As the year has already kick started and we look at our priorities for 2023, infusing AI into our application and enabling a truly intelligent enterprise is one of our major targets.
We have an AI winning plan which has focus on different use cases from various lines of business and these are positioned for customer usage. We steadily see the number of use cases increasing and some of them are also highly adopted and appreciated by customers. But we still have our challenges.
How can we have even more breakthrough applications of AI that actually influences customer decision making while selecting an ERP software? How can we increase the scale and depth of application of AI within our products?
Quite often a term that is offered as a solution is "AI mindset" across the organization.
What is the "AI Mindset"?
I would interpret AI mindset to mean that employees across Lines of Businesses have an understanding of what AI or ML can and cannot do. Using this understanding they would proactively re-think on how the processes or products in which they have expertise can be further infused with AI to generate value for the customer.
How can we achieve this mindset across the organization?
Before we can answer this question, let us reflect on this: if we ask anyone with limited knowledge of AI to speak about it, what would the most common response be?
Chances are that they will talk about the recommendation service provided by the online shopping experience. And this makes sense - We only understand what we experience ourselves!
How can we make everyone in the organization experience AI more on a day to day basis?
Let us take a look at a scenario:
As a cloud software provider, we have a development system whose uptime is highly critical. Quite often we are plagued with downtimes and performance issues due to the large number of developments that take place on this system and a very large number of developers are affected by this. As a developer, before I release a change, can we use AI to predict the impact on the system? Or can there be a heads-up provided to the Landscape Owners regarding the "possible risk" of an upcoming change leading to some risk-mitigating steps?
Besides the obvious (but difficult to quantify) value of predicting downtimes and reducing risk, the greater value is that we make AI a part of the daily life of each developer/colleague in the organization.
As we experience AI on a daily basis, it will lead to a virtuous circle where everyone understands AI capabilities and naturally applies it to improving processes and situations using the expertise and support from the central AI teams/experts.
If past experience on automation projects is to be used as a guide, a new paradigm once proven and understood, will soon catch fire with multiple colleagues with varied expertise applying this to various different use cases. At this point we would have achieved this AI mindset and astonishing results will follow.
Although it may seem counter intuitive, besides the focus on external use cases, providing adequate focus on internal applications of AI could be a great driver for accelerating and establishing an AI mindset, which will lead to more innovative ideas that reaches the customer.
Let me know your thoughts below.
