Are Tech Jobs Still a Safe Bet in the Age of AI?

The headlines are loud: high‑profile layoffs at companies like Block and Shopify, executives talking about “AI efficiencies,” and stock prices jumping when headcount is trimmed. It’s natural for people early and mid‑career in tech to wonder: are tech jobs still a safe bet?

The short answer is yes, but “safe” looks different than it did during the zero‑interest‑rate, growth‑at‑all‑costs era. The roles, skillsets, and career paths that will thrive are shifting. Understanding that shift is the real hedge.

Layoffs, AI, and the Reality Behind the Headlines

When a company like Block announces layoffs and frames them as an AI‑driven transformation, it can sound like a referendum on tech careers. But in many cases, these moves follow a familiar pattern:

• Years of aggressive hiring to hit ambitious goals.
• Growing “bloat” in tactical and overlapping roles.
• A shift in market conditions and profitability pressure.
• A story about “AI efficiency” that makes the correction more palatable to markets.

Shopify’s now‑famous pivot is a good example: a significant layoff wave positioned as a bold reset and AI‑forward future. Block’s recent move looks similar: an over‑hiring correction dressed up as a visionary AI play. Investors reward this kind of narrative; Block’s stock jumped sharply on the news because it signalled discipline, not because technology jobs are suddenly obsolete.

Layoffs at big tech companies are not new. Large organizations have always gone through cycles of expansion and contraction as strategies change. AI mostly provides a convenient and partially true storyline about efficiency and transformation. As we love to say, "two things can be true".

So when we ask “Are tech jobs safe?”, we’re often really asking: “Are over‑staffed, big‑logo tech jobs safe?” The honest answer is: not always, and not forever.

A Valley and a New Mountain: How AI Changes the Job Landscape

We may be entering a valley for certain types of roles, especially those that are perceived as "routine and easily automated", but on the other side is a new mountain of roles that don’t exist yet, or are only just emerging.

In the near term, AI will:

• Compress or eliminate some repetitive, tactical work.
• Change the entry‑level experience for engineers and other technical roles.
• Enable companies, especially early‑stage ones, to build more with smaller teams.

Over the long term, AI is more likely to reconfigure work than erase it. Most organizations are not replacing entire teams with AI; they’re looking for ways to augment human capability. That still requires product strategy, design, data, engineering, operations, compliance, and go‑to‑market expertise, plus judgment about where and how to use AI safely and responsibly.

In other words: AI is less a wrecking ball for tech jobs and more a force multiplier for people who are willing to adapt.

From Coders to Problem Solvers: The Rise of the Product‑Minded Engineer

Tech roles are shifting from tightly scoped execution toward solving messy, valuable business problems. The work that endures is less about cranking out code and more about framing and prioritizing problems, understanding customers, integrating AI and tools pragmatically, and making smart trade‑offs across product, engineering, operations, risk, and finance.

As a result, product‑minded engineers or "Product Engineers" are becoming an archetype: people who write solid code, grasp architecture and data, and also shape product decisions, talk to customers, and stitch together services, APIs, and AI components. Even at the entry level, expectations are rising around communication, collaboration, and product thinking. The premium is moving from “I can write a lot of code” to “I can use code and AI to deliver real business outcomes,” and those who invest in problem framing, experimentation, and AI fluency will find the strongest opportunities.

Leaner Teams, Different Companies, Same Demand for Builders

Another shift is where tech talent is needed.

Companies that grew headcount aggressively are under pressure to operate more efficiently. In those environments, we’re likely to see:

• Fewer layers of management, more balance between strategy & output, and more "wearing many hats".
• Clear expectations that each person owns broad scope and leverages AI to increase their output.
• Periodic restructuring as strategies evolve.

At the same time, early‑stage and growth‑stage companies are using AI to build more with smaller, highly skilled teams. For product‑led growth companies, AI can amplify self‑serve onboarding, support, and product discovery. For enterprise‑focused businesses, there’s still an ongoing need for sales, customer success, implementation, and relationship management that AI can support but not replace.

Ultimately, demand is for people who can build, ship, and commercialize technology in environments that value capital efficiency and durable business models. Tech jobs are still a strong bet, but the edge increasingly goes to those who can operate in lean, cross‑functional teams, tie their work directly to business outcomes, and use AI as a tool rather than seeing it as a threat.

AI Use and Compensation: Today’s Reality, Tomorrow’s Question

In our own 2026 Salary Survey data, when we ask tech leaders how often they use AI and for what, the relationship between AI usage and compensation was surprisingly flat: people who rarely use AI are, on average, paid roughly the same as those who use it frequently.

That suggests two things:

1. We’re still early in the adoption curve. Many leaders and ICs are experimenting, but AI usage is not yet a primary driver of pay.
2. Market signals lag capability. Compensation structures tend to catch up to skills and impact with a delay.

Looking ahead 5–10 years, it’s hard to imagine a world where comfort with AI doesn’t become a more explicit part of roles, seniority, and inevitably compensation. For now, AI fluency looks like an edge rather than a requirement  but over time, it’s likely to become table stakes, especially for roles closest to product strategy, data, and engineering.

Why Tech Still Represents a Strong Career Bet

So, are tech jobs still a “safe” bet?

If “safe” means “guaranteed lifetime employment at one company,” the answer has never truly been yes. Roles have always carried concentration risk: your fortunes are tied to a single company’s strategy and the broader market cycle.

If “safe” means durable demand for people who can build and commercialize technology in many different contexts, the answer is still yes, with some nuance:

• Roles in orgs that have over-hired are the most at risk.
• The roles that combine judgment, creativity, and cross‑functional collaboration are the most resilient.
• AI is amplifying the difference between these two categories, not eliminating the need for humans altogether.

Tech is also bigger than “big tech.” Every industry is becoming more digital and more data‑driven. Banks, insurers, logistics companies, healthcare organizations, and industrial businesses all need product thinkers, engineers, designers, and operators who can integrate AI into the fabric of their operations.

That integration work of translating messy business problems into reliable, scalable systems is not going away. It’s getting more important.

How to Stay Relevant: Learn, Unlearn, and Stay Close to the Customer

Against this backdrop, the safest strategy for individuals isn’t to avoid tech. It’s to approach a tech career like an evolving product:

• Stay nimble. Be willing to learn new tools, paradigms, and ways of working as they emerge.
• Invest in adaptability. The ability to both learn and unlearn is becoming critical at every level.
• Get closer to the customer. The more you understand real needs and behaviours, the harder it is to replace your judgment with automation.
• Think in systems, not just tasks. People who can see across functions like product, engineering, operations, risk, and GTM will have more ways to contribute.
• Treat AI as a force multiplier. The individuals and teams who thrive will be the ones who integrate AI thoughtfully into their workflows instead of seeing it as a zero‑sum threat.

Some roles will shrink, some will evolve, and new ones will emerge. But the underlying demand for people who can build, ship, and scale technology remains very real.

Tech jobs are still a strong bet, especially for those who are ready to climb the next mountain, not just defend the last one.