Generative AI Wave Raises Uncertainty About the Future of IT Help Desk Roles

The rapid development of generative AI has sparked widespread discussion: as technology becomes increasingly proficient at routine tasks, what role should humans play, or even whether human involvement is still needed. This issue is particularly prominent in entry-level positions in IT service desks.

Most analysts and technology leaders believe that generative AI will inevitably lead to economicjob disruption. However, when directly asked whether technology will replace workers, most people hesitate on this issue—some also say it is possible, but at this stage it is not yet recommended.

"It depends on the situation, but if a company has a well-established knowledge base and is well-trained, generative AI can indeed largely replace level-one service desk specialists—which may be somewhat unsettling for some people," said Mark Tauschek, Vice President of Infrastructure and Operations Research at Info-Tech Research Group.

Level-one specialists are typically the "front line" of the IT department, responsible for communicating with users and performing basic troubleshooting. This role is also an entry point for aspiring technologists. According to Glassdoor data analysis as of June, the average annual salary for level-one help desk employees in the United States is approximately $48,000.

Although it is an entry-level position, level-one service desk employees have a significant impact on how other departments in the company perceive the IT department as a whole. Their efficiency in solving problems and the way they treat end users are thefoundation of employee experience。

"If we are not leading in this area, it would be very foolish."

—Jeremy Rafuse, Vice President of Digital Workplace at GoTo

However, experts are thinking about what role these specialists will play in the technology department in the future, although many analysts believe that concerns about imminent large-scale unemployment are exaggerated.

According to a survey of 405 U.S. corporate directors and above conducted by The Harris Poll in June on behalf of Insight Enterprises, more than a quarter of professionals said thatworkforce attritionis one of their concerns about the implementation of generative AI.

Jeremy Rafuse, Vice President of Digital Workplace at software development company GoTo, said that within the company, there are indeed concerns about job disruption among IT employees as the team attempts to use generative AI to automate some tasks.

"When you talk about automating certain workloads immediately, it is hard not to have such concerns," said Rafuse, who leads GoTo's IT department. "We are trying to promote this as an opportunity to learn new things, which may not only enhance your skills, allowing you to do different work, but will also create new positions that do not currently exist."

GoTo, the parent company of LastPass, has automated routine tasks in the service desk for years. Rafuse said that recently, the IT team has spent time learning about generative AI and identifying low-risk use cases.

"We don't want to just hide under the blanket," Rafuse said. "But the team is aware of this and is quite optimistic, seeing it as an opportunity to learn new things."

In the service desk ecosystem, companies hope to use generative AI to analyze large amounts of data, identify trends related to satisfaction ratings, and locate customer pain points.

"If we are not leading in this area, it would be very foolish," Rafuse said, a view that resonates with most technology executives.

According to a survey of 900 respondents conducted by IDC in July, sponsored by Teradata, nearly 95% of technology executives said theyfeel pressureto adopt generative AI within the next six months to a year. More than half said they are under "high or significant" pressure.

"Can" does not mean "should"

Despite concerns about generative AI replacing workers, popular model manufacturers have countered the claim that LLM and generative AI capabilities should—or can—replace employees.

"Humans should always be involved in AI systems," Sandy Banerjee, Head of GTM at Anthropic, said in an email. "Even if AI systems are answering questions or classifying tickets, there should be a quality assurance process where humans track the system and evaluate its output."

After all, AI is not without flaws. In research published by Anthropic, the company found that Claude models still make mistakes and fill knowledge gaps with fabricated content, emphasizing that models should not be used in high-risk situations or where incorrect answers could cause harm.

Researchers fromStanford University and the University of California, Berkeleyfound that OpenAI's models do not necessarily improve over time. In some cases, performance and accuracy significantly declined, indicating the need for continuous monitoring.

Nevertheless, models from generative AI startup Anthropic are available to enterprises through off-the-shelf methods and third-party services like Slack. Asgenerative AI modelproviders continue to release updates in beta and treat tools as "work in progress," they are alsotargeting enterprise applications。

When OpenAI first launched ChatGPT plugins in March, it compared the code interpreter plugin to "a very enthusiastic junior programmer working at the speed of your fingertips," but the tool can still generate incorrect information or "produce harmful instructions or biased content," as noted on the ChatGPT web page.

Despite vendor warnings, the decision to replace workers with generative AI depends on cost and how much the organization values specific positions.The National Eating Disorders Associationmade headlines for deciding to close its human-staffed national hotline and instead use a chatbot named Tessa. After users reported experiences where Tessa recommended weight loss and dieting restrictions, the nonprofit removed the tool in June.

"If people don't like it, they will avoid it."

—Chris Matchett, Senior Director Analyst at Gartner

At GoTo, the team sets expectations through meetings and discussions, clarifying what generative AI technology can and cannot do. Rafuse emphasized that the technology should be used as a tool, but cannot be fully relied upon because it may make mistakes.

"You know, sometimes you only have one chance, and if you tell someone incorrect information, they won't come back to you," Rafuse said. "First impressions last forever."

Misinformation and bias are not the only risks. Before and during deployment, Melanie Siao-Si, Vice President of International Care and Service at GoDaddy, said the team ensures communication of usage guidelines to prevent employees from exposing proprietary information.

The U.S. Federal Trade Commissionis currently investigating OpenAIto determine whether it has engaged in unfair or deceptive data security practices.

"Especially in care organizations, we are navigating uncharted territory, so we are experimenting," Siao-Si told CIO Dive. "Obvious challenges include data security and privacy, as well as potential threat actors using the same technology to target our customer care organization."

Current state

Eight months after the launch of ChatGPT, most technology leaders describe awareness of generative AI technology as being between the "peak of inflated expectations" and the "trough of disillusionment" in the Gartner hype cycle.

The hype cycleincludes five key phases: innovation trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity. On Wednesday, Gartner placed generative AI at thepeak of inflated expectations。

on its 2023 Hype Cycle for Emerging Technologies. "Many technologies do follow this cycle, and I don't think generative AI will be an exception," said Justin Falciola, Senior Vice President and Chief Technology and Insights Officer at Papa Johns. "The only question is that no one knows exactly which stage we are in."

The task for technology leaders is to navigate through the hype and find value. At GoDaddy, Siao-Si is leading AI experiments in the customer care team, and the company aims to improve customer experience by providing multiple ways to get in touch.

According to Siao-Si, on product pages, the team manages a prompt library to help customers build their businesses in different ways. AI-driven bots also assist customers in refining their needs before receiving guidance.

Enterprise software provider Atlassian announced in April that it updated the capabilities of its generative AI tool in Jira Service Management to support response tone adjustment, as part of itsAtlassian Intelligence layerseries of updates.

In a GIF product demonstration, a human agent asked Atlassian Intelligence to adjust the response to be more empathetic, changing "Your new laptop will arrive next Tuesday" into a five-sentence reply. Tone options also included reassuring, casual, friendly, and professional.

"The reminder here is that the user is always in control," Sherif Mansour, Head of AI Product at Atlassian, told CIO Dive in an April demonstration. "They can cancel and not accept suggestions, or they can accept, edit, and modify."

As enterprises prepare systems for generative AI implementation, leaders need to addressknowledge gaps across the organizationand differences in user preferences. If companies fail to provide a seamless transition from chatbots to human points of contact, it may also haveunintended impacts on customer experience。

"If people don't like it, they will avoid it," said Chris Matchett, Senior Director Analyst at Gartner. "That's why we recommend not making it a mandatory gatekeeper or greeter before talking to a human."

Matchett said that generative AI-driven self-service channels should be implemented as an option for end users. "Let people choose it when they want, rather than forcing it on them."