Harnessing AI to Elevate the Employee Experience: Insights from a TalTech Master’s Thesis
At Moticheck, we’re passionate about shaping the future of work by helping organizations listen to, understand, and act on employee feedback. That’s why we’re excited to share a compelling perspective from Heleriin Veeber, a TalTech graduate whose recent master’s thesis explores how artificial intelligence can be leveraged to support a more personalized and data-driven employee experience.
In her in-depth research, Heleriin examines the role of AI-powered platforms, like Moticheck, in enhancing employee engagement, trust, and retention through meaningful feedback and actionable insights. Drawing on interviews with HR professionals across Estonia, the study highlights both the opportunities and challenges of integrating AI into people operations.
Whether you’re an HR leader, team manager, or just curious about the evolving intersection of technology and employee experience, this article offers valuable takeaways for navigating the future of work.
Possibilities for Applying Artificial Intelligence in Supporting Employee Experience
At this year’s Opinion Festival, someone remarked that Estonia’s digital tiger has drowned. Every now and then, media comparisons reveal that we’ve dropped to the middle range among EU countries in digital technology adoption.
A few unicorn startups no longer maintain the reputation we had achieved by the early 2010s. We need a broader application of artificial intelligence (AI) in the daily operations of organizations. AI, seen as a key resource in business models, enables organizations to become data-driven, cultivate a digital culture, and gain competitive advantages. In HR management, AI is increasingly used in talent management, performance management, recruitment, employee development and engagement, and HR analytics.
The collaboration between AI and people is seen as a way to reduce time spent on repetitive tasks and to focus more on building trust-based relationships between employees and leaders, helping to better understand their needs and wishes.
Components of Employee Experience and HR Analytics
Employee experience, though still under-researched, has gained increasing attention over the past decade. It is closely tied to employees’ expectations, needs, and desires, which in turn relate to an organization’s strategic goals and leadership. HR research has focused on employees’ psycho-cognitive feelings, identifying elements such as happiness at work, meaningful tasks, team trust, recognition, engagement, development, supportive leadership, and work environment.
Monitoring employee experience involves evaluating perceptions of company culture, leadership, and the overall work environment. Decisions related to employees should be data-based. HR analytics begins with goal setting, identifying key metrics, collecting data, developing indicators, analyzing the information, and finally using it in decision-making.
Often, HR analytics aims to identify labor risks, measure performance and engagement, and develop career paths. From the perspective of employee experience, HR analytics helps understand relationships with the organization, cultural fit, job suitability, and identify opportunities for improving satisfaction and productivity.
Employee needs and expectations vary across different career stages. To meet evolving expectations, employee-centric HR management should be implemented, relying on timely, task-based data collection and analysis. This aligns organizational goals with employee skills, abilities, and interests, thereby boosting motivation.
Personalized HR Management with AI Support
Improving employee experience hinges on creating personalized experiences. Personalized HR can guide career development, skill acquisition, flexible work arrangements, and customized benefits, integrating these with recruitment, development, talent management, and compensation.
Leaders’ attitudes toward employees are increasingly important, as employees trust their leader, receive enough feedback, recognition, and support. To offer this, leaders need information, which modern technology can provide. Platforms based on AI can help identify issues before they become critical, enabling timely intervention.
AI-driven platforms allow real-time survey results, helping leaders respond swiftly. These tools offer organizations insights into behavioral patterns, faster responses to employee needs, and a more personalized employee experience.
Incorporating AI in managing employee experience aids in understanding past events, anticipating workforce issues, and improving future decisions and leadership quality. Investing in personalization can enhance employer branding, financial results, reduce turnover, and increase customer satisfaction.
Using Moticheck to Understand Employee Experience
In spring 2024, the author conducted a qualitative study to explore how Estonian organizations use AI to support positive employee experience and to map user experiences of AI-based platforms (mainly Moticheck).
Two groups were surveyed: one with 9 organizations using AI-based platforms for employee experience (mostly Moticheck), and a second group (n=8) considering or undecided on adoption. Semi-structured interviews revealed shared interest in positive employee experience and data collection on loyalty, engagement, attrition risk, Net Promoter Score, etc.
Some organizations still view personalized approaches as more suited to small businesses. Both groups understood employee experience similarly, but differed in how they used feedback data.
With Moticheck, summaries, team discussions, and action plans often fell to team leaders. Non-users relied more on HR managers for surveys and the dissemination of results.
Most organizations focused on descriptive analytics, reflecting past data rather than predicting trends. Analytics was mainly linked to salary, training, and turnover metrics. While data-driven decision-making was valued, some still relied on intuition in people management.
Both groups emphasized that gathering feedback without follow-up actions is pointless. Resource limitations were a barrier to implementing changes based on feedback.
Interestingly, Moticheck non-users emphasized data and analytics in decision-making more than users, who valued human-centered and intuitive approaches. The study highlighted the risk of not using data in decision-making and change processes, as noted in scientific literature.
Despite regular feedback collection (at least via 1:1 meetings), collaboration between team leaders and HR departments was limited. In the era of hybrid and remote work, relying solely on observation is no longer sufficient. Organizations need clarity in roles for analyzing and acting on feedback. Some HR teams lacked visibility into how feedback was used, signaling room for improvement.
Users of the Aidan chatbot noted it was especially useful for new managers. Experienced leaders felt the bot recommended actions they would have taken anyway.
Interviews suggested Moticheck enhances feedback collection and data analysis. However, to improve results, leaders should be trained in data-based decision-making and recognize the value of platform-derived insights.
Organizations should also standardize usage practices, ensuring insights reach HR and all leadership levels, not just team leads. A notable strength of AI platforms is how they foster a sense of inclusion: employees feel noticed, heard, and valued.
The risk lies in inaction. If feedback isn’t followed by meaningful change, trust erodes. Moticheck accelerates data collection and processing, and while not a panacea, it has significant potential as user skills mature.
Heleriin Veeber, TalTech Master’s Student in Human Resource Management
Originally published in personaliuudised.ee, October 2024
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