Understanding your AI Maturity
Last week, on the back of the hired!bcn conference, I wrote an article intended to start a conversation on Artificial Intelligence and what it could mean for businesses.
AI clearly is a subject that has caught people's imagination, and it seems to be a disrupter as much as what the World Wide Web was perceived to be when it started the dot-com bubble in the early 2000s.
John Plender in the Financial Times seems to believe that, although comparable, this potential bubble is not 'dot-com redux', as he calls it. I guess we have to wait and see, but I want to offer some concepts that could help us make sense of this.
I would suggest that there are at least two key conceptional dimensions that need to be considered when framing the AI developments in a business context.
How will your strategic operating model evolve over time with the evolving global market?
How will your organisational AI maturity coevolve with the market to ensure you are able to execute the activities required to operationalise your strategic operating model?
Let's start with the second question this week, because it in itself should already trigger some key questions and considerations, prior to embarking on strategic operating model conversations.
An Artificial Intelligence Maturity Model
When developing a maturity model, my clients usually find it helpful if I use a simple metaphor to describe the levels. A useful one is the 'crawl-walk-run' model that describes the journey that most people embark on during their lives.
See the image below with some phrases that could describe the characteristics of each of the levels.
Do these levels and their descriptions make sense to you?
A key premise, of course, is that before a baby can crawl, it needs to sit stably first; we need to be able to effectively walk before we can run and if we want to launch ourselves off a cliff with a delta wing, we need to master both running and jumping (and holding the wing, I suppose). That is what we call maturity.
We need to have established a certain level of maturity, before we can try to master the skills of the next level.
In an article that I wrote a couple of years ago about what I call 'the law of the requisite maturity'. The key message there was that it is very difficult to get any business model adopted if we are not yet mature enough to understand the challenges we face. Can we aim to fly, if we don't know what the things are I need to know and master to do just that?
Another key premise is that, although we all could have the ambition to eventually majestically fly through the Pyrenees or the Alps, we most certainly not all have this ambition.
From a business perspective, we have to realise that there is a significant cost to keep pursuing progress on the maturity curve. Therefore, it is essential to set our desired level of maturity, both at a corporate and a departmental level. And then stick to that. Much of that may well be defined by the markets we choose to operate in. Evolution is an ecosystem-wide process. We need to continuously benchmark ourselves with our competitors.
We need to ensure that our AI maturity matches our strategic ambition. Not less, of course, but also not more.
Lastly, we may be limited by the skills and capabilities available in our chosen markets. That is our internal skills and experience, but also that which we may want to acquire in the market. After all, we won't be the only one and essential AI and Machine Learning (ML) skills are scarce.
We need to ensure that our skills and capabilities are an inherent part our desired AI maturity levels.
Lots to consider.
For us as business organisations, but also as individuals working in this evolving landscape.
How does this model resonate with you?
So, where do you think your business maps onto this maturity curve? And why?
Are you consciously thinking about where you are and where you want to be?
Have you figured out how to measure your maturity, not just qualitative as in the proposed model, but also quantitative mapped to your business's KPIs?
Will there be an 'AI bubble' that will burst like the dot-com bubble, or is the FT's John Plender correct?
Next time I will explore operating model elements, we might need to consider if we would like to move up the maturity curve. Any ideas would, of course, be very welcome.
This is a conversation, after all!