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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Last Update: 4/23/2026
Your role’s AI Resilience Score is
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
High
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
Training and Development Managers are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.
Training and development managers are labeled as "Mostly Resilient" because while AI can help with routine tasks like drafting course outlines and generating test questions, it doesn't replace the need for human skills such as empathy, personal feedback, and creativity. AI tools speed up content creation and analysis, allowing managers to focus more on hands-on training and mentoring, which are crucial human elements in this field.
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Learn more about how you can thrive in this position
This role is mostly resilient
Training and development managers are labeled as "Mostly Resilient" because while AI can help with routine tasks like drafting course outlines and generating test questions, it doesn't replace the need for human skills such as empathy, personal feedback, and creativity. AI tools speed up content creation and analysis, allowing managers to focus more on hands-on training and mentoring, which are crucial human elements in this field.
Read full analysisAnalysis of Current AI Resilience
Training & Dev. Managers
Updated Quarterly • Last Update: 2/17/2026

Training and development managers create and organize educational materials and run learning programs. Today, AI tools are starting to help with those tasks. For example, new generative AI systems (like GPT models) can draft course outlines, write parts of manuals or quizzes, and even suggest multimedia content for training [1] [2].
One industry report notes that some companies already use AI to generate learning content and test questions on their training platforms [2]. AI-powered chatbots can even guide learners during training – helping them plan actions, reflect on progress, and practice skills [2]. In other words, many routine parts of building courses are being augmented by AI.
However, experts stress that AI is not replacing human trainers. For instance, the research found that AI can give a solid first draft of course material, but course designers still need to review and refine it [1]. Likewise, a CIPD report warns that AI must be used carefully in learning and development – algorithms can be biased or wrong, so human oversight remains essential [2].
In practice, AI is helping training managers work faster (by generating content or analyzing data), but human skills like empathy, personal feedback, and creativity are still crucial.

Companies are adopting AI in training at a steady pace, driven by easy availability of tools and clear benefits. Today there are many AI content-creation tools and learning platforms at low cost, so employers can try AI without huge investment. Research even suggests that extra training gives strong returns: one study found companies got about $4.23 back in productivity for each $1 spent on employee training [3].
This kind of evidence makes firms eager to improve training, for example by using AI to personalize programs or speed development. In fact, a Deloitte survey cited in the CIPD report found over 50% of companies already use some AI in employee learning programs [2]. At the same time, adoption can’t happen overnight.
Training and development work is highly human: people-to-people guidance, nurturing skills, and understanding each learner. The Bureau of Labor Statistics notes there are about 46,000 training managers in the U.S. and the job is still growing [4], implying that companies aren’t just replacing them with machines. Cultural and ethical concerns also play a role: employers worry about data privacy and about AI repeating biases, so they move carefully.
Overall, AI is increasingly used to augment training (by creating materials, analyzing skill gaps, and supporting learners), and many organizations are adopting it [2] [3]. But human judgment, mentoring, and creativity remain highly valued—so AI takes over routine tasks while people focus on personal coaching and hands-on training.

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They help employees learn new skills by planning and directing training programs, making sure everyone can do their jobs better.
Median Wage
$127,090
Jobs (2024)
46,400
Growth (2024-34)
+5.8%
Annual Openings
3,800
Education
Bachelor's degree
Experience
5 years or more
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Prepare training budget for department or organization.
Conduct orientation sessions and arrange on-the-job training for new hires.
Evaluate instructor performance and the effectiveness of training programs, providing recommendations for improvement.
Conduct or arrange for ongoing technical training and personal development classes for staff members.
Analyze training needs to develop new training programs or modify and improve existing programs.
Confer with management and conduct surveys to identify training needs based on projected production processes, changes, and other factors.
Coordinate established courses with technical and professional courses provided by community schools and designate training procedures.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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