Summary:

Consumer AI is outpacing enterprise AI tools. The bigger the chasm between these experiences gets, the greater the security and engagements risks for employers. On the flipside, accelerating AI adoption in the enterprise can help eliminate boring tasks. By converting bullshit jobs to real ones, we could make a quantum leap in workplace productivity and employee happiness.

When someone talks about the “consumerisation of IT”, you can carbon-date them. Douglas Neal and John Taylor described this phenomenon way back in 2001. So, if you’re a Zoomer and you hear someone use the term, you know how old they are! Jokes aside, “consumerisation of IT” referred to how the tools workers used in their personal lives were similar to the ones they would use at work. Enterprise software had to adopt the same level of sophistication and user experience that people expected from the tools they used outside work.

A big reason for this shift was the commodification of tech, led by innovative companies like Apple, Google, and Facebook. Today, Gmail on your iPhone or Android for work coexists with your personal Gmail. We take it for granted. As these innovators hustled to disrupt the status quo, the incumbents like Microsoft and Salesforce had to get their act straight, too. Today, many enterprise tools match the user experience of their consumer counterparts. When they don’t, people don’t adopt the tools at work. 

We’re experiencing a similar commodification with AI today. Until ChatGPT burst on the scene, compute power limited the widespread use of AI. It’s been creeping up on us but with rather specialised, narrow use cases. For example, Gmail would autocomplete a sentence for you, a piece of software would reduce noise in your image, or your camera would lock on to the eye of a subject you were photographing. Large language models that run on massive computing infrastructure have now democratised AI beyond these narrow use cases. 

These days, I don’t know anyone who doesn’t use AI in some way. Remember “there’s an app for that”? In 2024, we’ve graduated to “there’s an AI for that.” I imagine this commodification of AI will be a real challenge for enterprises to keep up with.

Riding the AI hedonic treadmill

Between Notion, Adobe, Gemini, ChatGPT, Midjourney, Claude, Grammarly, Krisp and several other specialised tools, I use more AI outside work than my employers provide me at work. Of course, I’m a tool nerd, but I don’t think I’m that unique any more. Cast a glance at your LinkedIn feed and the number of people in your network talking about AI use cases in their lives. Ask your friends and coworkers about how they’re using AI. You’ll arrive at one resounding conclusion -  AI for life outpaces AI for work.

This conclusion has far-reaching consequences. People’s ways of interacting with computers are changing. When people expose themselves to these novel interactions outside work, they expect their work tools to provide a similar experience. We’ve experienced these pressures earlier with Web 2.0 and the smartphone revolution. But this time, things are different. With the unprecedented computing power available, AI innovation is happening faster than anything we’ve seen before. People are getting used to “AI-powered-everything”, and AI is becoming an implicit expectation for work tools. 

Convenience over compliance. All day, baby!

When users get used to an interaction pattern and can’t experience it at work, it frustrates them. Imagine, for example, being able to use NotebookLM for research and synthesis outside work but having to analyse a 200-page document at work - the old-school, manual way. Taking that confidential document and running it through your personal NotebookLM is tempting, right? Yeah, information security and privacy are a problem. Still, you know the choice most people will make between taking a security risk that no one may notice, and the convenience of avoiding a painful task.

Users who don’t get their desired experience may avoid specific tools altogether. At work, there are mandatory tasks and optional tasks. People will grit their teeth and soldier through the compulsory tasks, even if they’re painful. But optional tasks don’t get this free pass. So yeah, if your timesheets app doesn’t have AI, people will still fill timesheets because they want their salaries at the end of the month. However, they won’t wrestle with an outdated experience in creating and sharing knowledge. Make their task more accessible or enjoyable through AI, and you may tell a different story.

More AI, less bullshit?

I’ve mentioned David Graeber’s book, Bullshit Jobs, earlier on this website. Here’s how Vox magazine paraphrases Graeber’s description of bullshit jobs.

“Bullshit jobs are jobs which even the person doing the job can’t really justify the existence of, but they have to pretend that there’s some reason for it to exist. Shit jobs are bad because they’re hard, or they have terrible conditions, or the pay sucks, but often these jobs are very useful. In fact, in our society, often the more useful the work is, the less they pay you. Whereas bullshit jobs are often highly respected and pay well but are completely pointless, and the people doing them know this.”

Dilbertesque corporations are full of bullshit jobs. Heck, I added three categories to Graeber’s original list of such jobs, and I’m sure you can expand that list, too! But capitalism doesn’t need these bullshit jobs. Capitalism loves productivity, and bullshit jobs do anything but productive work. Oh, and here’s a little secret. People doing bullshit jobs would also prefer a real job, but they have no alternatives.

The promise of AI is in eliminating bullshit jobs. Take, for example, the job of the person who curates your company’s weekly newsletter that less than 10% of your colleagues read. The comms person who does this job is probably a skilful writer and content creator. Still, they spend considerable time copying and pasting newsletter submissions, spell-checking and rephrasing them to the corporate voice, and then massaging the content into an email newsletter. AI can do all these low-skill tasks faster, more efficiently and often more consistently than humans. Can your employer delegate this drudgery to AI and use the comms person to create original content instead? Wouldn’t that be a win-win for both the capitalists and the workers? 

I suspect that the more innovative, more agile companies will soon find ways to eliminate bullshit jobs and reassign their people to more creative, meaningful tasks. They’ll embrace AI commodities faster than the Dilbertesque corporation to be more productive and, as a result, more profitable.

Most people predict that AI will have an exponential impact on individual, team, and company productivity in years to come. Many also speculate that AI can lead to large-scale job losses, and some argue that those job losses are already happening. But I wonder if there’s a different way to look at this proliferation of AI. 

Instead of job losses, can we think of more enriching, more enjoyable jobs? Can AI help engage employees better? As against old-school capitalism that squeezes workers, can AI inspire a more humane version of capitalism that delivers higher productivity while giving people more leisure time? How about bigger challenges?

The possibilities are immense and I’ll be honest, they’re out there for anyone' who’s looking. My employers are in the midst of a pilot with Glean - an enterprise search and AI assistant. While the stock Glean installation is enough to supercharge any enterprise knowledge stack, Glean recently hit the ball out of the proverbial park, by helping the average employee become a citizen AI developer, with Glean apps. You can create custom apps for use-cases specific to your work. Check out this video from Glean about how you can create an app to simplify onboarding for your team.

Think about the implications of such tools. In a single shot, you can automate the FAQ and onboarding buddy practices that I’ve earlier advocated for on this site. When AI can free up our time from one set of activities, we can refocus our attention towards challenges that push us to be more creative than the machines. Surely, that’s something most employees and employers can get behind. What do you think?