The employee experience (EX) in 2026 is defined by rapid technological advancements, evolving workforce dynamics, and persistent organizational change. The Qualtrics 2026 Employee Experience Trends Report indicates that 72% of employees report experiencing significant change, signaling a critical juncture for HR and CX leaders. The report, drawing insights from employees across 24 countries and multiple industries, highlights the urgent need to prepare workforces for an uncertain future, emphasizing connection, purpose, and support as foundational elements for resilience.
Rethinking Engagement: Beyond Top-Line Metrics
Traditional measures of employee engagement, inclusion, well-being, and expectations exceeded have declined to historical baselines in 2026 after increases in the prior year. This signals a need for leaders to look beyond surface-level metrics and focus on the underlying work experiences that shape employee attitudes and behaviors. The core drivers of engagement remain consistent: alignment with deep-rooted organizational values, clear opportunities for growth, respectful treatment, and a belief in a positive future. Employees fundamentally seek to feel connected to their organization and its mission, both in the present and for what lies ahead .
Disruptive technology, specifically AI, is perceived by employees as an energizing force that unlocks new capabilities and relieves pressure. In contrast, disruptive organizational changes such as widespread reorganizations, layoffs, leadership churn, or significant budget cuts tend to exhaust employees. While some change and pressure can be beneficial – employees experiencing a moderate amount of change reported higher engagement and productivity – the source of that change is critical. Modernizing changes in technology, workflows, and strategic direction drive engagement. Conversely, changes perceived as disruptive lead to disengagement and impact productivity. Feeling supported to adapt to organizational change is the single biggest driver of positive employee expectations.
A particular cohort requiring focused attention is long-tenured employees, those with five or more years of service. These individuals, often repositories of critical institutional knowledge and interpersonal connections, express greater concern about their future amid rapid change compared to newer hires. Organizations must recognize their need for explicit support and reassurance to retain their value.
What to do:
- Re-anchor to core values: Clearly articulate and live organizational values. For a financial services institution, this might mean reinforcing customer-first principles in all policy changes, demonstrating how new processes improve client trust.
- Invest in targeted growth paths: Implement personalized development plans, especially for long-tenured employees, to address concerns about stagnation. This could involve cross-functional training for B2B SaaS engineers to work on new product lines or upskilling retail managers in advanced data analytics.
- Differentiate change management strategies: Distinguish between technological advancements and structural reorganizations. For AI adoption, focus on enablement and skill-building. For structural changes, prioritize transparent communication, clear rationale, and support resources (e.g., career counseling, new role opportunities).
What to avoid:
- Generic engagement initiatives: Avoid broad programs that do not address the specific drivers of connection and value.
- Neglecting institutional knowledge: Failing to engage long-tenured employees in change processes risks losing critical organizational memory and expertise.
- Indiscriminate cost-cutting: Implementing sweeping layoffs or leadership changes without clear communication and support will erode trust and engagement across the workforce.
Navigating the Dual-Edged Sword of AI Adoption
The integration of AI into daily work is accelerating, with 52% of employees reporting frequent (daily or weekly) AI use in 2026, a 7-point increase from the prior year . Employees cite numerous benefits, including faster task completion, improved work quality, increased productivity, and the ability to perform tasks previously beyond their capabilities. AI is viewed as an enabler of organizational change, with those experiencing more change reporting more positive attitudes toward AI’s supportive role.
However, this rapid adoption presents a significant governance challenge: “shadow AI.” A growing percentage of the global workforce is sourcing their own AI tools to augment their work, particularly under increased productivity pressure. This introduces substantial risks, including data security breaches, compliance violations, intellectual property exposure, and inconsistent customer experiences. For example, a customer service representative in a telecom company might use a publicly available large language model (LLM) to draft responses, inadvertently exposing sensitive customer data or company policies.
Organizations have a critical role in demonstrating AI’s value, providing approved tools for specific purposes, and establishing clear guidelines for responsible use. Leaders must regularly measure AI usage and sentiment to ensure that sanctioned tools meet employee expectations and mitigate unapproved tool usage.
What to do:
- Develop an enterprise AI governance framework: Establish clear policies for AI tool usage, data handling, and ethical considerations. This must include explicit consent protocols for customer data used with AI, and specific guardrails for sensitive information.
- Provide approved AI tools and training: Implement a curated suite of AI-powered tools integrated with enterprise systems (e.g., CRM for personalized customer outreach, billing systems for query automation) and provide comprehensive training on their effective and secure use. For a retail company, this might mean a sanctioned AI assistant for inventory management, with clear data input and output guidelines.
- Monitor and measure AI adoption and sentiment: Use EX platforms to survey employees on their comfort with AI, the value it provides, and adherence to policies. Track AI feature adoption rates within approved applications to understand efficacy. Establish a cross-functional AI governance committee with representation from HR, IT, Legal, and relevant business units.
- Implement a phased rollout with red-teaming: Introduce AI capabilities in controlled environments with rigorous testing for bias, accuracy, and unintended consequences before wider deployment. For a healthcare provider, this could involve a RAG (Retrieval Augmented Generation) system for patient information retrieval, with strict data access controls.
What to avoid:
- Ignoring shadow AI: A passive approach to unsanctioned AI tools will inevitably lead to security vulnerabilities and compliance risks.
- “Wild West” AI adoption: Allowing employees to use any AI tool without guidance or oversight can result in inconsistent data quality, intellectual property leakage, and reputational damage.
- Over-reliance on containment: Focusing solely on blocking shadow AI without addressing the underlying employee needs for productivity enhancement will be ineffective.
Rebuilding Trust: Prioritizing Frontline, Part-Time, and New Hire Experiences
Cost-cutting measures, particularly those impacting employment models and onboarding, are creating a significant divide within organizations, leading to disengaged employees and, consequently, unsatisfied customers. The report reveals a concerning trend: part-time and frontline workers, who often directly interact with customers, exhibit substantially lower job attitudes than their full-time and management counterparts. These cohorts report significant concerns about receiving adequate feedback (63% for frontline, 46% for part-time) and the ability to challenge traditional ways of working (50% for frontline, 46% for part-time).
The onboarding experience, consistently identified as underwhelming, has further deteriorated. New hires with less than one year of tenure are significantly less engaged, included, and committed. The “new hire honeymoon period” has not only disappeared but has become “downright bitter” in larger organizations. This lack of investment in critical employee segments has direct business consequences. For example, a B2B SaaS company relying on under-supported new sales development representatives will see lower conversion rates and pipeline generation. Customer experience issues, such as communication problems and service delivery failures, are often traced back to poorly trained and ill-equipped frontline staff.
The link between engaged employees and satisfied customers is well-established. Organizations must view investment in the experience of part-time, frontline, and new hires as a direct investment in customer loyalty and brand reputation. Employee listening is a powerful tool to address these gaps; 42% of employees want their companies to listen more frequently, and 68% enjoy giving feedback. Critically, while senior leaders report positive changes based on feedback (85%), only 48% of frontline workers agree. This widening gap in perceived action is often a symptom of poor communication rather than a lack of actual initiatives.
What to do:
- Revolutionize onboarding programs: Design onboarding for new hires to explicitly foster connection, provide clear career pathways, and embed cultural understanding. Include structured mentorship, regular check-ins (e.g., 30-60-90 day feedback loops), and early exposure to senior leadership. For a large e-commerce retailer, this means robust training for seasonal hires on product knowledge and customer interaction protocols, ensuring a consistent customer experience.
- Empower frontline and part-time workers: Implement formal mechanisms for frontline employees to provide feedback, challenge processes, and contribute to solutions. This could involve regular team huddles, dedicated feedback channels in ticketing systems (e.g., a “process improvement” flag in a CRM), and empowering them with decision-making authority within defined thresholds (e.g., credits up to $25; 7-day window for returns).
- Strengthen manager capabilities: Train managers to provide constructive, performance-improving feedback and to actively listen to their teams. Establish clear SLAs for managers to respond to employee concerns or feedback.
- Close the feedback-to-action loop: Implement robust employee listening platforms (e.g., pulse surveys, focus groups) and, crucially, communicate transparently about how feedback is being used and the actions being taken. For a large telecom, if customer service agents suggest improvements to a common billing issue, leadership must communicate the implemented changes and their impact back to the agents.
What to avoid:
- Transactional onboarding: Treating new hires as a cost center rather than an investment, leading to high turnover and poor initial performance.
- Ignoring frontline insights: Overlooking direct feedback from employees who interact with customers daily means missing critical opportunities for service improvement.
- Listening without acting or communicating: Gathering feedback without demonstrating visible action or communicating outcomes will breed cynicism and disengagement.
Summary
The 2026 employee experience landscape demands proactive, strategic intervention from senior marketing and CX leaders. Declining engagement metrics, the dual challenge and opportunity of AI, and the critical need to support frontline and new hires underscore the urgency. Organizations that foster genuine connection, provide clear direction, and actively listen and respond to their employees—especially during times of accelerated change—will build resilient workforces capable of navigating future disruptions and delivering superior customer experiences. The imperative is clear: invest in the human element, govern technology responsibly, and connect employees to purpose, thereby securing organizational success in a dynamic future.
