AI Skills to Develop in 2026 and Beyond
AI is quickly becoming entrenched in the workplace. Organizations of all sizes and in every industry are taking advantage of chatbots. AI agents and analytics capabilities are embedded into business applications. However, many organizations struggle to take full advantage of their AI investments.
In a recent Salesforce survey, 95 percent of business leaders said that integrating AI into their operations remains a significant hurdle. The biggest challenge is outdated IT infrastructure, followed by cybersecurity. However, organizations are also having trouble finding people with the skills needed to use AI effectively.
Organizations need professionals with expertise in AI-enabled cloud platforms, software programming, agentic AI coding and data science and analytics. However, nontechnical staff must also have a range of AI skills. Employees in virtually every role will need the ability to interact with AI.
These skills enable any professional to enhance their productivity using AI tools:
Prompt Engineering: The ability to craft clear, contextual, and iterative queries to get accurate results from AI models.
Critical Thinking & Evaluation: Validating AI outputs for errors, “hallucinations” (plausible but false facts), biases, and logical consistency.
AI Ethics & Bias Awareness: Recognizing ethical risks such as data privacy concerns and algorithmic bias in automated decision-making.
Tool Proficiency: Staying updated on a diverse array of task-specific tools for writing, design, data analysis, and workflow automation.
As AI automates routine tasks, human-centric “soft” skills have also become extremely important. Organizations value workers who can communicate, collaborate, and think critically. Humans can manage relationships and build trust in ways machines cannot. We also have the ability to understand the broader organizational context and business objectives to decide when and how to apply AI effectively.
Human adaptability and insight are essential to identifying the right challenges to tackle and breaking them into manageable sub-tasks for AI assistance. Cross-functional skills are also important given that AI agents collect, analyze and act on data from across the enterprise.
Workers need to remain adaptable as AI capabilities continue to evolve rapidly. Continuous up-skilling and practical learning will be essential to remain competitive and valuable to employers.