Employees are eager to use AI. A recent Workday survey shows that 73 percent of workers “hope their company explores more AI implementation.”
“At Insight, the groundswell of interest around generative AI has been high,” said Carm Taglienti, chief data officer and distinguished engineer at Insight Enterprises. “People have been genuinely curious about it, which we have wanted to encourage and incentivize.”
In response to employee enthusiasm, the Arizona-based information technology company developed a private, secure generative pre-trained transformer (GPT) solution and made the tech available to its workforce. Fostering companywide participation and friendly internal competition has been the key to success, according to Taglienti.
“Our teammates have felt empowered to test, learn and explore the tool, uncovering use cases that we have been able to replicate internally and bring to market for clients,” he said.
But not all organizations have the resources to launch a private or “in-house” tool. With the right strategy and vetting, third-party tools can be just as effective in satisfying employees’ curiosity about AI.
ChatGPT and Beyond
Using ChatGPT has cut the time needed to write a job description from an hour to, in some cases, roughly 10 minutes, according to Priti Patel, chief people officer at G2, a business software and services company headquartered in Chicago.
Her team is actively using ChatGPT to conduct performance reviews, write job descriptions, and glean themes and insights from quarterly employee survey comments. But while ChatGPT is the most widely recognized AI tool, it’s far from the only one available.
“There are other helpful AI time-saving tools and features, including Zoom’s AI assistant for transcribing interviews and intake calls our team has with hiring managers,” Patel said.
Jessica Blodgett, SHRM-CP, director of people, culture and community at the New York-based CMMB, an international nongovernmental organization, relies on Google’s Bard because it provides different drafts to review and tweak. She also uses LinkedIn’s AI tool to help build a pipeline of passive candidates for open roles. Blodgett sees her HR peers using more AI tools in recruitment, general HR administration, and learning and development.
“This includes tools such as AI coaches to help develop employees,” she said. “In recruitment, you will see HR leaning into automated resume screening, scheduling, predictive interview outcomes, skill matching, or even LinkedIn that uses AI to identify and reach out to passive candidates.”
Tips for Assessing and Integrating AI Tools
Listening to and considering employees’ requests about adopting AI tools is crucial. Employees who feel their input is valued are more engaged and may have outside experience with specific tools that can benefit the organization. However, adopting the use of an AI tool should be strategic.
“At the end of the day, regardless of how they’re doing it, leaders should not invest in AI just for the sake of it,” Taglienti said. “There has to be a clear ‘why’ and business imperative that’s driving any of these decisions.”
Here are four things to consider when an employee expresses interest in implementing an AI tool.
1. Understand the risks. Blodgett said it’s essential to know the risks associated with any AI tool up for consideration. That includes knowing how transparent the vendor is about updating and training its models. In graduate school, Blodgett and her capstone partner researched the risk mitigation capabilities of over 140 AI tools. They found that the average AI tool scored 1.5 on a scale of 7.
Blodgett and her research partner generated a list of questions to help understand the risks, and they encouraged HR leaders to consider at least these two:
- Does the AI tool have the ability to expose current biases?
- Can a human understand the tool without additional training?
2. Establish guidelines. It’s crucial to have an organizational AI policy before moving forward with vetting or implementing an AI tool. Governance is central to making any effort successful, Taglienti said.
3. Evaluate and adapt. Eser Rizaoglu, a senior analyst in Gartner’s HR technology strategy and management team based in London, said the organization recommends:
- Evaluating generative AI use cases and broader AI use cases, with business value and feasibility as drivers for prioritization.
- Working with HR technology leaders on guidance for when to buy or build generative AI capabilities, based on each individual use case.
- Monitoring the market as new use cases and lessons emerge.
4. Understand where it saves time. “It’s important to be aware of where your team is spending their time to determine where AI can be most effective,” Patel said. “However, don’t stop at your department. Marketing, sales or product [development] might be using AI in ways that HR can adopt, too—such as automated slide content creation for internal meetings or summarizing employee survey data.”