Why professionals still don’t trust AI and AI agents despite growing adoption – YouGov study

Source Cryptopolitan

Pegasystems Inc. (Pega) recently published the results of a new research exploring how workers feel about agentic AI. The joint research published with YouGov surveyed over  2,100 US and UK professional who use digital devices for their jobs. 

The research defined “AI agents” as software programs or tools powered by artificial intelligence that can assist with various tasks, such as generating content, analyzing data, automating repetitive processes, or providing recommendations. 

According to the research, even though a majority of workers (57%) have shown interest in using AI agents at work, others remain cautious, expressing significant concerns about reliability and quality. 

Why some professionals still don’t trust AI agents 

According to some reports, professionals have historically expressed distrust of AI, citing concerns about reliability and explainability. Agentic AI systems often make decisions that can be difficult to interpret, leading to potential errors and misunderstandings. 

When asked about why they don’t use AI agents, 33% of professionals expressed worry about the quality of work AI produces. 32% were concerned about a lack of human intuition and emotional intelligence, and 30% just didn’t trust the accuracy of AI-generated responses. 

Some are also worried about AI agents obscuring the decision-making process, making it challenging for professionals to understand and trust the outcomes. Such a lack of transparency can hinder troubleshooting and halt progress in innovation. 

Another reason why some pros are not totally into agentic AI is because they can limit your ability to grow and learn. According to them, while AI agents perform tasks given to them effectively, they typically do so without explanation.

This means professionals may miss out on learning opportunities that come from being involved in the creative process. The end result is a superficial understanding of tasks and a reduced ability to improve or troubleshoot over time. 

The reason many are called professionals is because they have attained mastery over key steps of processes required to succeed in their crafts. As a result, many pros would prefer to maintain control and understanding, but that is harder to do when autonomous AI agents are involved. 

Hence, AI agents raise the question of whether professionals will sacrifice what makes them special for automation that does not completely guarantee outcomes and undermines explainability with time. 

How professionals embracing AI Agents are doing compared to their skeptical colleagues 

In recent times, more organizations have adopted agentic AI, a nod toward its ability to improve operations and productivity. Pegasytems’s research found that about 58% of workers who took the survey admitted to already using AI agents today. 

These early adopters have recorded seeing benefits. About 41% of responders chose the automation of tedious tasks as the primary benefit, followed by reduced time spent searching for job-related information (36%) and quick meeting summarization (34%). 

Despite the current limitations and concerns, 46% of those who took the survey believe AI will have a positive impact on their jobs over the next five years, and only 13% anticipated negative effects. The remaining respondents were neutral toward the topic or unsure about AI’s impact.

When it comes to improving these agents, those who already use them have identified the areas they think need more attention. 

42% pointed to enhanced accuracy and reliability as the top priority for improving agentic AI tools. Next on the list was better training on how to use these tools (39%), then increased transparency in AI decision-making processes (33%). 

The research showed that professionals’ perceptions of AI agents and AI have improved across the board. However, resolving the issues they identified could improve the acceptance rate. 

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Disclaimer: For information purposes only. Past performance is not indicative of future results.
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