The Reality of AI in the Workplace and its Impact on Entry-Level Jobs

Executive Summary

The rise of AI in the workplace has sparked both excitement and concern—especially around its impact on entry-level jobs. While headlines often warn of junior roles disappearing, our survey of 2,000 professionals, including HR leaders, reveals a more balanced reality.

AI is transforming how companies operate by automating repetitive, low-value tasks. But rather than eliminating entry-level jobs, it’s reshaping them. Most organizations continue to hire early-career talent, while evolving the structure of these roles, increasing skill requirements, and rethinking onboarding and development.

AI adoption is widespread, particularly for data analysis, training, and onboarding. Yet full automation of entry-level roles is rare. Instead, AI frees up employees—including new hires—to focus on more strategic, creative, and people-focused work.

Experience still matters. Entry-level roles remain a critical foundation for skill-building and career growth. Internships, apprenticeships, and soft skills like communication and adaptability continue to be essential—and are irreplaceable by AI.

From an HR perspective, AI offers strong potential for improving training efficiency and personalization. However, outcomes vary. While some organizations report faster onboarding and reduced costs, others warn that poor implementation can harm engagement and learning quality.

In short, AI is not replacing human potential but augmenting it. For graduates, entry-level paths remain vital. For employers, the challenge is to modernize—not eliminate—how they nurture early talent. This white paper explores these insights in detail and outlines what the future of entry-level work may really look like in an AI-enabled world. 

1. The State of AI Adoption

AI has become a well-integrated part of the modern workplace, though its role is still evolving and has generated a mix of enthusiasm and anxiety over the last couple of years. News headlines often suggest a future where AI replaces junior roles entirely, leading to fears that early-career opportunities may soon disappear. However, insights from our recent survey of 2,000 professionals—including a dedicated group of HR leaders—paint a far more balanced picture.

Where AI Is Being Used

The most common use cases for AI are centered around improving efficiency and reducing manual effort:

• Employee training (69.2%)
• Onboarding (63.5%)
• Data analysis and reporting (52%)
• Content creation and communication support (34%)

These findings indicate that AI is being used more to enhance existing processes than to replace them altogether.

Among HR professionals specifically, the use of AI is concentrated around core employee lifecycle functions:

• Training (47.2%)
• Onboarding (43.5%)
• Adaptive learning systems that adjust in real time based on performance were cited by nearly half of HR respondents (49.3%) as a key application
• Personalized learning paths (42%) and virtual coaching tools (34%) are also seeing adoption

How Effective Is AI So Far?

The impact of AI on training is significant, but not universally positive. Most HR professionals report that AI has:

• Reduced training costs (36.7%), though nearly 29% also reported increased costs, likely due to initial investments in tech and implementation
• Improved training effectiveness for over half of respondents (52.8%)
• Accelerated skill development (43.6%)
• Boosted learner engagement (39.1%)

However, around 21% reported a reduction in training effectiveness, citing reasons such as poor content quality, loss of the human touch, or inappropriate use of automation.

Training Costs: A Double-Edged Sword

The impact on training costs is equally nuanced:

• 36.7% of HR professionals report reduced training expenses thanks to AI
• However, 28.6% say costs actually increased—likely due to upfront investments in tools, integration, and content development
• Another 27.2% report no significant change in cost at all

These responses indicate that while AI can create efficiencies, it’s not a guaranteed cost-saver—at least not in the short term.

Widespread Adoption, but Not Daily Use

Despite growing integration, AI is not yet embedded into daily work for most.

• 27% of professionals use AI daily
• 47% use it occasionally
• A small percentage are still unsure how their tools are using AI, reflecting a need for better internal education and adoption frameworks

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AI Governance: A Work in Progress

About half of the surveyed organizations have formal AI policies in place, showing a move toward structured oversight. However, a significant portion still operates in a gray area, using AI informally without clear governance or best practices—highlighting a risk of misapplication and uneven results.

2. Entry-Level Work: Redefined, Not Replaced

AI is undeniably changing how companies operate, especially when it comes to automating repetitive, low-value tasks. But rather than eliminating jobs, it is reshaping them. Most organizations are not doing away with entry-level hiring. Instead, they are evolving how these roles are structured, what skills they require, and how early-career talent is onboarded and developed. It’s redefining responsibilities, raising the bar for skills, and requiring companies to rethink how they attract early talent. Despite widespread concerns about AI replacing entry-level jobs, our findings suggest a more balanced reality. While AI is certainly transforming how early-career roles function, it is augmenting rather than eliminating these positions.

Perceptions of Replacement Are Overstated

When asked to what extent AI has replaced entry-level tasks:

• Only 8.7% of respondents said AI has completely replaced entry-level responsibilities
• A significant 50.9% believe AI has replaced these tasks to some extent
• Another 22.1% say it has done so to a large extent
• Just 14.9% believe AI has had no impact at all

These responses reflect a clear trend: entry-level roles are evolving, not disappearing. Only a small fraction of organizations report full automation of entry-level roles. In most cases, AI is used to free up time, allowing employees—including junior hires—to focus on more strategic, creative, and human-centric tasks.

How Companies Are Adapting

Organizations are not turning away from early-career hiring but instead adjusting their strategies:

• 12.5% are redesigning entry-level roles to include more strategic or creative tasks
• 8.2% are offering more internships or apprenticeships to prepare young talent
• 8.4% are prioritizing digital apprenticeships focused on AI or data training
• 9.9% report hiring fewer entry-level candidates—but this is a minority response

The takeaway: rather than eliminating entry-level opportunities, most companies are evolving them to better align with modern workflows and AI-enhanced environments.

Leapfrogging Is Rare, and Experience Still Reigns

Crucially, the majority of professionals and HR leaders surveyed still believe that experience matters. Entry-level roles continue to serve as an essential gateway for skill development and career growth. The most effective strategies for young professionals to remain competitive remain unchanged: internships, apprenticeships, and early work experiences. Soft skills such as communication, adaptability, and critical thinking are still in high demand—and remain beyond the reach of AI.

Although some headlines suggest that AI will allow graduates to skip over entry-level jobs entirely, the data tells a different story:

• Only 14% of respondents believe recent grads can leapfrog directly into higher-level roles
• 30.8% say that’s not really the case—most still need to gain foundational experience
• 40.4% believe leapfrogging is possible to some extent—but only for grads with very specific skills or industry knowledge

Similarly, among HR professionals:

• 38.1% reported hiring grads directly into higher-level roles, but mostly in specialized areas like AI, data science, or software engineering
• Over 50% of organizations have not changed their experience requirements, showing that traditional paths to career development remain highly relevant

Skills Still Matter—but Experience Matters More

Even as automation changes job requirements, experience remains a key differentiator:

• 54.9% of respondents said internships, apprenticeships, or volunteer work are still the best way to stay competitive
• 44.5% emphasized the continued value of soft skills like adaptability, collaboration, and problem-solving—traits AI cannot replicate
• Technical certifications and digital fluency are gaining importance, but they do not replace real-world experience

replace real-world experience.

While AI is streamlining many low-skill tasks, it has not removed the need for entry-level roles. These positions are being reimagined—not eliminated—paving the way for smarter, more capable, and more human early-career experiences.

3. The HR Perspective: Opportunities and Cautions

HR professionals are increasingly embracing AI—not as a trend, but as a practical tool to improve efficiency, reduce costs, and personalize employee experiences. However, while adoption is growing, so too are the complexities and challenges that come with implementation.

What HR Uses AI For

Among HR professionals surveyed, the most common applications of AI fall into two main areas: employee training and onboarding.

• 69% use AI for training employees
• 63.5% use it to support onboarding new hires

These are not just surface-level use cases. AI is being used to create adaptive learning experiences, with nearly half (49.3%) of HR professionals reporting that AI is now helping tailor training content in real time based on employee performance. Another 42% use AI to create personalized learning paths based on roles or skill levels. Around one-third (34%) also utilize virtual coaching or AI-powered tutoring, indicating that these technologies are starting to find their way into more advanced areas of L&D.

This marks a shift from one-size-fits-all training models to more dynamic, scalable, and learner-focused solutions.

How Effective Is It? Mixed Signals

From the HR perspective, AI presents significant potential for improving the efficiency and personalization of training, but the results are mixed. While some report reduced costs and faster onboarding, others caution against poor implementation, which can undermine learning and reduce engagement.

While many HR professionals report clear benefits, the results show that the impact of AI on training and development is not uniform:

• 52.8% believe AI has improved training effectiveness
• 21.1% report that effectiveness actually declined—often due to poor implementation, low-quality content, or the loss of human interaction
• 27.2% saw no meaningful change at all

This suggests that AI’s value in training hinges on how well it is deployed, not just whether it is used. Simply adding AI to a process isn’t enough; success depends on thoughtful integration, strong content design, and continued human oversight.

Accelerated Ramp-Up and Skills Development

The promise of faster employee ramp-up times does appear to be materializing:

• 79% of HR professionals report that AI has reduced the time it takes to train and onboard new hires, with 34.2%saying the reduction was significant
• 43.6% say AI has sped up skills development
• 39.1% believe it has improved learner engagement and motivation, likely thanks to interactive and personalized formats

These are strong indicators that when used well, AI can positively transform the early stages of the employee experience.

Who’s Most Affected by AI in Training?

Not surprisingly, entry-level and junior employees are the most impacted by AI-driven training changes—cited by 35.5% of HR respondents. These individuals typically require the most onboarding support, making them ideal candidates for adaptive learning and AI-supported training tools.

Senior and executive employees, on the other hand, were less affected (19.68%), likely because their development needs are more bespoke and strategically focused.

Evolving Qualification Priorities

AI is also influencing what qualifications HR teams prioritize when hiring for early-career roles:

• 29.4% say AI has made skills-based qualifications more important
• 30.2% report that technical certifications have gained weight

Interestingly, soft skills and real-world experience remain largely unchanged in importance, with 51.5% saying AI has no effect on how they value experience, and 47.3% saying the same for soft skills.

This underscores a key takeaway: while AI may reshape job descriptions and workflows, the fundamentals of good hiring—real-world readiness and interpersonal capabilities—still matter just as much.

HR professionals are leveraging AI to modernize training and onboarding, reduce time-to-productivity, and personalize development. But the benefits are not guaranteed. Poorly implemented AI can backfire, and significant upfront costs remain a barrier. For AI to deliver on its promise in HR, it must be deployed thoughtfully—with clear goals, quality content, and a continued focus on the human side of work.

Conclusion: Augmentation, Not Elimination

The findings from our survey make one thing clear: AI is transforming the nature of work, but it is not wiping out entry-level opportunities as many headlines suggest. What we’re seeing is not a wave of replacement—but a shift in expectations, responsibilities, and the types of skills that matter.

Across both HR professionals and general respondents, there is broad agreement that AI is automating many routine tasks traditionally assigned to junior employees. However, only a small fraction believe AI has completely replaced entry-level roles. Instead, the data shows that most companies are evolving these roles, using AI to take over the low-value tasks and creating space for employees to focus on higher-order, more strategic work.

This redefinition has real implications for both employers and young professionals.

For companies, it means the approach to early-career hiring must change. It’s no longer enough to recruit for generic administrative roles. Organizations must now design entry-level positions that offer meaningful learning opportunities, strategic exposure, and hands-on experience with digital tools—including AI. Employers who do this well will not only build stronger teams but also stand out in a competitive talent market.

For graduates and job seekers, the message is equally important: entry-level roles are still here—but they’re evolving. Foundational experience is still critical, and the need for internships, apprenticeships, and other early career pathways remains high. Soft skills like adaptability, communication, and critical thinking continue to be in demand—precisely because they are the qualities AI cannot replicate.

At the same time, skills-based hiring is gaining traction. AI may have accelerated this trend, but it hasn’t negated the value of real-world learning. Technical certifications and digital literacy can open doors—but they don’t replace experience.

Even in training and development, AI is more of a co-pilot than a driver. While many HR professionals report improved onboarding and learning outcomes through AI, others caution that poor implementation can backfire, harming engagement and effectiveness. The tools may be smart, but they still rely on human insight, empathy, and thoughtful design to succeed.

Ultimately, AI is a force for augmentation—not elimination. It’s a tool to elevate human capability, not replace it. For entry-level employees, that means a future of work that is more challenging, more dynamic, and potentially more rewarding. But it also means the need for clear pathways, supportive learning environments, and leadership that understands how to unlock human potential through technology.The future of work isn’t less human—it’s differently human. And AI, when used responsibly, can help shape that future for the better.  AI may be changing the landscape, but it hasn’t rewritten the rulebook.