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AI is evolving rapidly, and companies are racing to design and integrate new AI-driven capabilities into their software. The new tools promise to optimize productivity, streamline operations and boost innovation. But is it all going too fast?
SAP Introduces AI Copilot Joule
Just a couple of weeks ago, SAP joined a growing list of companies that now integrate generative AI into their software. The company has embedded its new generative AI copilot, Joule, into its enterprise cloud suite, as a way to provide contextual insights from SAP solutions and third-party data sources.
The company said in a statement that Joule is expected to not only help SAP customers make faster and more informed decisions, but that it will also transform the user experience and the way business runs.
SAP sees AI as a central part of its marketing strategy for SuccessFactors, steering its messaging and product development down complementary paths. In fact, a notable chunk of its recent SuccessConnect conference focused on how the company has wrapped AI into the entire SuccessFactors HXM suite.
“Joule draws on SAP’s unique position at the nexus of business and technology and builds on our relevant, reliable, responsible approach to Business AI,” SAP CEO Christian Klein said in the press release announcement. “Joule will know what you mean, not just what you say.”
But Joule represents just one component of SAP’s vision of AI for HR.
Last week, the company also announced an AI-based talent intelligence hub that offers employers greater visibility into skills coverage and gaps. Embedded in SuccessFactors HXM, the hub creates a skills portfolio for each employee based on skills and attributes data gleaned from performance feedback and dynamic teams. With it, managers can view, add and update skills and other attributes for their direct reports, while employees can build and store data about themselves.
A Modern Gold Rush
Klein’s promise doesn’t seem particularly outlandish among all of the coming product features being hyped by solutions providers throughout HR technology.
Many businesses have been eager to find ways to tap into the power of generative AI, according to the New York Times. As a result, solutions providers are racing to create and sell products that incorporate generative AI to their enterprise customers.
Just recently, Workday also announced the release of a series of AI and ML capabilities designed to help businesses drive productivity, streamline business processes, empower their people and make better decisions.
At about the same time, employment firm Oyster announced an AI-powered chatbot, this one designed to answer questions about global hiring and remote-work regulations, while Skillsoft launched a beta AI conversation simulator that is expected to provide employees with “a safe space” to practice important business conversations with an AI trainer.
All of this taking place in a matter of weeks.
Then, in the last year, the Times wrote, “Amazon, Box and Cisco have unveiled plans for generative AI-powered products that produce code, analyze documents and summarize meetings. Salesforce also recently rolled out generative AI products used in sales, marketing and its Slack messaging service, while Oracle announced a new AI feature for human resources teams.”
In addition, there has been a notable surge in global interest for HR tech. Recent insights from Startups.co.uk found that the Google Trends data shows worldwide searches for the term “AI in HR” reached the peak interest score of 100 toward the end of July 2023.
Related Article: Artificial Intelligence Is Evolving Like Us, Just Faster
AI Overload
Alongside the rush of emerging capabilities and the spotlights trained AI’s possibilities, hints of reality are poking their heads above the surface. After months of hype surrounding the potential of generative AI, investors and startups are ratcheting back their enthusiasm and trying to take a more measured approach to the market.
A number of startups built on a foundation of AI are confronting declining market interest and facing the need for layoffs, The Wall Street Journal reported. Adding to the pressure: Investors aren’t convinced that new companies will survive, particularly as brand-names like Microsoft and Google push into the space.
The flood of products unveiled since last year is bewildering many technology customers. On the one hand, they want time to understand how AI capabilities can fit their needs. On the other, they’re pressuring vendors to keep up with developments.
“Some of our customers, all they want to hear is that we’re thinking about AI,” said Ellen Loeshelle, director of product management, intelligence platform at Qualtrics. “Like I could say that in one sentence and get off the phone and they’d be happy.”
No wonder analysts are taking a cautious approach to new AI products. It’s become difficult to understand the differences — and benefits — of all these new tools coming out.
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For example, Joshua Greenbaum, principal at Enterprise Applications Consulting in Berkeley, Calif., said SAP’s Joule may be more about SAP positioning itself as an industry leader than offering a true AI solution.
“This technology is not available now, and the LLMs that it will be built on are still in development,” he said in an interview with TechTarget. “The fact that SAP has 20,000 customers who have agreed to give some version of their enterprise data to build the models is muddied by the fact that we don’t know who these companies are, what their business processes are or what corners of the global economy they represent.”
Related Article: It Could Be 5 Years Before We See Productivity Gains From Generative AI
A VC Wonderland?
“There is a ton of VC propaganda” out there about investments in AI, said John Luttig, an investor at Founders Fund, which has invested in ChatGPT developer OpenAI, in an interview with the Journal. “It’s an unequivocal optimism without asking any of the hard questions on product, user interface, distribution or end markets.”
Consider chatbots for example. The advent of generative AI raised the market’s stakes, as developers hyped improved accuracy and more natural interactions between machines and users. ChatGPT’s breakneck growth led investors to believe customers would adopt such products quickly. That, in turn, encouraged them to pour money into fledgling businesses that had few customers and less revenue.
Now, the bloom is off the rose.
In its article, the Journal reported that visitors to ChatGPT’s website dropped by 10% in both June and July. Midjourney, whose technology creates images from user-created descriptions, reported a drop in visits in May, June and July. And over the past six months, Synthesia, which uses text to create videos, has seen flat or declining website user growth.
That may be because the rush of interest and new products capitalizing on generative AI isn’t without risks.
For one thing, the use of AI today lacks rules or regulations, although organizations and regulatory bodies are trying to catch up. For another, the technology faces challenges such as embedded bias and privacy concerns, which are not always recognized and reported.
A recent Gartner survey also found that over half the respondents’ companies have no internal policy on generative AI, the Times said.
In light of these challenges and potential pitfalls, there have been calls for a more intentional approach to utilizing AI. A Greenhouse survey of over 2,700 candidates and over 100 HR leaders found a striking 84% of HR professionals believe there should be more education and training about AI tools in the workplace.
“HR teams that buy into AI technology should not introduce it to the workplace without having a secure support infrastructure in place” said Startup.co.uk’s Lead Writer Helena Young. “If businesses are to protect sensitive employee information from unwelcome eyes, it’s paramount to train HR staff to use new technologies and systems before bad practice becomes normalized.”
The question now is, where does that leave all these new shiny AI toys?
