A common debate about the impact of AI on the workforce is the rate at which workers may be displaced as more repetitive tasks and basic analysis are automated – job displacement versus job creation. While AI is displacing roles that depend on routine, digital, rules-based tasks, it is also creating a demand for new roles and transforming other jobs by leveraging human-AI collaboration. But the impact of AI goes beyond just how work is performed. It is changing the nature of work, and therefore the roles of individuals in organizations and how companies prepare their workforces for those roles.
The Development Paradox
AI is eliminating, transforming, and creating jobs, continually reshaping requirements for success at both the individual and organizational level. This shift presents a quandary for leaders who must consider the productivity advantages of AI against the need to build capabilities and skills across their workforce, as well as determine what roles are needed to effectively perform the work and how they should be structured.
In an environment where the integration of AI and work is increasingly dominant, leaders must be able to balance opposing ideas and approaches that impact employee development and organizational growth. These fall broadly into three categories: Productivity Gains vs. Skills Erosion, Operational Efficiencies vs. Developing Talent Pipelines, and Jobs Based Talent Strategies vs. Skills-based Talent Strategies.
Productivity Gains vs. Skills Erosion
The efficiency advantages of AI are clear, with routine and repetitive tasks being completed in less time and with fewer resources. This is reflected in the reduction of roles in areas like data entry, call centers, and financial reporting. As AI automates tasks such as performance and compliance reporting, and allows teams to better self-organize around projects, supervisory layers are also reduced, flattening the organization, lowering costs and increasing productivity.
However, usage of AI can lead to key knowledge elements being lost. Think of it as always having the correct answer without an understanding of how that answer was derived. Disrupted career pathways, reduced training opportunities, and skill stagnation negatively impact employee development and can lead to less innovation in the workplace. Further, studies have shown that overreliance on AI can lead to a reduction in critical thinking, analytical, and problem-solving skills in the workforce.
The impact of AI goes beyond just how work is performed. It is changing the nature of work, and therefore the roles of individuals in organizations.
Operational Efficiencies vs. Developing Talent Pipelines
Used effectively, AI allows organizations to operate faster, with more accuracy, and at a lower cost by automating routine work, sharpening decisions with data, and coordinating processes. In leveraging AI-based technologies, organizations can scale operations without a proportional increase in hiring. This lets employees focus on more strategic, high-value work, and shifts the role of managers towards coaching, leading change, and problem-solving.
A challenge is some of the roles being reduced or eliminated have traditionally served to train entry-level employees or provide career progression for experienced workers. Through entry level roles, employees learn foundational business skills such as how organizations work, influencing and stakeholder management, and learning from failure. This means fewer employees gain the experiences needed to develop judgment for higher level roles. In addition, with fewer entry level jobs, pathways for first generation college graduates, those making career changes, and under represented groups narrow, which can decrease diversity and future leadership representation.
Jobs Based Talent Strategies vs. Skills-based Talent Strategies
Traditional talent strategies focus on the requirements and credentials for a specific role. The desire is to identify candidates whose backgrounds and education exactly match the role requirements, with the job description emphasizing formal qualifications, years of experience, and detailed job responsibilities. Employee advancement follows a hierarchy, with individuals moving from one role to the next on a defined career ladder or path.
By contrast, skills-based talent strategies deconstruct roles and prioritize specific skills and competencies, along with the individual’s potential, over degrees or previous job titles/roles. Organizations can better match employees to projects based on their skill set and hire for specific skills. This approach also provides broader job opportunities for talent without the traditional credentials. The focus on what people can do helps organizations to be agile and diverse, creating more equitable and flexible career pathways.
Both job and skill-based strategies, or a hybrid, are appropriate based on the needs of the organization. Virtually all jobs will see some change in their requirements, and the ability to quickly upskill and reskill talent at scale given these changes will be important.
Human-AI Collaboration
Despite its advantages, employees have been slow to adopt AI. While organizational leaders are enthusiastic about AI usage, employees do not mirror that enthusiasm due to fears about job security, and a lack of engagement and voice in the decisions to use AI in their jobs. Various researchers have identified a lack of trust as a key factor in the slower adoption of AI by employees, and the mistrust is amplified when employees feel AI has been forced upon them by their leaders. The pressure to adopt AI may make employees less likely to share ideas or take risks, fearing that mistakes could accelerate their replacement.
Yet trust can increase rapidly when employees gain experience using AI and find practical solutions to help them do their jobs. The fall 2025 Edelman Trust Barometer Flash Poll: Trust and Artificial Intelligence at a Crossroads found that hands-on experience is the fastest route to trust. The more people use AI, the more they trust it, and the more they trust it, the faster they embrace it. Organizations can improve employee adoption of AI by making it safe and simple to use. Start with real use cases and treat AI simply as a change in how work gets done. Address fear and resistance directly through creating two-way communication channels, and help employees to understand AI as a core career skill for staying relevant.
When employees are comfortable using AI, organizations benefit from a collaborative approach that enhances productivity while maintaining the judgement, creativity, and problem-solving necessary for making complex decisions.
Conclusion
AI presents many opportunities and challenges, with fundamental changes to how employees develop the required skills and capabilities their organizations need. To stay ahead of these changes, organizations must plan for the transition. This means assessing and realigning your talent strategy, and investing in the right infrastructure, practices, and processes to support reskilling and internal mobility.
In the age of AI, talent development is rapidly evolving to focus on individualized paths that build the skills, knowledge, behaviors, and expertise required. AI tools can curate content, answer questions in the moment, and integrate training into daily workflows to accelerate learning and mastery. It could be the breakthrough that provides the necessary scale and speed to more effectively develop talent.
With intentionality, AI can enrich employee growth and learning through honing existing skills and providing targeted development to enable the development of new ones.
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