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The Fall 2024 Workforce Index Shows AI Hype Is Cooling

New global survey reveals a disconnect between AI aspirations and adoption rates. Here’s how leaders can keep their company’s AI journey on track.

Del equipo de Slack12 de noviembre de 2024

Quick take: 

Executives are all in on AI, with 99% planning AI investment in the coming year. And yet, for the first time since generative AI’s introduction, adoption rates are plateauing and excitement is cooling among the global workforce. 

Read on to learn the surprising reasons employees are hiding their AI use from their managers, why workers worry that AI tools could lead to a higher workload, and how to harness the know-how of the rising generation to optimize AI’s workplace impact — plus more insights from the Workforce Index, Slack’s survey of 17,000+ desk workers around the world.

Key findings

  • Executives are all in on AI: 99% say they will invest in AI this year and 97% say they feel some level of urgency to incorporate AI into business operations. 
  • And yet, for the first time since generative AI arrived on the scene, sentiment and uptake among desk workers is starting to cool. Over the past three months, AI adoption rates stalled in France and the U.S., while excitement rates around AI dropped 6 percentage points globally. 
  • Nearly half (48%) of all desk workers would be uncomfortable admitting to their manager that they used AI for common workplace tasks. The top reasons for workers’ discomfort are 1) feeling like using AI is cheating 2) fear of being seen as less competent and 3) fear of being seen as lazy 
  • The data shows a gulf between what desk workers wish AI would allow them to focus on and the ultimate effect they predict it will have on their work lives: Employees most want AI to allow them to refocus their time on meaningful activities, but they suspect that AI could lead to more busy work and increased workload. 
  • A persistent lack of training continues to hamper AI uptake; 61% of desk workers have spent less than five hours total learning how to use AI.  
  • The good news is that desk workers are eager to upskill on AI; 76% feel urgency to become an AI expert and the top two reasons most commonly cited are industry trends and personal goals (with management expectations further down the list), showing an intrinsically motivated workforce.
  • And employees and executives agree that up skilling is a top priority: “Learning and skill building” tops the list of activities that executives would like employees to prioritize to improve business performance. It also tops the list of activities that desk workers wish AI would give them more time to focus on.

Executives are all in on AI. AI innovation remains the number one top-of-mind issue for executives — above all external factors, including politics or the economy. Ninety-nine percent of executives say they will invest in AI this year, with 72% prioritizing a “significant” investment and nearly all (97%) saying they feel some level of urgency to incorporate generative AI into business operations. 

And yet, for the first time since the arrival of generative AI, sentiment and uptake among desk workers is starting to cool. 

Between September 2023 and March 2024, AI adoption had steadily increased globally, growing from 20% of the global desk worker population to 32% in March 2024 — or about a third of all desk workers. But over the past three months, AI adoption rates have stalled in some countries; France saw just two percentage point growth, from 31% to 33% of desk workers trying AI, and the U.S. saw just a single percentage point growth, from 32% to 33% of desk workers.

AI uptake growth over time - Workforce Lab - Workforce Index

Excitement around AI is also cooling, dropping six percentage points (47% to 41%) among the overall global population. This trend is being driven by the U.S., where the portion of workers who say they’re excited about AI helping them to complete tasks at work dropped nine percentage points (from 45% to 36%) over the past three months and France where excitement rates dropped 12 percentage points (from 53% to 41%). Excitement also dropped in Japan and the UK. 

“With so many businesses making AI investments right now, these findings are a real wakeup call to leaders,” said Christina Janzer, head of Slack’s Workforce Lab. “AI adoption isn’t just about enterprises, it’s also about employees. With sentiment around AI dropping, businesses need to help employees accelerate their AI journey and address the cultural and organizational blockers standing in their way.”

 

The why: What is causing the AI downshift? 

To some degree this pattern matches the typical maturity curve for new technology. But our data points to more blockers: 

  1. Uncertainty around and discomfort with AI norms 
  2. Perception that AI is not yet living up to the hype
  3. Persistent and significant lack of AI training

AI blocker: Uncertainty and discomfort around AI norms

Previous Workforce Index research has found that many workers are uncertain about what types of AI use are permitted at their company, but new findings reveal that formal permission isn’t the only inhibitor of AI uptake; desk workers are also at odds about when it’s socially and professionally acceptable to use AI at work. 

When presented with a list of 11 common workplace tasks from writing messages to brainstorming new ideas to analyzing data to writing code, nearly half (48%) of all desk workers said they would be uncomfortable admitting to their manager that they used AI for at least one of the above. 

Among those who said they would be uncomfortable to share their AI use with their manager, the top reasons most commonly cited for this were: 

  • Feeling like using AI is cheating (47%) 
  • Fear of being seen as less competent (46%)
  • Fear of being seen as lazy (46%)

Interestingly “AI use is discouraged or not allowed by company policy” was the least commonly cited reason (21%).

Unsurprisingly, those who are comfortable with sharing that they used AI for work tasks are 67% more likely to have used AI for work compared to those who say they would not be comfortable admitting AI use.

“Our research shows that even if AI helped you complete a task more quickly and efficiently, plenty of people wouldn’t want their bosses to know they used it,” said Janzer. “Leaders need to understand that this technology doesn’t just exist in a business context of ‘Can I get the job done as quickly and effectively as possible,’ but in a social context of ‘What will people think if they know I used this tool for help?’”

💡 Take action: guidance for leaders

With the wildly varying perspectives among desk workers about what uses for AI are socially and professionally acceptable, it’s clear that AI enablement can’t be one size fits all. Even within a single team, employees are likely to have mixed feelings around whether or not it’s okay to use AI for a specific task.

Run an AI team-building exercise: Past Workforce Lab research has identified five AI personas that typify commonly held perspectives among the workforce. Similar to personality or strengths tests for team building, conducting an AI personas exercise is a fun way to draw-out varying points of view, clarify guidelines and expectations, identify blockers holding people back from trying AI, and surface creative use cases across roles and functions.

AI in public: Seeing how others are using and benefiting from AI tools helps clarify AI norms. Make your team’s AI use more visible by creating a Slack channel dedicated to sharing and troubleshooting AI use cases and discussing AI news or by starting team meetings with an invitation for people to share their AI learning for the week. Leaders can set the course by regularly sharing milestones in their own AI journeys, modeling that AI experimentation (from the successes to the trial and error) is celebrated and encouraged.

AI blocker: Perception that AI is not yet living up to the hype

Much of the excitement and hype around AI has been centered on the promise that it will help workers accomplish tasks faster and save time. But what should that time be used for? 

Unlike money, time isn’t a fungible resource that can easily be reallocated toward a better purpose; just because you save a few hours doesn’t necessarily and automatically make you more effective in your day. The data reveals a disconnect between what desk workers wish AI would allow them to focus on, what AI is best suited to do, how people are using AI today, and the ultimate effect workers expect AI will have on their work lives. 

Employees most want AI to allow them to refocus their time on activities they find meaningful. They think it’s best at assisting with administrative tasks. And yet they suspect that AI could lead to more busy work and a higher daily workload overall.

When asked “If AI saved you several hours of time a week at work, how would you wish to prioritize that time in an ideal world?” respondents said they’d most want to use the time saved from AI toward non-work activities followed by learning and skill-building. 

But when asked a variation on that question: “If AI saved you several hours of time a week at work, how would you actually prioritize that time?” respondents said they’d spend the time on more administrative tasks, followed by more work on existing core projects. 

And finally, when asked “Which common work tasks is AI best suited to do?,” administration topped the list (87%), followed by assisting with core work projects (80%), and innovative or creative work projects (81%).

“Employees are worried that the time they save with AI will actually increase their workload — with leaders expecting them to do more work, at a faster pace,”  said Janzer. “This presents an opportunity for leaders to redefine what they mean by ‘productivity,’ inspiring employees to improve the quality of their work, not just the quantity.” 

💡 Take action: guidance for leaders

Focus on up-skilling: “Learning and skill building” tops the list of activities that executives want employees to prioritize to improve business performance. Notably, it also tops the list of activities that desk workers wish AI would give them more time to focus on. 

This is a promising area of agreement for leaders to lean-in on. The data shows that desk workers are intrinsically motivated and eager to learn; the majority (76%) feel urgency to become an AI expert and the top two reasons most commonly cited are industry trends and personal goals.

Redefine productivity to represent more than just “more of the same”: Much of the rhetoric around AI has centered on its ability to boost employee productivity, and for good reason; those who are using AI regularly do show higher scores for overall productivity. 

However executives ranked “innovative or creative work projects” as the second area they’d most want desk workers to focus on to improve business performance, while “administrative tasks” fell to the bottom of the list. This presents the opportunity for leaders to redefine what productivity means by clarifying the areas where employees can move the business forward.

AI blocker: Persistent lack of clear company permissions and training

In our last Workforce Index, we saw that those who are trained to use AI are up to 19 times as likely to report that AI is improving their productivity. And yet lack of AI training remains a persistent problem; as of August 2024, just 7% of desk workers consider themselves expert AI users. The majority of desk workers (61%) have spent less than five hours learning how to use AI and 30% of workers say they’ve had no AI training at all, including no self-directed learning or experimentation.

💡 Take action: guidance for leaders

Think “PET”: Permission, Education, Training: Close to half of workers (45%) don’t have explicit permission to use AI. Step one of any AI investment should be to implement the “PET” plan, providing clear permission, education, and training for employees. 

Think top-down, peer-to-peer, and bottom-up: The majority of desk workers (70%) believe that AI training should be a mix of employee- and employer-led, so leaders should make time and space for top-down training opportunities as well as self-guided and peer-to-peer learning, such as inviting employees to share creative AI use cases in weekly team meetings or in dedicated Slack channels. 

AI microlearning: “AI training programs don’t have to be a heavy lift,” said Chrissie Arnold, director of future of work programs at Workforce Lab. “At Slack, we’ve had pretty amazing results from just 10 minutes a day of AI microlearning.” 

Forecasting the AI future: Three predictions for leaders

Prediction: The AI-native generation will be the standard-bearers for AI’s workplace impact

What the data shows: 68% of global desk workers believe that the average college student graduating today has more AI skill than the average employee at their company. And those newest to the workforce agree; desk workers in their first job are twice as likely to think of themselves as an AI expert compared with desk workers with more job experience. Millennials and Gen Z are also most likely to be seeking out self-directed learning opportunities, from online courses to exploring functionality through trial and error to peer-to-peer learning. 

What this means for leaders: “This is a great opportunity for leaders to tap those newest to the workforce to step into peer mentorship,” said Janzer. “Inviting your AI-savvy employees to share their excitement and creative use cases for AI encourages employee connection and gives new recruits a chance to shine.”

Prediction: The AI-native generation is most at risk of AI degrading social connection

What the data shows: 81% of AI users say they turn to AI for advice or assistance on an important project instead of consulting a friend or peer at least occasionally, and 28% say they do so frequently. This trend is being driven by Gen Z and Millennial workers who are most likely to consult AI in place of a colleague with 30% of Gen Z  and 33% of Millennials saying they do this frequently, compared to 23% of Gen X and 13% of Boomers. 

What this means for leaders: “For leaders, the challenge is to leverage AI not just as a tool for efficiency but also as a catalyst for reimagining how humans connect and collaborate to tackle intractable challenges and deliver the best possible experience for customers,” said Mick Costigan, the VP of Salesforce Futures. “As AI and agents scale across workflows and industries, more is at stake for each human-human interaction, and leaders will need to approach human connection with greater intentionality.”

Prediction: Job-seekers will increasingly prefer AI-savvy employers

What the data shows: 3 out of 4 desk workers say that a prospective employer’s ability to provide and enable workers on AI tools is a factor in their job search, with nearly two in five saying they’d prefer working for companies that provide AI tools and enable their use. This trend is likely to accelerate, as people in their first job are 1.8 times more likely to say AI enablement is a “very important factor” in their job search.

What this means for leaders: “This finding shows that companies that drag their feet on AI enablement are compromising their ability to attract and retain top talent,” said Nathalie Scardino, president and chief people officer at Salesforce. “As AI and agents become an integral part of the workplace, employees will increasingly gravitate toward organizations that prioritize innovation and provide the tools necessary to stay competitive. At Salesforce, we have thousands of employees using Agentforce agents everyday to do their jobs — and they’ve told us that experience is important to them.”

For a deeper dive into this research and to join the conversation, register for the Workforce Lab webinar. 

Methodology

The survey included 17,372 workers in Australia, Brazil, Canada, France, Germany, India, Italy, Japan, the Netherlands, Singapore, Spain, Sweden, Switzerland, the U.K., and the U.S. and was fielded between August 2 and August 30, 2024.

The survey was administered by Qualtrics and did not target Slack or Salesforce employees or customers. Respondents were all desk workers, defined as employed full-time (30 or more hours per week) and either having one of the roles listed below or saying they “work with data, analyze information or think creatively”: executive management (e.g. president/partner, CEO, CFO, C-suite), senior management (e.g. executive VP, senior VP), middle management (e.g. department/group manager, VP), junior management (e.g. manager, team leader), senior staff (i.e. non-management), skilled office worker (e.g. analyst, graphic designer).

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