Determining where the world of work is heading and how it is being transformed is not easy work and there are many great thinkers and institutions spending time on this. But for anyone leading a company or involved in the business of technology transformation, it’s imperative you do your own thinking.

Here is mine.

This is far from absolute. Just some fairly sporadic and speedy sense making on the fly.

I’m thinking a lot about related subjects as part of new trend report: Future of HumAIn Work.

I don’t think there is anything earth shattering in the diagram. I guess the important thing is what to do if I’m even part way right. Here are some added thoughts:

• The S-curve of technology evolution, in case you are wondering, is a model that describes the life cycle of a technology, from its inception to its eventual decline, before it is subsumed by a subsequent or more progressive technology.
• The two recent S curve activities I have plotted are probably correct in the main, I guess it’s the detailed characterisation that is questionable.
  • It’s safe to say Hybrid work is a current state of play for most, despite some company’s operating at the extremes, allowing employees to work fully remote or requiring them to be fully in the office. For most its some state of hybrid presence.
    • I think the whole curve started in the pandemic and the main driver was enabling remote work, so far so obvious.
    • They say necessity is the mother of invention, but I don’t quite see it that way: Innovation is the why, change is the how. I think the pandemic was a crisis that spurred on the use of a lot of existing technology as a way of circumnavigating the crisis. Not an ideal way to innovate and no innovation at all really.
    • Of course, working for Microsoft (disclosure), I would mention Microsoft Teams which did benefit hugely. But so too did Zoom, Google Meet, etc.
  • Intelligent work obviously relates to AI’s use at work.
    • I think some of the early drivers especially for Generative AI have been improved productivity but it’s going to go beyond this to drive real business impact. Good recent report out from Microsoft here: Generative AI in Real-World Workplaces, the Second Microsoft Report on AI and Productivity Research (pdf).
    • I think the release of Chat GPT by Open AI cannot be underestimated in terms of the impact it has had bringing AI into the mainstream. What they did was pretty powerful and can be characterised as breakthrough innovation. And we’ve only just got started.
    • Again in terms of Microsoft technology, it is Copilot for Microsoft 365, which is part based on Open AI’s technology that is going to drive the productivity, innovation and business value.

What to do next

Now the question begged is, what to do if the current wave is right. There are three options:

1. You can wait. It’s early days, the technology is new and immature and there’s a lot of experimentation going one. Being a fast follower is okay and you can let the early adopters make the mistakes. The risk is that they are not going to share all their learning, you will have to go through the curve on your own. On the upside, this may come to nothing and you will have save a lot of time, money and effort.
2. Experiment. This is the middle way and means you don’t have to “bet the farm”. Try some early experiments in proof of concepts in key areas that you have identified, early use cases in other words. Think like a startup: Lean startup methodology applied to successful enterprise technology adoption.
3. Dive in. This is where you have seen the light, maybe you’ve already done some early experimentation, you have some evidence and you go all in. In other words, full scale adoption of the technology in the belief that you will build early advantage.