{"id":197,"date":"2025-11-04T11:17:52","date_gmt":"2025-11-04T09:17:52","guid":{"rendered":"https:\/\/sites.uwasa.fi\/silenskyte\/?p=197"},"modified":"2025-11-04T12:06:14","modified_gmt":"2025-11-04T10:06:14","slug":"rethinking-how-we-understand-technology-in-business","status":"publish","type":"post","link":"https:\/\/sites.uwasa.fi\/silenskyte\/2025\/11\/04\/rethinking-how-we-understand-technology-in-business\/","title":{"rendered":"Rethinking How We Understand Technology in Business"},"content":{"rendered":"

Au\u0161rin\u0117 \u0160ilenskyt\u0117, Ph.D.
\n<\/strong>Assistant Professor of International Strategic Management (Tenure track), Strategic Business Development Research Group, School of Management, University of Vaasa, Finland<\/em>
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Conversations in business and management increasingly turn to advanced technologies \u2014 artificial intelligence (AI), blockchain, software-as-a-service (SaaS), and others. These terms have become part of our everyday professional vocabulary. They feature in conference panels, classroom discussions, and corporate strategies.<\/p>\n

Yet, as these topics become more common, a challenge emerges: the more we talk about them, the easier it becomes to stay at the surface level.<\/strong> There is a growing risk that we, as management professionals, scholars and educators, become comfortable<\/em> using the language of technology without truly understanding the technologies themselves.<\/p>\n

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Talking About Technology Is Not the Same as Understanding It<\/strong><\/h3>\n

The popularity of advanced technologies has made it tempting to assume familiarity. But AI, SaaS, or blockchain are not monolithic or self-explanatory. Behind each lies a complex set of algorithms, design decisions, and technical limitations that shape what these tools actually can \u2014 and cannot \u2014 do[i]<\/a>.<\/p>\n

When business professionals or researchers discuss technology only in broad or abstract terms, they risk misunderstanding its real capabilities and impact. This is why collaboration between management experts and engineers or technology developers is not optional \u2014 it is essential<\/strong>. Those who design and build these systems can help us see what happens beneath the interface. They can clarify how a feature works, what assumptions it relies on, and where its boundaries lie[ii]<\/a>.<\/p>\n

Without such collaboration, we risk forming expectations that no technology can realistically meet and adopt the technologies for business practice with erroneous assumptions, failing later in the implementation process.<\/p>\n

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Technology Adoption as a Socio-Technical Process<\/strong><\/h3>\n

Implementing a new technology in an organization is never just a technical decision \u2014 it is a socio-technical process[iii]<\/a><\/strong>. This means that the success or failure of adoption depends not only on how the technology is built, but also on how people understand and use it.<\/p>\n

It is therefore vital to consider both perspectives. On the technical side, we need to understand how a particular system was designed, what data it uses, and what decisions are automated or supported. On the social side, we must look at how users perceive these technologies \u2014 whether they find them trustworthy, usable, and relevant for their work.<\/p>\n

A mismatch between design and perception can lead to frustration or even rejection of technology<\/strong>. For instance, a management tool driven by AI might be designed to support decision-making<\/em>, but if employees see it as a threat to their autonomy, the technology will not achieve its purpose. SaaS tools for strategic management<\/em> may be misunderstood or adapted incorrectly since their functionality is likely to be discovered only over time and in a non-linear manner, often directed by managerial interests and cognitive frames[iv]<\/a>.<\/p>\n

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The Gap Between Hype and Reality<\/strong><\/h3>\n

Another challenge arises from the way emerging technologies are often presented. The discourse around AI, blockchain, and other \u201cdisruptive\u201d tools is filled with future-oriented promises<\/strong> \u2014 efficiency, transparency, or even revolutionizing entire industries. While such visions can be inspiring, they can also create a gap between imagined<\/em> and actual<\/em> capabilities.<\/p>\n

In management practice, research and education, it is important to recognize this gap. What a technology might do someday<\/em> is not the same as what it can do today<\/em>.<\/strong> When management discussions focus primarily on future potential, they may overlook the practical realities of implementation \u2014 the technological limitations, costs, and human factors that shape real-world outcomes.<\/p>\n

Understanding where a technology truly stands on its development path helps us make better, more responsible decisions about its use.<\/p>\n

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From Buzzwords to Meaningful Insight<\/strong><\/h3>\n

To move beyond buzzwords, cultivating genuine, cross-disciplinary understanding is vital. This does not mean that every management practitioner or scholar must become a programmer. Rather, it means fostering curiosity and humility<\/strong>: asking engineers to explain how a system works, exploring what drives a model\u2019s accuracy, and acknowledging that technological knowledge evolves quickly.<\/p>\n

Engaging with technology developers and data scientists helps ensure that our discussions in business and management are grounded in reality, not speculation. It allows us to connect technological design with organizational practice \u2014 and ultimately, to grow managers who can make informed, ethical, and sustainable decisions in a digital world.<\/p>\n

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Some practical steps instead of closing thoughts<\/strong><\/h3>\n

The integration of advanced technologies into business life is not slowing down. To understand the potential of advanced technologies deeply and realistically, here is what we can do:<\/p>\n