By Qudsia Bano

Global hiring demand for data and artificial intelligence professionals has rebounded sharply in 2026, with job postings jumping more than 80% year-on-year as demand accelerates for AI engineers and professionals combining programming, database, communication and AI capabilities.

DataCamp's The State of AI Careers 2026, based on an analysis of two million unique job postings across 85 regions worldwide, shows that the data and AI labour market has moved from hiring stagnation into a strong recovery, with specialised AI positions recording particularly rapid growth.

The report, available with Wealth Pakistan, analysed hiring demand between January 2024 and May 2026 across 25 positions spanning AI and machine learning, data science and applied analytics, data engineering and infrastructure, and data leadership and foundational software roles. Duplicate advertisements for the same vacancy appearing across different platforms were removed from the dataset.

The hiring trajectory shows a marked turnaround. Job postings declined slightly during 2024 and remained largely stagnant through the first half of 2025 before beginning to recover later in the year. Hiring demand then accelerated sharply in early 2026, suggesting companies may be moving beyond the conservative planning phase of 2025 towards actively funding and staffing AI initiatives.

The shift becomes particularly clear when comparing first-quarter hiring demand. Data and AI job postings fell 9.8% year-on-year to 487,069 in the first quarter of 2025, from 540,051 a year earlier. They subsequently surged to 877,850 in the first quarter of 2026, an increase of 80.2% year-on-year.

Specialised AI positions are leading the expansion by a wide margin. AI engineer roles grew 255% year-on-year, while generative AI engineer positions increased 197%, according to the report. Both categories offer median base salaries above $100,000, with their rapid growth suggesting companies are actively seeking professionals capable of implementing AI systems.

Strong demand is not confined to roles explicitly carrying an AI title. Infrastructure-oriented positions such as data engineer, Python developer, data architect and machine learning engineer also rank high on the growth ladder as companies develop the foundational pipelines required to support AI systems.

Median salaries for these infrastructure-heavy roles range from around $95,000 for Python developers to $175,000 for machine learning engineers, according to the report.

Traditional analytics occupations remain an important part of the market, although their growth is slower. Data analysts, data scientists and business intelligence analysts sit below the 50% year-on-year growth threshold, with median salaries ranging from around $70,000 to $120,000.

Leadership positions command some of the highest compensation. Data science managers, data analytics managers, analytics product managers and chief data officers consistently record median salaries above $120,000, while the median salary for a data science manager approaches $190,000, the highest among the positions analysed.

Beyond particular job titles, the analysis identifies a common skills foundation that determines employability across the data and AI sector.

Of the 25 occupations studied, Python, communication, SQL and computer science appeared as key requirements across all 25. AI knowledge followed closely, appearing as a core competency in 22 of the 25 roles. The report notes the four universal competencies consistently rank among the most frequently requested qualifications in employer postings, making them functionally important for candidates seeking to pass initial résumé screening.

Growing exposure to AI is also associated with higher rather than lower compensation.

The report cites labour-market research showing that a 10% increase in AI exposure is associated with a 25% higher salary. Separate research cited in the report found that workers with AI skills commanded a 56% wage premium in 2025, up from 25% the previous year.

Employers are also increasingly willing to pay more for broader AI and data literacy rather than reserving salary premiums exclusively for highly specialised engineers. DataCamp's separate 2026 literacy research found that 74% of leaders were willing to offer higher salaries to candidates with good data literacy, while 69% were prepared to pay more for candidates demonstrating good AI literacy.

The majority of salary premiums employers were prepared to offer for strong data and AI literacy fell between 10% and 30%.

The findings suggest that the expanding data and AI labour market is rewarding a combination of specialised technological capabilities and transferable skills. While advanced AI positions are recording the fastest growth, communication remains a universal requirement alongside Python, SQL and computer science.

The report concludes that workers seeking long-term career advantages should build foundations in programming, computer science, database management and communication before adding explicit AI competencies, including prompt engineering, agent management and domain-specific AI applications.

With data and AI hiring demand recovering strongly from the stagnation of 2024 and early 2025, the report indicates that labour-market opportunities are increasingly favouring professionals who can combine conventional technical foundations with practical AI capabilities.

Credit: INP-WealthPk