Artificial Intelligence (AI) is the latest trend, and it is no surprise that its use in assessments is growing. But the data also shows that companies are actually testing for thinking skills more than AI usage skills.

• The skills with the highest relative growth were
  • programming (+54x share),
  • problem solving (+39x), and
  • data visualisation (+35x).

• ChatGPT-enabled assessments were still in the experimental phase, reaching about ~2.5% of events by December, but this is 2.5x growth from just ~0.9% in January. Adoption also showed sharp month-over-month spikes and a small set of companies repeatedly enabled ChatGPT across multiple events

Insight: Companies are moving away from asking "Do you know this specific syntax?" to "Can you solve this problem and visualise the result?" As for using ChatGPT to assist in assessments, even though the absolute number looks small, this is not stagnation—it’s classic early-stage platform adoption. Going forward, more companies are evaluating how candidates work with AI, not whether AI replaces them. This also means that candidates who can explain how they apply fundamentals in real scenarios gain an edge in 2026.

The data shows a decisive move toward stricter assessment environments to combat cheating and ensure quality.

• Adoption Growth: The share of companies using proctoring grew from 64% in January to a peak of 77% in July.
• Standardisation: By the end of the year, nearly 2 out of 3 events (64.5%) were proctored.

Insight: The "honor system" is dead in tech hiring. Companies are willing to add friction (proctoring) to the process to guarantee that the high scores during assessments are legitimate. Candidates should also expect verified, monitored evaluations to be the norm.

As we evaluated skills used by companies when creating assessments, four major skill clusters appeared. Together, these clusters reveal how hiring priorities evolved—and what stayed constant throughout the year.

These clusters are:

1. Foundational CS & Logic (The core)
2. Full Stack Engineering (Enterprise Workhorse)
3. Data and AI Engineering (Modern Standard)
4. Cloud & DevOps (Volatile Specialist)

Foundational CS and logic skills sit at the core, powering full-stack engineering, data and AI engineering, and—more selectively—cloud and infrastructure expertise. Our data shows that companies consistently evaluate skills in this layered, connected way, rather than treating each skill in isolation.

• Cluster 1: "Foundational Problem Solving & Algorithms" (The core)
  • Composition: Algorithms, Data Structures, C++, Mathematics, Logical Reasoning.
  • Usage: This is consistently the most used cluster, with 95% of the companies adopting it per month.
  • Insight: This cluster acts as the primary filter for the massive candidate volumes. Most entry-level/fresher hiring happens via this cluster of skills. Companies need a solid foundation for people they are hiring for, and this cluster evaluates the necessary skills for that.
• Cluster 2: "Full Stack Engineering" (Enterprise Workhorse)
  • Composition: Java, Spring, .NET, React, Angular, Microservices.
  • Usage: Strong engagement. About 75-80% of the companies use skills in this cluster
  • Insight: This cluster drives the "Mid-Year Hiring" (July-Sept). It represents the practical, job-ready skills needed for immediate project deployment.
• Cluster 3: "Data & AI Engineering" (The Modern Standard)
  • Composition: Python, SQL, Machine Learning, Data Science, Pandas.
  • Usage: Tracks closely with Cluster 2
  • Insight: Python and SQL have graduated from "specialist" skills to generalist requirements, now nearly as ubiquitous as Java for backend roles.
• Cluster 4: "Cloud & DevOps" (The Volatile Specialist)
  • Composition: AWS, Azure, Docker, Linux.
  • Usage: Lower volume and also higher volatility.
  • Insight: Hiring for these roles occurs in specific bursts rather than a steady stream, suggesting targeted hiring campaigns for infrastructure teams.

The 2025 job market appears stable but cautious, characterised by steady mid-year hiring, selective expansion by a subset of companies, and no broad-based contraction. Hiring intent was present but disciplined rather than aggressive. Hiring did not accelerate broadly, but it also did not contract.

• Hiring demand is steady, not collapsing:

From March through November, the number of candidates assessed remained consistent in the average range per month, with a gentle rise into mid-year and a gradual taper toward year-end. There is no multi-month stagnation, and activity resumed quickly after dips, indicating ongoing hiring, not hiring freezes.

• Mid-year hiring strength signals real demand:

Assessments created peaked in July–September, as they do every year, driven by the hiring of fresh graduates. November also saw a spike in assessment creation, indicating that companies are getting ready for campus hiring season in early 2026. Because assessments created precede candidates assessed, this is a forward-looking signal and indicates a healthy hiring market in 2026.

• The market is selective, not broad-based:

Top companies account for a disproportionate share of assessments, while a long tail of companies assess fewer candidates. Some companies clearly expanded hiring mid-year, whereas others remained flat or episodic. There is no synchronized pullback

For 2026, we expect steady hiring with disciplined screening, not rapid expansion or freezes.

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While new technologies emerge, the data confirms that foundational technical skills remain the absolute gatekeepers for employment. These skills appear in the highest volume of assessments and are non-negotiable for most technical roles.

The "Big Three": Algorithms, SQL, and Data Structures are the top three most assessed skills by volume.

Language Leaders: Java and Python continue to dominate as the primary programming languages for assessments, significantly outpacing others like C++ or JavaScript.

Adoption Consistency: Core skills like algorithms and SQL are adopted by the widest range of companies, making them the safest bet for candidate preparation.

Takeaway

Despite growing interest in AI and emerging technologies, foundational skills remain non-negotiable for tech hiring

For candidates in 2026: Mastery of fundamentals is still the fastest path to employability.

For companies: Foundational skills continue to be the most reliable hiring signal based on what your peers are doing