The Workforce is “Quiet Cracking”: Can L&D Rescue Your AI Transformation Crisis
Beyond burnout and quiet quitting, a more insidious phenomenon has emerged – "Quiet Cracking." No wonder 2025 continues to be a crisis of burnout for HR.
Recent research from TalentLMS reveals this persistent feeling of workplace unhappiness now affects more than half of employees (54%), with one in five experiencing it frequently or constantly.
Unlike its predecessors, quiet cracking represents a deeper form of disengagement that often remains invisible until it's too late.
But what's driving this wave of silent distress?
Whilst political and global uncertainty are undoubtedly having an effect, at the heart of this crisis lies a troubling catalyst: the widespread but often poorly executed implementation of AI in the workplace, leaving employees feeling increasingly uncertain, undervalued, and unprepared for change.
Quiet Cracking: The Human Cost of AI Transformation
While quiet quitting might be a healthy boundary-setting response to overwork, quiet cracking represents a more troubling deterioration of the employee-employer relationship. It signals that employees are not just limiting their effort, but experiencing a fundamental disconnection from their work.
In the context of AI transformation, this distinction is particularly important. Many employees are not deliberately withdrawing their effort (quiet quitting) but rather experiencing genuine confusion, fear, and disconnection (quiet cracking) as they try to navigate a rapidly changing workplace.
And it's not surprising.
The statistics (TalentLMS, 2025) tell a revealing story:
- While 82% of employees feel secure in their current roles, this confidence plummets to 62% when asked about their future with their company
- 29% report unmanageable workloads during this transition period
- 15% don't clearly understand their role expectations in an AI-transformed workplace
Annual research released by Orgvue reveals that 39% of business leaders made employees redundant as a result of deploying AI. Of those, 55% admit they made wrong decisions about those redundancies.
This reveals a fundamental problem: organizations are implementing the technology without fully understanding how AI should integrate with their human workforce.
AI Implementation Gone Wrong
The Orgvue research reveals that businesses have moved from "optimism to pragmatism" in their AI adoption approaches as they come to terms with the consequences of quick, poorly planned decisions.
The hasty rush to implement AI without proper workforce planning has created a climate of uncertainty and distrust.
Consider these telling statistics:
- 35% of organizations acknowledge a lack of expertise as one of the biggest barriers to successful AI deployment
- 25% don't know which roles can benefit most from AI
- 30% don't know which roles are most at risk from automation
With this level of uncertainty at the leadership level, is it any wonder that employees are experiencing quiet cracking?
When leaders themselves don't understand how AI will reshape roles and responsibilities, employees are left to navigate this ambiguity on their own.
Learning & Development: The Missing Link
Employees who haven’t received training in the last year are 140% more likely to feel job insecure.
But it's not fair to place the responsibility on HR's shoulders. If quiet cracking is a systemic challenge and symptom, the answer also lies in its systemic and cross-functional approach.
This isn't just about HR developing new learning programs, so much as it's about how organizations update their processes, implement company-wide change initiatives, and of course, create a culture of adoption and innovation.
Building a Resilient Workforce Through Learning
To address quiet cracking as a response to AI transformation, organizations need a comprehensive learning and development strategy that focuses on both the technical and human aspects of change.
Here are three key approaches:
1. Implement AI literacy programs for all employees
It will have been difficult not to notice Meta's recent rollout of its AI Assistant into WhatsApp. It's going to get harder and harder to ignore AI, yet introducing AI literacy as part of onboarding will go a long way toward developing employees' job readiness and organizational readiness, too.
Rather than keeping AI implementation knowledge siloed within IT or leadership, democratize understanding through comprehensive training that helps every employee understand:
- How AI works in your specific organization
- Which tasks will be augmented versus automated
- How roles will evolve rather than disappear
- Where human skills remain essential and valuable
Why it works?
Transparency directly addresses the uncertainty and additionally, training will most likely bolster employee confidence.
2. Develop skills mapping and personal development plans
40% of tech workers expect skills to be outdated within three years, urging companies to prioritize smarter learning strategies for 2025.
Creating development plans and focusing on skills-based training is likely to bolster confidence and focus on developing practical skills, enhancing expertise and driving a continuous cycle of skill development.
Why it works?
Personalized development plans give employees a sense of agency and future orientation that counteracts the helplessness associated with quiet cracking.
3. Train managers to navigate change
Navigating change and the ability to manage change is fast becoming one of the most cited soft skills. Managers should know that leading through change isn’t about having all the answers, it’s about guiding your team through uncertainty with confidence.
This points to a critical training need for managers, who must learn:
- Techniques for supporting employees through technological change
- How to communicate effectively about AI's role in the organization
- Skills for facilitating team collaboration in hybrid human-AI environments
Why it works?
Leaders inspire confidence and bolster morale in the face of change.
The Business Case for Investment in Learning
Beyond addressing the human cost of quiet cracking, there's a compelling business case for investing in learning as the primary approach to AI transformation.
The economic impact of disengagement is staggering.
Disengaged employees are a problem that costs the economy $8.8 trillion a year (Gallup). And that was 2023!
And disengaged employees inevitably lead to:
- Decreased productivity as employees psychologically withdraw
- Increased turnover as disengaged employees seek opportunities elsewhere
- Resistance to adopting new processes (AI-enhanced or otherwise)
- Loss of institutional knowledge as experienced employees leave
Investing in learning and development creates a different trajectory as it:
- Builds employee confidence
- Enhances organizational preparedness to meet future demands
- Creates the skills necessary for effective human-AI collaboration
- Transforms uncertainty about the future into excitement about possibilities
Learning as The Essential Resilience Tool
Quiet cracking isn't just coincidentally occurring alongside AI transformation—it's a direct human response to how organizations are managing this technological shift.
The evidence clearly shows that employees who receive adequate training, support, and clarity about their evolving roles are significantly less likely to experience disengagement.
As mentioned in AI In HR: The 2025 Landscape;
- Automation doesn’t replace jobs—it redefines them (and the skills needed)
- Upskilling is the new normal
- Humans matter
“Leaders cannot be distracted by the potential of AI and divest in human inputs. The future requires a strategic partnership of both.”
Learning and development isn't just one solution among many—it's the essential bridge between technological change and human adaptation.
By investing in comprehensive training that addresses both technical skills and emotional resilience, organizations can transform AI implementation from a trigger for quiet cracking into an opportunity for workforce growth and engagement.
Organizations that recognize this connection and prioritize learning as an integral part of their AI strategy won't just avoid the pitfalls of quiet cracking—they'll create workplaces where humans and AI truly enhance each other's capabilities, driving both wellbeing and business success.
What's Next?
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