Competency at Risk: Managing AI's impact on People Development

By Hubert Saint-Onge

Relying on AI at lower levels within an organization can truncate the development of crucial competencies at intermediate and higher levels. Without mitigating measures, the development of people and the realization of their leadership potential will be negatively affected. This challenge arises from several interconnected factors that influence the composition of work and the development of competence-building pathways. An even deeper concern underlying the impact of AI is the potential for eroding organizational capability due to the disruption of competency development pipelines across organizational levels.

The objective of this article is to explore the dynamics involved and find ways to mitigate the risks. We examine AI-driven displacement patterns and their second-order effects on competency development. We are essentially asking whether AI creates a ‘missing middle’ challenge which impedes the advancement of people to higher leadership levels. The all-too-often unspoken fear is the ‘hollowing out’ of organizations caused by AI.

1. Skill Dependency and Automation

The World Economic Forum's 2025 Future of Jobs Report assesses that AI and automation will have displaced approximately 85 million jobs globally by the end of 2025. Most of the roles affected involve routine tasks that can be easily automated using AI to perform repetitive functions and improve efficiency. For instance, AI systems can readily automate tasks like scheduling, data entry, and even aspects of patient care roles in healthcare. Employees in such roles may find themselves increasingly sidelined or entirely replaced by AI technologies, not only in healthcare but also in other sectors, such as manufacturing and finance. Organizations are still navigating the integration of AI and assessing its long-term implications for the workforce. While 14% of global workers have already experienced job displacement due to AI, this impact is far from the levels that will eventually be reached in the relatively near future.

As AI systems increasingly take over routine and operational tasks, employees at lower levels may become overly reliant on these technologies. For instance, if entry-level employees are tasked with using AI-driven platforms for data entry, report generation, or customer service interactions, they may not develop the foundational skills necessary to perform these tasks effectively over time. This reliance can lead to a lack of understanding of the underlying processes and critical thinking skills that are essential when moving into more complex roles. For example, let’s assume an employee is not trained to interpret data independently because they always rely on AI-generated insights; they may struggle when faced with strategic decision-making responsibilities later in their career.

2. Implications for Competency Development

The displacement of jobs by AI raises significant concerns regarding competency development within organizations. As roles evolve, there is a pressing need for employees to reskill and upskill to remain relevant. The Future of Jobs Report notes that around 40% of core skills demanded by employers are expected to change, highlighting a shift towards competencies that complement AI rather than compete with it. For example, soft skills like emotional intelligence, creativity, and advanced problem-solving will be essential for navigating an AI-augmented workplace.

Organizations may face challenges in promoting competency development as traditional pathways for career advancement are disrupted. If lower-level positions are diminished or eliminated, the upward mobility of employees may be hindered, potentially leading to a loss of expertise at different levels in the organizational hierarchy. This is particularly concerning in organizations where in-depth institutional knowledge and expertise are essential for informed strategic decision-making.

AI experts reinforce the view that this technology is advancing at a rapid pace and gradually penetrating higher-level functions. While initially, AI applications had an impact mostly at lower levels of the organization, the progression of AI is such that it is rapidly being adopted at higher levels of organizations. As the adoption of AI permeates vertically higher organizational levels, we are likely to experience a systematic depopulation of competencies that could significantly impact organizational capabilities such as strategic acumen and agility? 

3. The SAM100 case as an illustration

The SAM100 (short for Semi-Automated Mason), manufactured by Construction Robotics, was seen as a highly innovative bricklaying robot when it was launched in 2014. The robot could lay more than 3,000 bricks per day, six times as many as a human mason. However, the sales of the robots were nowhere near as impressive as their productivity. Adoption proved to be slow.

Over time, more subtle factors emerged as possible causes of the contractors’ hesitation to buy these robots. The brick-laying industry has experienced chronic skills shortages. It is well-known that contracting companies have been struggling to find qualified labour. If this was the case, one could ask why were contractors hesitating to buy the robots despite flexible purchasing arrangements? As it turns out, skills development became a significant point of contention. Less skilled workers became ‘tenders’ with tasks that consisted of feeding mortar and bricks to the robot. However, the robot was unable to perform the finishing joints. A more experienced and skilled mason had to follow behind the robot to strike the finishing joints.  

In Canada, Europe and the US, an apprenticeship is the recommended path to becoming a bricklayer. Government-sponsored bricklayer apprenticeships are three-year programs that offer structured training and are often preferred by employers. Being a ‘tender’ of the brick-laying robot could never count as part of an apprenticeship program because it does not contribute to the development of brick-laying skills.  A ‘tender’ could never acquire the skills needed to strike finishing joints. This was the question that bricklaying contractors faced: should they invest in a bricklaying robot, would their operations be limited by the lack of skilled workers to strike finishing joints? The technology-based barrier to the development of entry level workers became the obstacle to buying the brick-laying robots.  

A parallel be drawn with regards to AI advancement in organizations and its impact on competency development. The question the SAM100 case raises is whether people using AI in the middle layers of the organization become the ‘tenders’ of AI, applying its functionality to build greater efficiency without needing the inherent exercise of judgment. Does this activity, in fact, lead to the deferral of the development of critical and strategic thinking, as well as the social judgment they will need at their level and beyond?  As ‘tenders’, will they miss the essential competency development that would otherwise qualify them to keep progressing in the organization?

4. Reduced Exposure to Complex Problem-Solving

AI tools can streamline workflows and enhance efficiency; however, they can also limit employees' exposure to complex problem-solving scenarios. When lower-level positions are heavily automated, employees miss opportunities to engage in critical thinking and decision-making processes, which are vital for higher-level competencies. For example, a customer service representative who relies on AI for troubleshooting may not develop the nuanced understanding required to handle escalated issues effectively. This lack of a more rounded experience can hinder career progression because higher-level roles often require a nuanced understanding of complex situations and the ability to navigate them judiciously.

5. Erosion of Soft Skills

Overly relying on AI can hinder the development of essential soft skills, such as communication, collaboration, and emotional intelligence. As AI increasingly takes over interactions, whether in customer service, project management, or team collaboration, employees at lower levels may have fewer opportunities to develop their interpersonal skills. Without these competencies, employees may struggle to transition into roles that require team leadership or stakeholder engagement. For example, an employee accustomed to mainly interacting with AI systems may struggle to communicate effectively with colleagues or clients when transitioning into a higher-level role.

6. Organizational Layers and Competency Loss

As AI becomes more prevalent, organizations may inadvertently lose competencies essential for future success. The reliance on AI for decision-making can lead to a dilution of critical thinking and analytical skills among employees, as they may become overly dependent on automated systems for insights and guidance.

When AI takes over decision-making and operational tasks, there is a risk of eroding competencies in the middle levels of the organization, resulting in what is often referred to as the ‘missing middle’, an organizational stratum that has historically been critical to the development of future leaders. When the automation driven by AI becomes increasingly pervasive across an organization, it is likely to erode the leadership skills essential for upward mobility. When this starts to happen, it is necessary to implement interventions that mitigate this impact. For example, if mid-level managers are replaced by AI systems capable of data analysis and report generation, there may be fewer individuals available to strategically interpret these insights. This could lessen the organization's ability to innovate and respond effectively to market changes.

Middle management has traditionally served as a vital conduit between strategic leadership and frontline employees. Effective middle managers possess a unique blend of technical expertise, social intelligence, and leadership skills, which fosters effective communication and mentoring. Middle management also plays a crucial role in translating high-level strategies into readily actionable operational steps. Middle managers are often responsible for developing talent, resolving conflicts, and fostering a collaborative culture. Their growth into higher leadership roles relies heavily on hands-on experience, social skills, and opportunities for decision-making at a level that encourages personal development. This represents a developmental capacity necessary for cultivating the leadership pipeline that sustains organizational resilience over time.

While the elimination of managerial roles can lead to a flatter, more efficient organizational structure, it can also reduce the diversity of thought and experience within a leadership team.  The absence of diverse perspectives can stifle adaptability and resilience, the vital strengths of teams in an ever-changing business environment. When this happens, the organization loses its resilience and ability to respond effectively. It is therefore imperative that organizations explore ways to address the propensity for AI to weaken the organization by engendering a ‘missing middle’ challenge.

7. Organizational and individual development implications

Organizations must proactively consider strategies for competency development that not only address the immediate impacts of AI but also foster a culture of continuous learning and adaptability. An organization that successfully integrates AI at lower levels may inadvertently foster a culture that prioritizes efficiency over learning and development. If employees are not encouraged to question, innovate, and engage with their work on a deeper level, their organization may face a stagnation of ideas and a lack of proactive problem-solving. The result may be a workforce that is less equipped to handle the challenges faced at higher levels of the organization, ultimately impacting the organization's overall effectiveness.

Individuals who emerge from roles that heavily utilize AI may find themselves at a disadvantage when competing for higher-level positions. The gap in competencies developed in lower-level roles can become apparent during performance evaluations and when considering people for advancement to higher-level roles. Organizations that do not actively support competency development across all levels may inadvertently create a talent pipeline that lacks the depth and breadth of skills required to be a dynamic force in the marketplace.

8. How to address the erosion of middle management competency

The increasingly widespread use of AI at the middle management level necessitates concrete actions to adapt to this new reality. When there is such a radical change in the tools used to get work done, a corresponding change is needed in how individuals perform their work and develop their competencies. Beyond that, AI's infiltration into workplaces can inadvertently weaken the social and leadership skills essential for upward mobility and an effective talent pipeline for organizational succession. How can organizations best mitigate these significant risks associated with the emergence of AI?

Mitigation measures, such as delayering and work redesign, must be implemented to address the challenges involved. For instance, processes and structures need to be updated to align with the evolving nature of work in the era of AI prevalence. Solutions must be found to address the loss of opportunity for competency-shaping experiences and the resulting loss of both articulated and tacit knowledge.  Employees must be expected to complement the use of AI by incorporating critical thinking and judgment into their work. Broken progression pathways must be rectified to align with the new tools and the way work gets done. Leaders must define where people must exercise human-driven judgement and articulate the logic supporting AI-generated recommendations.

A framework must be in place to identify where, in the organization, human judgment is critical. There should be an audit to identify deskilling risks, such as over-reliance on predictive analytics, which can erode diagnostic skills. An architecture must be developed to preserve opportunities for skill development and identify specific tasks (eg drafting initial client proposals) that should not be given access to AI support. On a broader scale, it is also essential to provide employees the ability to override AI recommendations when they, for instance, clash with human values. By selectively preserving human judgment zones, organizations avert deskilling risks and the displacement of people who have the experience to excel in higher-value roles. When AI is given the license to exercise judgment without human overlay, there is a corresponding loss of insight that is irrecoverable.

Conclusion

The integration of AI into the workforce presents both challenges and opportunities as it reshapes not only work but also competency development in organizations. As AI transforms traditional job roles, employees will need to adapt by acquiring new skills that align with the evolving demands of these roles. Organizations must be vigilant in recognizing the potential loss of critical competencies and strive to create pathways for development that embrace both technological advancements and the irreplaceable value of human skills. By doing so, they can ensure sustained organizational effectiveness and resilience in the face of ongoing technological disruption.

While AI has the potential to enhance efficiency and productivity at lower organizational levels, it can also hinder the development of essential competencies required for higher-level functions. The implications of AI on competency development within organizations are profound, particularly as this technology continues to evolve and displace traditional job roles across various levels of the workforce. When automation takes over routine decision-making and operational tasks, there is an organizational risk of ending up with a ‘missing middle’, which is not only where fundamental skills are acquired, but also where strategy is translated into execution. Letting go of people with the rationale that those remaining will then be able to gravitate to higher value-added activities is not a viable option without thoughtful preparation.    

Organizations must be mindful of this potential downside and implement strategies to ensure that employees at all levels are equipped with the skills necessary for both current and future roles. This may involve creating opportunities for hands-on learning, fostering a culture of continuous improvement, and providing pathways for skill development that go beyond mere task execution. By doing so, organizations can build a more capable and resilient workforce prepared to navigate the increasing complexities of the business environment with the compelling support of AI.

Adopting AI is imperative for organizations, but doing so without thoughtfully applied organizational safeguards is foolish. Organizations must reframe their thinking to avoid being passive victims of AI-caused disruptions to become active designers of human competencies in the context of an increasingly pervasive and powerful AI presence. The key is to structure new roles and processes that leverage technology with irreplaceable human capabilities.   

I’m grateful to Dr. Ralph Oliva, Professor of Marketing at Penn State, for sharing information and insights on the SAM100 case.