Half of Employees Still Hiding AI from Their Bosses (And It's Their Bosses Faults)
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Today on the AI Daily Brief, why workers are still hiding their AI usage from their bosses, and why it's their boss's fault. Before then in the headlines, NVIDIA CEO Jensen Huang says that China is not behind in AI. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Thanks to today's sponsors, KPMG and Superintelligent. And to get an ad-free version, go to patreon.com slash ai daily brief.

Quick note before we dive in, we unfortunately had a very last minute dropout from a sponsor for May and we're running a business here. We want that full slate of ads. So if you have ever thought about advertising on this show before and would like to get yourself some slots at a discount, I'm trying to fill that inventory and quickly shoot me an email, nlw at breakdown.network and put sponsor in the subject line. Thanks. And let's get to the show.

Welcome back to the AI Daily Brief Headlines Edition, all the daily AI news you need in around five minutes. We kick off today with the latest scuttlebutt around the China-US AI battle. Specifically, we have some very interesting comments from NVIDIA CEO Jensen Huang, who when pointedly asked how far behind China was, basically said they're not. How far behind do you think China is?

China is not behind. China is right behind us. I mean, we're very, very close. But remember, this is a long term. This is an infinite race in the world of life. You know, there's no two minute end of the quarter. There's no such thing. And so we're going to compete for a long time. And just remember that this is this is a country with great will and they have great technical capabilities. 50 percent of the world's researchers are Chinese. And so this is an industry that we will have to compete.

So these are pretty stark comments. I mean, usually I just read them, but the sincerity with which he says they're not behind, I think is part of what has really captured people's attention.

Now, of course, there is context for these comments. I've shared before the back and forth between NVIDIA and the Trump administration on chip export restrictions. Basically, the restriction of the H20 chips seems like it came as a surprise to NVIDIA. Now, for his part, Jensen is definitely playing the U.S. political game. The company recently announced that it plans to build $500 billion in AI infrastructure in the U.S. over the next five years, a move which President Trump has loudly applauded. At

At the same time, NVIDIA is racing to minimize losses from these new rules by getting chips out before the rules go into effect. Moving over to other tech giants, we are in earnings season right now, which is always a good chance to get a pulse of what's going on. Microsoft's earnings yesterday were solid. Microsoft grew revenue at a 13% pace with a 33% annualized gain for their Azure Cloud division. CFO Amy Hood guided that this stellar cloud growth would continue forecasting a 35% pace for the current quarter.

At the same time, she warned that the company expects to run into capacity constraints by June, stating, Here she's referring, by the way, to Microsoft's fiscal year, which is currently in Q4 and ends in the summer.

Now, all of this comes after Microsoft reportedly canceling several data center leases and slowing down major AI infrastructure projects. The company insists that these two points are not necessarily related, with Hood reiterating the commitment to invest $80 billion into data centers this year. Based on the reporting, there wasn't a clear sense of the scale of the cancellations, but they did seem to be somewhere between marginal and moderate rather than a gutting of AI spending.

Hood reminded investors that it takes time to pour concrete and rack hardware, adding, These are very long lead time decisions from land to build out. It can be lead times of five to seven years, two to three years. So we're constantly in a balancing position as we watch demand curves. The way that the earnings whispers account summed it up was this. The death of our AI CapEx has been greatly exaggerated. The reality is we are just balancing things like we always do. You're just paying more attention to it now.

Meanwhile, Meta is telling a different story, committing and doubling down once again on the AI infrastructure build-out, whatever the costs. They're in a pretty good position to do that because Wednesday's earnings saw steady revenue growth and a slight beat on estimates. On the earnings call, CEO Mark Zuckerberg said that he isn't concerned about an economic downturn harming the advertising business, stating, "...we're well-positioned to navigate the macroeconomic uncertainty."

At the same time, the tariffs have led the company to rethink how they approach AI expenditure for the year. Meta had already committed to spend between $60 and $65 billion on AI infrastructure, which was a big jump from last year's spending, and the company is now guiding that the final figure will be in the range of $64 to $72 billion due to the trade war. CFO Susan Lee said,

She added that Meta is working to mitigate that impact by, quote, Meta is now set to spend more on infrastructure than they have in the past two years combined.

And while previous boosts to Meta's spending have caused Wall Street to squirm, this round of earnings seemed to be well-received. The stock was up 6% in overnight trading following the report. Andrew Rocco, a stock strategist at Zacks Investment Research, said that increased AI spending is now seen as a positive indicator.

Zuckerberg also presented the releases from this week's LamaCon in a positive light, noting that WhatsApp is the primary way that people around the globe access Meta's AI assistant, but that that platform isn't the dominant messaging app domestically, saying, So I think the Meta AI app as a standalone is going to be particularly important in the United States to establishing leadership.

Lastly today, rounding out this big tech catch-up theme, Google is close to striking a deal to bring the Gemini assistance to iPhones, at least according to CEO Sundar Pichai, who is on the stand at the Google antitrust trial. Pichai said that he expects to close the Apple deal by the middle of the year and integrate Gemini into the iPhone ecosystem before year's end.

Presumably, the integration will allow Siri to call on Gemini the same way it currently punts complex queries and writing tasks to chat GPT. Apple SVP Craig Federighi had hinted at this integration last year when Apple Intelligence was first unveiled, stating, We want to enable users ultimately to choose models they want, maybe Google Gemini in the future.

The discussion came out of cross-examination of the CEO. Pichai acknowledged negotiations with Apple CEO Tim Cook, saying, He was trying to understand our plans for how we're evolving AI technologies, our roadmap, and as part of that, we talked about the Gemini app distribution as well. Is this yet one more piece of evidence that Apple is giving up the ghost and saying they can't develop their own AI? We'll just have to wait and see.

For now, that's going to do it for today's AI Daily Brief Headlines Edition. Next up, the main episode. Today's episode is brought to you by KPMG. In today's fiercely competitive market, unlocking AI's potential could help give you a competitive edge, foster growth, and drive new value. But here's the key. You don't need an AI strategy. You need to embed AI into your overall business strategy to truly power it up.

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Welcome back to the AI Daily Brief. Today's episode is honestly almost a throwback. You might remember that about a year ago, when we were looking at Microsoft's Work Trends Index for 2024, one of the big themes was this secret cyborg idea. I think at the time, the stat was that 75% of knowledge workers were now using AI. And again, this was in Q1 of 2024. And of those, 78% of them were bringing their own tools to work and not telling their colleagues and bosses about it.

Microsoft called this BYOAI. This set a tone for a lot of discussions throughout the year. Remember, at that time, we were firmly in the paradigm of AI as a productivity enhancement tool for individual employees. Times have shifted somewhat, and a lot more of the attention now is on the design and integration of agentic systems and their implications for how things are built in general. But of course, even with all these big structural changes, employees haven't gone away.

In fact, if anything, I think that the shift to agentic makes the need to upskill employees even more pertinent because it looks nothing like the upskilling that's happening now. But I'm getting a little bit ahead of myself. Let's talk about the studies that prompted this episode, and then we'll come back and do a little bit more of this analysis.

So again, to reiterate, this secret cyborg trend is a thing that's been happening for a while. This was reaffirmed by a Slack study back in August that found that 48% of workers were uncomfortable telling their managers that they use AI for common tasks for fear basically that they would be seen as cheating or appear lazy or incompetent. New research from KPMG in collaboration with the University of Melbourne finds that this is still sort of the case. The report was called Trust Attitudes in the Use of Artificial Intelligence.

It surveyed 48,000 workers across 47 countries between November and January. You guys know I'm a stickler for how recent my surveys are. And while I wish these numbers were taken last week, especially because I think Q1 has seen a dramatic shift in agent adoption, we're still talking about pretty recent data. The study found that 57% of workers are still hiding their use of AI at work, and 50% are presenting AI-generated content as their own. And yet,

Yet, if the secrecy is still alarming and still suggests that there is still a big trust gap and suggests that the biggest trust gap in AI might not be trusting AI, but the trust between employees and leaders, overall, the study is yet another indicator of just how much AI has infiltrated the workplace.

67% of respondents said that they intentionally use AI at work, and 69% of employees said that their organization uses AI. And there are some positive impacts. 54% are reporting increased efficiency, quality of work, and innovation. 43% are reporting increased revenue-generating activity.

which I think is a really important statistic as it's a rubber hitting the road sort of number. Although a meaningful percentage, 28%, have also indicated that they have an increased workload stress and pressure because of AI. So if broadly speaking, there's a lot of positive growth in AI and a lot of reporting of starting to see positive effects from AI, it'll be interesting to note that I think that the big story from this report and really the subtext of all of this is that organizations are woefully behind AI.

when it comes to actually supporting the integration of these tools in a coherent and comprehensive way.

This report found that only 60% of organizations have an AI strategy in place, only 54% have responsible use policies, and the lack of policy has real impact. So whereas people last year that were reporting that they were keeping their AI usage secret, I think were doing so in large part because of their perception of societal attitudes towards AI usage, I think now a lot of it has to do with the incredible disparity between the tools available to employees in their work life and the tools available to them as general consumers.

70% of workers in this survey globally said that they're using publicly available free tools. These tools, of course, are not enterprise grade. They don't have specific privacy or security guarantees, but they are a hell of a lot better than any of the absolute dog poop that makes up what enterprises are spending boatloads on for their employees.

What's more, I believe that the disparity between the enterprise offerings and the consumer offerings is doing nothing but increasing. Now, on top of this, organizations aren't even really supporting people with the tools they are provisioning. Just 42% of those surveyed said that they felt that they had the skills and knowledge to use AI appropriately. Only 28% have formal or informal training in AI. Only 52% overall feel they can use AI tools effectively.

KPMG writes,

and uploading sensitive company information such as financial, sales, or customer information to public AI tools. Three in five report that they've seen or heard of other employees using AI tools in inappropriate ways. Two in three report relying on AI output without evaluating the information it provides. And over half say they've made mistakes in their work due to AI. What makes these risks even more challenging to manage is that over half of employees avoid revealing when they use AI to complete their work.

and present AI-generated content as their own. These findings highlight a lack of transparency and accountability in the way AI tools are being used by employees at work. Now, I'm not sure that it was KPMG's goal to make it seem like the onus is entirely on employees. But let me be clear. This is not an employee problem. This is a leadership problem. A failure to provide the right tools, a failure to provide the right policies, a failure to provide the right guidelines, a failure to provide the right training, a failure to provide the right guardrails.

And most of all, a failure to communicate what your expectations are as an organization, how you see the future shaking out, and where employees fit in that vision, these are all leadership deficits. And yes, it is employee usage where the problems of these leadership deficits come home to roost, but make no mistake, they are leadership deficits. It is not an employee's job who is just trying to do their job better to get your AI policies in place. In

and to run around half the organization trying to figure out if this incredibly powerful tool that could make their work much better is or isn't appropriate based on what you figured out. That is a job for leadership, for executives to communicate, and to actually make the decisions that need to get made. Now look, enterprise change is extremely difficult. These organizations are huge, Borg-like.

And I absolutely believe that they are working as hard as they ever have to adapt to a new technology paradigm as quickly as they can. But the simple fact of the matter is it's not fast enough. And if you are an enterprise leader who is listening to this right now, the numbers here are clear and in black and white. It is almost certainly the case that you have to move faster.

and the stakes are doing nothing but increasing. One of my big gripes right now with the state of upskilling and education in AI is that it's still operating in the paradigm of nine to 12 months ago, that AI upskilling was all about how employees get more productive by using co-pilots. The reality is we've already shifted out of that era. We are now firmly entering the era where the key skills are how to build, provision, and manage agent teams.

how to think differently about delegation, about the design of work on a fundamental level, how to understand new capabilities that were not possible before that digital employees can unlock. No one is provisioning that sort of training right now, and it's going to bite people very, very quickly.

When I take a step back, I spend all day every day with companies who are thinking about AI transformation. I am incredibly bullish about where this all resolves. I think that individuals and teams are going to be empowered to build things in ways that were completely unthinkable, not just years ago, but even months ago. I think that the potential that work in five years is better than it's ever been is extremely high. But I also think that a lot of how this shakes out is going to come down to how we behave now. This is a

This big study suggests that there is a lot more work to be done. For now, though, that is going to do it for today's AI Daily Brief. Appreciate you listening, as always. And until next time, peace.