizational changes rather than performance issues. The technology sector has produced the largest concentration of these executives in the current market. Leaders who ran product organizations at companies that restructured, CTOs whose companies were acquired, CISOs whose security teams were consolidated after mergers. These executives carry institutional knowledge, proven track records, and the operational scars that only come from having built and managed at scale. They are our specialty, and our 94% two-year placement success rate reflects how precisely we match them to the companies that need what they have already proven they can do.
Compensation Architecture Expertise
Technology executive compensation in 2026 defies simple benchmarking. AI leaders earn a 10% average premium over comparable engineering executives, but the structure varies dramatically by company type. Early-stage firms rely heavily on equity with moderate base salaries. Public companies offer more cash-heavy packages with RSUs. PE-backed technology companies structure around performance milestones tied to exit timelines. Variable pay is increasingly linked to digital and AI transformation deliverables rather than traditional operational metrics. We navigate this complexity to structure offers that are competitive enough to attract the right candidate and aligned enough with your economics to be sustainable.
Our Search Process
Designed for a Market Where Every Open Month Is a Competitive Disadvantage.
An unfilled technology leadership role does not just cost salary savings. It costs the AI initiative that does not launch, the security posture that erodes, the product roadmap that stalls, and the engineering talent that leaves for companies with stronger leadership.
Technology Environment Assessment
We start by understanding your technology landscape, not just the job description. What is your architecture? Where are you in the AI maturity curve? What is the security posture? Is this an AI transformation play, a post-restructuring rebuild, a cybersecurity elevation, or a growth-stage scale-up? What industry-specific regulatory and compliance requirements shape the technology environment? The answer determines the candidate profile. A CIO for a FinTech startup navigating regulatory complexity is a fundamentally different hire than a CIO for a manufacturing company digitizing operations. We scope every search against your specific technology reality.
Displaced Talent and Passive Sourcing
The technology restructuring has created the deepest pool of available senior talent since the dot-com correction. We source from this pool deliberately, identifying executives displaced from major companies whose skills match your environment. We also access passive candidates through relationships built across the technology ecosystem: operators running platform companies, security leaders who have navigated breaches, AI executives who have scaled from experimentation to production. The combination of displaced talent and passive sourcing gives us access to candidates that job postings and LinkedIn outreach cannot reach.
A.I. (Actually Interviewed) Assessment
Every candidate undergoes deep evaluation against your technology environment's specific requirements. We verify AI deployment experience with operational specificity: what they built, what scale it reached, what business outcomes it delivered. We assess cybersecurity governance capability by testing whether they can articulate risk in business terms and demonstrate decision authority. We evaluate technical depth through scenario-based discussions, not keyword matching. We examine cultural and organizational fit by understanding how they have built and led teams through transformation. Impressive resumes do not survive our assessment process. Demonstrated capability does.
Transition and 90-Day Integration
Technology leadership transitions carry compounding risk. The new leader inherits production systems, security posture, engineering culture, vendor relationships, and in-flight initiatives that cannot pause. Our 90-Day Success Plan provides structured integration: understanding the technology architecture and technical debt landscape, assessing team capability and retention risk, identifying quick wins that build credibility, and establishing the governance frameworks that AI-era technology leadership demands. We remain engaged through the critical first quarter to protect both the hire and the technology organization's momentum.
"The thing that sets Artemis Partners apart for us is communication and professionalism. There isn't a single question that has gone unanswered for longer than a 12-hour period no matter what. They are amazing allies in the world of talent acquisition and the level of confidentiality and professionalism they all work with sets them leagues apart from other firms."
VP of Talent Acquisition / Technology / Houston
Start the Conversation
The Companies That Move Fastest on AI Leadership Will Define the Next Decade of Technology.
Schedule a 30-minute conversation with Johanna Watson to discuss your technology leadership needs. Whether you are building an AI organization from scratch, elevating cybersecurity to the board level, replacing a CIO who cannot drive transformation, or hiring your first Chief AI Officer, Artemis places the executives who turn technology capability into competitive advantage.
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