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Underused AI technology: How to avoid going down this road?

Today, artificial intelligence (AI) technology is attracting a lot of investments as many enterprises strive to embrace and integrate it into the workflow. This investment boom is driven by the business eagerness to unlock its potential for efficiency, better performance and for staying competitive in the market. Nevertheless, there are particular challenges which enterprises face on their way to leverage AI technologies. 

 

One of the key issues is the misuse of AI because of misalignment with business objectives and growing concerns about employees' readiness for its adoption. The recently released annual report from WalkMe, called "The State of Digital Adoption 2025, Special AI Edition," emphasizes that enterprises have lost over $104 million in 2024 due to underutilized technology and ineffective productivity practices.

 

This situation causes one major concern: what are top AI technologies big companies waste money on and how to avoid it? Let's take a closer look at it.

When AI is an extra feature 

Primarily, such tools as AI-powered analytics, automation instruments and generative AI solutions for content creation are in the list of top technologies which organizations focus on. The main issue is that companies often expect immediate returns from implementing such AI solutions, neglecting to thoroughly plan and allocate time and resources for a more strategic approach.

 

Simply introducing new technology isn't enough — companies still need specialists to deal with it. So, a significant problem in the AI market right now is the shortage of professionals with the relevant expertise. As a result, AI services remain underused because employees find them too complex, lacking the necessary experience to adopt them into daily workflow.

 

Additionally, even though AI-driven decision-making systems can offer valuable insights, they are meaningless if employees do not fully trust its recommendations or do not understand how to interpret data effectively. Similarly, such technologies as AI chatbots and virtual assistants which promise enhanced user interaction can easily fail because they might not align with how employees are used to working. Therefore, it leads to maladaptation.

 

Eventually, unclear guidelines and insufficient training are the main reasons why AI remains underutilized and mistrusted.

How to avoid investing money in underused technologies

As it becomes clear, investing in AI solutions has to be done strategically, since adopting AI technologies just because it's a popular trend isn't the case. Thus, it's imperative to define actual and tangible benefits for the company in the first place. If they can't be clearly outlined — it's better to put off the idea of integrating these technologies.

 

However, if there is a strong belief that these AI technologies will benefit the business, it's essential to look for adoption of those ones that emphasize usability and staff training. Consequently, expecting a radical transformation from integrating AI without a clear strategy for its successful implementation is unrealistic.

 

It’s better to start with a pilot program that would imply gathering feedback from employees to point out key challenges and adjust successful tactics accordingly. Afterwards, investing in AI training programs to bridge the skill gap and make employees feel comfortable with new technologies can become a solution.

 

Ultimately, integration of new AI solutions is a long-term and challenging process. By approaching it thoughtfully, strategically and with clear planning will help the business to reap the benefits in the long run and stay competitive on the AI-driven market.

 

Overall, taking all these factors into account is mandatory in case of proper AI technologies implementation not to allow their underusage. This will help enterprises to unveil their potential, drive growth and allocate financial resources prudently.

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This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.

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