Tech Salary Hikes: Cool, But GenAI and E-Security Jobs Are Still the Hot Spot
“The Best Jobs in America” report provides data on the average compensation for software

For about a decade, the tech industry experienced a period of fast-growing salaries, talent shortages, and a battle among companies to attract the best talent. Roles that were best compensated included software developers, data scientists, cloud solution architects, and tech consultants, who were subjected to double-digit increases and other perks such as bonuses and stock options.

Still, the trend appears to have changed over the last few years. Average increases pertaining to technology jobs have slowed down. This affects not only technology jobs but also related areas like traditional IT services and support jobs. Still, this trend of slow growth is not the same for all technology jobs. Specific jobs like Gen-AI and Cybersecurity have huge demands and top-notch salary requirements.

This disparity reflects a paradigm shift in the application, valuation, and monetization of technology. Organizations have become increasingly choosy about whom to employ, with less emphasis on hiring more people and more on high-impact skills that have a direct impact on productivity, innovation, and risk management.

The Reason for Cooling Tech Salary Rises Overall

1.1 Ending the Post-Pandemic Hiring Boom

The COVID-19 pandemic launched the world into an unprecedented digital acceleration. Enterprises were eager to:

Enable remote work

Migrate workloads into the cloud

Create digital customer experiences

Automating business processes

This triggered strategic hiring and high remuneration packages, particularly during the years 2020 to 2022. However, after this transformation settled, businesses started reviewing their cost structures.

As a consequence:

Hiring slowed down

Increase in salaries became conservative
W

Performance-related improvements replaced general increments

1.2 Global Economic Uncertainty

Macroeconomic considerations are also important in M&As:

High Interest Rates

Inflationary forces

Geopolitical tensions

Slower global growth

These circumstances compelled organizations to:

Controlling Operating Costs
Control

Postpone discretionary tech expenditures

Decrease dependency on massive IT staffs

Even profitable technology companies adopted a “do more with less” mentality.

1.3 Automation and Maturity of Core IT Skills

Traditional IT jobs are not as in-demand as they used to be:

Basic Java or .NET developers

Manual testers

Infrastructure administrators

Entry-Level Cloud Engineers

There are fewer requirements with automation tools, low-code platforms, AI-assisted coding, and standardized cloud services. Due to an increase in supply and a stabilized demand, pay raises also decelerated.

1.4 Large talent supply for traditional tech jobs

“Over the past ten years, millions of learners across the world have accessed courses in the

computer-science degrees

Coding bootcamps

Programming Courses Online

This has helped to improve talent availability in key software skills, particularly in junior to middle management positions.

GenAI: The New Gold Rush in Tech Careers

Even with the overall slowing in the industry, Generative AI opportunities exist in the midst of

2.1 What Is Generative AI?

Generative AIs: Models That Have The Ability To:

Develop text (ChatGPT, Gemini

Produce images and videos (DALL-E, Midjourney

Develop and Debug Code
Develop and

Analyze big data

Simulate human-like reasoning

These models aren’t just technology; they’re industry-changing platforms.

2.2 Why Companies Are Investing Heavily in GenAI

Companies are using GenAI for:

Boost worker productivity

Decrease operational expenses

Increase customer engagement

Automate decision-making

Gain competitive advantage

Contrastively, unlike other AI waves, GenAI provides an immediate and visible ROI, making it a board-level concern.

2.3 Roles of GenAI in High Demand

Among the most popular jobs are:

a) GenAI Engineers

They develop, optimize, and apply generative models using oracular systems such as:

OpenAI APIs

Hugging Face

LangChain

LLaMA models

b) Prompt Engineers

They create optimal SUIDs to:

Enhance accuracy of artificial intelligence

Decrease hallucinations

Produce customized reports for business applications

They integrate business requirements and AI possibilities by establishing:
•

Use Cases

Ethics guidelines

Deployment methods

d) MLOps and AI Infrastructure Specialists

They manage:

Deployment of model <

Scalability

Cost optimization

Cloud security and compliance

Security

2.4 Compensation Penalties for GenAI

GenAI professionals are charging 20 to 50% more pay when compared to the typical software developers in the similar experience range.

Theories

Unique skill set combination: AI + Domain Knowledge

Changing Technology
Today, technology

High Business Impact

Limited number of qualified talents
Limited

They prefer quantity to quality when it comes to recruiting for GenAI adoption.

E-Security: A Non-Negotiable

Gen AI is an innovation, but cybersecurity is survival.

3.1 Increasing Cyber Threat Landscape
Cy

Organisations are faced

Attacks by

Data breaches

Phishing et engineering socials

cloud misconfigurations

Cyber assaults conducted by

The damage caused by a single incident could cost in the region of millions of dollars.

3.2 Regulatory and Compliance Pressure

The

Countries have data protection laws that are being enforced:

GDPR

Digital Personal Data Protection Act in India

Industry-specific cybersecurity regulations

Violation of the requirement may entail:

Heavy fines

Operational shutdowns

Breach of customer trust

This means that cybersecurity is an investment that is mandatory and not optional.

3.3 In-Demand E

a) Cloud Security Engineers

They protect AWS, Azure, and GCP infrastructure.

b) Security Operations Center Analysts

They react to or monitor the threat in real time.

a) White Hat Hacker/CyberSecurity Specialist Midlands Cyber

They conduct attacks to know the loopholes.

d) Identity and Access Management Specialists

They manage access for users.

e) Cybersecurity Architects

They develop security frameworks for organizations.

3.4 Persistent Talent Shortage in Cybersecurity

Unlike traditional IT jobs:

Information security and upskilling
Ups

“Experience trumps credentials”

Errors carry heavy punishments

Despite this, there exists a shortage of cybersecurity talent in the global workforce, thus maintaining high pay rates and fueling the high demand for cybersecurity professionals.

Why GenAI and Cybersecurity Are Immune to Salary Cooling

4.1 Direct Impact on Revenue and Risk

GenAI increases productivity and innovation
There is an

“Cybersecurity protects against ‘C

They are directly connected with:

Business growth
In

Customer Trust

Legal compliance
The

Businesses are ready to pay top dollar to acquire talent.

4.2 Limited Automation of These Roles

Interestingly, although AI makes several jobs obsolete, jobs such as AI, as well as security-related jobs, are difficult to automate because:

Complexity

Context-dependent decision-making

Ethical considerations

4.3 High Cost of Skill Gaps

Engaging the wrong GenAi or recruiter will:

Display sensitive data

Cause system failures

Produce biased or unsafe AI output

This threat causes the companies to retain their best human resources.

Impact on IT Services and Indian Tech Industry

5.1. Service Companies vs. Product Companies

The traditional IT service providers face:

Pricing pressure

Automation

PACE speed reduces

On the other hand, product and platform businesses:

Aggressive investment in AI & Security

Pay more for ‘niche’ skills
If the best

This has widened the wage gap in the technology industry.

5.2 Shift from Mass Hiring to Skill-Based Hiring

Earlier:

Mass campus recruitment drives

Large training courses

Current:

Lateral hiring for specialized skill sets

Raining Dollars:

Fewer jobs of higher value

5.3 Tier -2 & Tier –

Telecommunications work, too,

Opportunities: Geographical Spread

Less location-based salary arbitrage

Nevertheless, GenAI and cybersecurity jobs are still rewarded at a metro level of compensation irrespective of their geographical location.

What This Means for Tech Professionals

6.1 Continuous Upskilling is Non

Professionals are required to

Go beyond simple programming
Developed by

Learn AI-assisted development

Learn basics of security

6.2 Domain Knowledge + AI = Career Growth

“The future belongs to those who combine intelligence and talent with character.”

Artificial Intelligence skills + finance

AI skills + Healthcare

AI skills + cybersecurity

Technically competent people are no longer adequate.

6.3 Certifications and Practical Experience Matter

In hot roles:

Projects are more important than Degrees

Open source contributions make it possible

Practical problem-solving is rated highly

Future Outlook: A Two-Speed Tech Job Market

The tech industry is now heading towards a two-tiered payment structure:

Slower Growth Segment:

Routine development

Legacy systems
These

Support and maintenance jobs

High-Growth Segment

Generative AI

Cyber Security

AI Governance & Ethics

Data engineering for AI
DB0S

Average increases in salaries may not be much, but outstanding performance will continue to receive outstanding compensation.

Conclusion: Quality Over Quantity in the New Tech Era
This slowdown in tech-related salary increases is not an indication of the end of the tech industry. It is rather an indication of its growth. Businesses are becoming more choosy about investing in individuals who contribute to innovation, efficiency, and safety. “The areas of generative AI and cybersecurity stand out for the following reasons: Solve urgent business problems High strategic value
There is high strategic Require rare and evolving expertise
In the federal context For professionals, there is an important reminder: Adapt, specialize, and remain relevant. “In a world where average is rewarded with average compensation,” Peter Drucker writes, “being future-ready is priceless.”