The most in-demand AI skills

Steven

The most in-demand AI skills

Summary

The enterprise AI landscape has shifted from experimentation to operational, agentic systems. Organisations now need teams that can design secure, scalable AI platforms, build agentic retrieval and orchestration architectures, and operate LLMs safely at scale. The article groups essential skills into five categories—technical foundations, AI development, AI-native software engineering, operational and risk-related skills, and business/strategic skills—and lists representative tools and frameworks for each. It also gives guidance on which skills to keep in-house versus outsource, and practical steps to develop and retain talent.

Key Points

  • Technical foundations: platform/cloud architecture, AI-ready data engineering, agentic RAG and knowledge retrieval, API/agent protocol orchestration.
  • AI development: applied ML engineering, agentic and multi-agent engineering, context engineering, fine-tuning and prompt engineering.
  • AI-native software engineering: AI-assisted coding and agent orchestration require specification, validation and review processes to avoid technical debt and security risks.
  • Operational and risk skills: LLMOps/MLOps, observability and cost management, output validation & QA, AI security, governance and model risk management.
  • Business skills: human+AI workflow design, change leadership, AI product management and portfolio prioritisation for measurable ROI and reduced shadow AI.
  • Hire vs. outsource: keep high-risk, highly integrated and strategically differentiating skills (e.g. agentic RAG, governance, LLMOps, validation) in-house; outsource more commoditised services with tight internal controls.
  • Develop and retain talent: perform a skills inventory, map skills to the AI roadmap, launch targeted upskilling (DevOps→LLMOps, QA→AI QA, security→red-teaming), partner with vendors with clear control points, and track delivery, cost and risk KPIs.

Why should I read this?

Short: if you run or hire for enterprise AI, this is worth your five-minute skim. It neatly organises the messy reality of agentic systems and shows what to hire, train or outsource next. We’ve pulled out the practical bits—where risk lives, which skills are non-negotiable in-house and how to keep talent—so you can act faster and avoid costly mistakes.

Author take

Punchy: this isn’t an academic list — it’s a playbook for CIOs and IT leaders. The shift to agentic AI is real and fast; the firms that codify skills into career paths, measurement and governance will scale AI safely, the rest will inherit chaos and audit headaches. Read the detail if you need to operationalise AI without exposure.

Source

Source: https://www.techtarget.com/searchcio/tip/In-demand-AI-skills