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By: Daniel W. Rasmus for Serious Insights
The 2024 Work Trend Index Annual Report from Microsoft and LinkedIn delivers some worrisome insights about the future of work. Most notably, it shines a bright light on the power of automation over common sense. For those of us who have worked in learning organizations, there is no more powerful outcome than an intelligent workforce engaged in actively improving processes, practices, and, most importantly, itself.
Self-taught individuals are bringing AI to work on devices and through browsers with little guidance, and most organizations have few plans for training. The overt focus on productivity in the Microsoft Work Trend Index does not provide the elevated perspective that generative AI deserves—the perspective required to recognize its transformative potential. The weak recommendations prove self-serving to technology interests rather than informative of broader opportunities for reinvention that could mitigate some of the failures inherent in e-mail and online meetings.
This post attempts to examine the report’s shortcomings, offer alternative perspectives on the data, and provide alternative recommendations aimed at engaging workers in co-creating their future.
I remember years ago sitting in a meeting while a young engineer was admonished for sending an email to a client via her personal email account. We were told that the attachment limits on the corporate email system made it impossible to send a large file via email. This was before the invention of filesharing services like OneDrive or Dropbox. Tools like FTP were cumbersome and locked down in an aerospace environment.
What wasn’t locked down were floppy disks. The young engineer copied the file to a floppy, took it home, and met her commitment to the customer by sending the company proprietary information from her personal email which had a larger attachment limit. She brought her own communication tool to work.
The Microsoft and LinkedIn 2024 Work Trend Index Annual Report states that 78% of people apply consumer or personally subscribed AI tools to work. That number says that people want to do work, and they want to do it well—and they see AI as a means to that end. The young engineer in the story above wasn’t trying to steal information or expose company secrets to the Dark Web; she was trying to meet a customer commitment for which she felt personally accountable.
People want to deliver value. They will find a way despite policy, even at the risk of their livelihoods. Why? Because the trust between customer and employee is often higher than the trust between employee and employer. Integrity often arrives from the bottom up. If AI can help do the right thing, it will be used even when it presents a different class of risk.
Interestingly, as much as AI has become The Skill that differentiates hires, 52% of those in the survey said they hide using AI for their most important work. Roughly the same percentage (53%) report that by using AI, they worry they will look replaceable. That’s a pretty damning indictment of management messaging. With 66% of the survey’s leaders saying they wouldn’t hire someone without AI skills, placing those people in an environment where they feel like those skills should become clandestine isn’t healthy.
Most corporations would do well to see AI as an opportunity not only for reinvention but for self-reflection.
Education is imperative with the increasing pace of change driven by AI developments. LinkedIn has seen a 160% jump in AI training engagement among non-technical professionals. Only 39% of people in the survey received training at work, and only 25% of companies plan to offer training this year.
The lack of investment in skills isn’t new. Training budgets are often the first casualty of budget cuts when companies feel competitive pressure. While it’s easy to claim a budget win, ultimately, underinvestment in learning claims employee futures as its victims.
With such a high expectation for AI skills among new hires and a lack of talent that can meet competency thresholds, the best move for organizations is to upskill employees who already know their jobs. Yes, they may feel threatened by AI, but they also likely see learning AI as a personal advantage. Those worried about being replaced by AI will fare better if they know how to use it effectively more than their peers who don’t take up the challenge to master it.
In the short run, companies will not be able to hire enough people with AI skills. That leaves them two choices. The first is floundering, which is what many are doing now. By underinvesting in education, they force their employees to learn on their own, but that isn’t a sustainable solution. Employees who gain AI skills will not only be more valuable in their jobs, but they will also be more marketable to roles in other companies looking for talent with AI competencies.
And yes, there is always the fear that if the organization trains people they will take their training elsewhere. That thinking reinforces the emotional disconnect that most companies have with their employees. Broken reciprocal social contracts can’t be mended unless organizations start respecting and valuing employees. With labor shortages in an emerging skill area, the ability to not only empower employees with new skills but also create a working environment that encourages their retention will become a differentiator at a time of transition.
The second choice: Become a Learning Organization. As much as AI will rapidly imbue technical solutions with near-human intelligence, it will just as quickly expose human ignorance, perhaps even a lack of compassion…
Read the rest of the article to hear about the Serendipity Economy and the productivity problem people face in the workplace: 2024 Work Trend Index Annual Report: The Worrisome Microsoft and LinkedIn Report
About the author:
Daniel W. Rasmus, the author of Listening to the Future, is a strategist and industry analyst who has helped clients put their future in context. Rasmus uses scenarios to analyze trends in society, technology, economics, the environment, and politics in order to discover implications used to develop and refine products, services, and experiences. He leverages this work and methodology for content development, workshops, and for professional development.
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