Feature
Money talks. And the purchasing decisions of corporate customers are making it clear what capabilities they value in generative AI.
AI vendors have money on the mind as well, as they work out what pricing model works best for their new offerings. In the past, companies like Apple, Google and Samsung used new and improved features to encourage consumers to upgrade their devices and accept higher price points. Today though, they treat AI as a product in and of itself. Microsoft, for instance, tacks on an extra $30 a month to use Copilot in Microsoft 365.
But as The Wall Street Journal wrote in a June article, “those new data centers and microchips aren’t going to pay for themselves.”
The genAI market is young and companies remain hesitant to invest, so vendors have to feel their way along to determine what to build — and at what cost to the consumer.
HR’s AI ROI
HR may have a particular ROI problem when it comes to AI — and tech in general. Many organizations don’t wring the full value from their HR tech budgets. Gartner reports that barely a quarter of HR professionals believe their company maximizes their HR tech stack’s capabilities, and only 35% think their current approach to using technology can be linked to business results.
“While HR leaders believe that HR technology is important and impactful, they continue to struggle with how to gain the most value,” wrote Mark Whittle, vice president of advisory in Gartner’s HR practice, in the report. “The goal isn’t to maximize technology’s value to HR alone, but to maximize the business value the technology can bring to the entire organization.”
Certainly, this disconnect between capabilities and results may come from asking the wrong questions or setting the wrong goals.
“Strategic business value is generated by bringing humans and technology together, not freeing up employees’ time to do strategic work on their own,” added Piers Hudson, senior director in Gartner’s HR practice.
This implies that vendor messaging about improved efficiency and “freeing up time for strategic tasks” is leading to misdirection.
The solution, Gartner believes, involves focusing on augmentation rather than efficiency. Doing so can increase HR tech’s business value by 54%, Gartner stated.
Related Article: Glitch in the Machine: Why HR Should Tread Carefully Along AI's Path
The Subjective Measure of 'Value'
All of this raises a valid question: how do we define what’s valuable? It’s not clear that customers are ready to do that.
On the one hand, enterprises like the idea of providing improved knowledge tools, but concerns about privacy, employee pushback and the fear of AI “hallucinations” are holding them back. As a result, businesses have been slow to buy group subscriptions to AI tools from companies like OpenAI, Alphabet and Microsoft.
Interest is also waning. In its State of Generative AI in 2024 report, Lucidworks, a San Francisco search developer, found that 63% of global companies plan to increase AI spending in the year ahead, down from 2023’s frenzied 93%.
In addition, the value of AI capabilities is still muddy. Apple can’t provide a clear idea of how much an improved Siri will be worth, for example. The value of increased productivity becomes tough to estimate when factors like reskilling or offboarding costs are factored in.
All of this poses a conundrum for vendors, who feel pressure to dive in deep even while customers remain in the shallow end of the pool.
Related Article: Navigating the App Jungle: Streamlining HR in a World of Endless Solutions
Where HR Should Be Focusing Now
The stakes are high for everyone. When workforce technology is clunky, HR pays the price, which complicates relations with those building the products.
According to the Gartner data, 69% of employees said they faced at least one obstacle when using HR technology in the past 12 months. Plus, nearly half of the HR staff surveyed reported that the use of HR tech has damaged HR’s reputation across the organization.
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It may be that the HR tech world is getting ahead of itself when it comes to AI. Rather than envision wide-ranging transformational changes at this juncture, making AI work in more modest circumstances could provide more credibility. So would demonstrating how GenAI’s capabilities align with HR’s basics.
Specifically, HR would probably be better served by understanding exactly how GenAI and technology in general can support new approaches to work — and spending less time thinking about technology’s impact on current jobs.
