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AI Skills Now Pervasive for Tech Jobs

AI roles now dominate tech market growth, according to ICT in Motion: The Next Wave of AI Integration, a new report from the AI Workforce Consortium.

Led by Cisco, the Consortium is a private sector collaboration that includes Accenture, Cornerstone, Eightfold AI, Google, IBM, Indeed, Intel, Microsoft and SAP.

Key Findings from the 2025 Report:

  • AI Skills Are Now Pervasive for Tech Jobs: 78% of the job roles analyzed include AI skills, highlighting a shift in role requirements across the G7.
  • AI Roles Dominate Technology Job Market Growth: 7 of the 10 fastest-growing ICT roles are AI-related, including AI/ML Engineer, AI Risk & Governance Specialist and NLP Engineer.
  • AI Ethics and Governance Skills Remain Critical: Demand for skills in AI Governance is +150% and AI Ethics +125%, reflecting the need for expertise at the intersection of technology, law and ethics.
  • Critical Technical Skills Deficit and Rising Importance of Human Skills: The skills deficit has reached critical levels in areas such as generative AI, large language models (LLMs), prompt engineering, AI ethics and AI security, while human skills like communication, collaboration and leadership are increasingly prioritized for responsible technology adoption.
  • Surge in Specialized AI Skills: The AI landscape is quickly shifting from chatbots to agents, driving demand for specialized skills, including AI security +298%, foundation model adaptation +267%, responsible AI +256% and multi-agent systems +245%.
  • Accelerated AI Job Growth Driven by Tech Hubs: Silicon Valley leads with a 156% increase in AI jobs, followed by London and Toronto, underscoring their status as global AI powerhouses, while Manchester, Lyon and Vancouver are emerging hubs with over 70% AI job growth.

Methodology: The report is based on extensive job posting data from Cornerstone and Indeed between July 2024 to June 2025 across G7 countries, including Canada, France, Germany, Italy, Japan, the UK and the United States, this latest edition arrives at a pivotal moment as AI continues to reshape economies, societies and global governance.

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Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...

AI Skills Now Pervasive for Tech Jobs

AI roles now dominate tech market growth, according to ICT in Motion: The Next Wave of AI Integration, a new report from the AI Workforce Consortium.

Led by Cisco, the Consortium is a private sector collaboration that includes Accenture, Cornerstone, Eightfold AI, Google, IBM, Indeed, Intel, Microsoft and SAP.

Key Findings from the 2025 Report:

  • AI Skills Are Now Pervasive for Tech Jobs: 78% of the job roles analyzed include AI skills, highlighting a shift in role requirements across the G7.
  • AI Roles Dominate Technology Job Market Growth: 7 of the 10 fastest-growing ICT roles are AI-related, including AI/ML Engineer, AI Risk & Governance Specialist and NLP Engineer.
  • AI Ethics and Governance Skills Remain Critical: Demand for skills in AI Governance is +150% and AI Ethics +125%, reflecting the need for expertise at the intersection of technology, law and ethics.
  • Critical Technical Skills Deficit and Rising Importance of Human Skills: The skills deficit has reached critical levels in areas such as generative AI, large language models (LLMs), prompt engineering, AI ethics and AI security, while human skills like communication, collaboration and leadership are increasingly prioritized for responsible technology adoption.
  • Surge in Specialized AI Skills: The AI landscape is quickly shifting from chatbots to agents, driving demand for specialized skills, including AI security +298%, foundation model adaptation +267%, responsible AI +256% and multi-agent systems +245%.
  • Accelerated AI Job Growth Driven by Tech Hubs: Silicon Valley leads with a 156% increase in AI jobs, followed by London and Toronto, underscoring their status as global AI powerhouses, while Manchester, Lyon and Vancouver are emerging hubs with over 70% AI job growth.

Methodology: The report is based on extensive job posting data from Cornerstone and Indeed between July 2024 to June 2025 across G7 countries, including Canada, France, Germany, Italy, Japan, the UK and the United States, this latest edition arrives at a pivotal moment as AI continues to reshape economies, societies and global governance.

Hot Topics

The Latest

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...