Organizations are currently investing heavily in in Artificial Intelligence (AI) to boost efficiency, sharpen decision‑making, and stay competitive. But technology alone doesn’t deliver results. However, AI only creates value when employees understand it, trust it, and know how to use it in their daily work.
Technology adoption without capability alignment
Many organizations adopt AI systems with the expectation that technological capability will automatically translate into improved outcomes. However, implementation without sufficient employee readiness often leads to underutilization or misuse of these systems. AI adoption is not only a technological decision but also an organizational and behavioral one (Lindner et al. 2025; Menzies et al. 2024).
From a decision-making perspective, this reflects a misalignment between technological investment and human capability. When employees lack the necessary understanding to interpret AI outputs, the potential value of the technology remains unrealized. This creates a gap between expected and actual performance, where investments fail to deliver meaningful returns (Li et al. 2022).
The role of digital literacy in AI-supported environments
Digital literacy plays a central role in enabling effective use of AI systems. It determines how well employees can understand, evaluate, and apply AI-generated insights in their work processes. Without sufficient digital literacy, users may rely blindly on outputs or fail to recognize their limitations (Rai 2020).
Within the theoretical framework, this can be linked to decision-making under uncertainty. When individuals lack the knowledge required to critically assess information, they tend to rely on simplified interpretations. This increases the risk of incorrect conclusions and reinforces dependency on automated outputs (Johanson and Vahlne 2009; Berente et al. 2021).
From a practical perspective, digital literacy is not limited to technical skills. It also includes the ability to question outputs, recognize bias, and understand the conditions under which AI-generated results are valid. These capabilities are essential for transforming technological potential into actual performance (Luo & Zahra 2023).
Digital literacy and attitudes toward AI as moderating factors
Employees with higher digital literacy are better able to critically evaluate AI outputs, reducing the likelihood of blind reliance or misinterpretation. Positive attitudes can support effective use, while distrust or resistance can limit adoption and reduce impact (Saketi 2026).
From a theoretical perspective, these factors act as moderating variables between AI-supported inputs and decision quality. Even when advanced systems are available, their contribution depends on how users interact with them. Misalignment between capability, literacy, and attitude can lead to inconsistent or suboptimal outcomes (Menzies et al. 2024; Lindner et al. 2025).
This highlights that successful AI adoption requires more than technological investment. It requires alignment between system capability, user competence, and perception of the technology (Saketi 2026).
Towards a more integrated AI implementation strategy
Improving the outcomes of AI investments requires a more integrated approach that combines technology, capability development, and organizational alignment. Training employees to improve digital literacy is a critical component of this process. It enables them to interpret outputs correctly and use AI systems more effectively (Li et al. 2022). At the same time, organizations must address employee attitudes toward AI. Building trust, clarifying limitations, and encouraging critical engagement are essential for effective adoption. Without this, even well-designed systems may fail to deliver expected benefits.
Artificial intelligence enhances decision-making when combined with human judgment and contextual understanding (Rai 2020; Luo & Zahra 2023). Organizations that invest in both technology and people are more likely to achieve meaningful value from AI adoption (Berente et al. 2021; Saketi 2026).
AI investments do not fail because of technology alone. They fail when organizations overlook the human factors that determine how technology is used. Digital literacy and employee attitudes are not secondary considerations they are central to achieving effective and sustainable outcomes.
Authors
Hassan Saketi is an international business student at LAB University of Applied Sciences. He focuses on artificial intelligence and international business.
Reko Juntto is a Senior Lecturer of Digital business at LAB University of Applied Sciences.
References
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Li, L., Lin, J., Ouyang, Y. & Luo, X. 2022. Evaluating the impact of big data analytics usage on the decision-making quality of organizations. Technological Forecasting & Social Change, 175, 121355. Cited 15 Feb 2026. Available at https://doi.org/10.1016/j.techfore.2021.121355
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Saketi, H. 2026. Human VS AI-Supported Decision-Making in International Market Entry. Thesis. LAB University of Applied Sciences. Bachelor of Business Administration, International Business. Cited 19 Mar 2026. Available at https://urn.fi/URN:NBN:fi:amk-202604156508
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