To begin with, a lot of talk is currently in progress citing importance of thinking in the direction of AI adoption. Nearly all the major technology disruptions in progress be it intelligence gathered via big data, internet of things, blockchain, cloud computing or flow based pattern recognition systems talk of their advancement or path towards collaborating in an Artificially Intelligent environment.
As per surveys attempted by prominent survey giants 47% of firms are talking about adopting an AI focussed roadmap starting with embedding at least one AI capability in their business processes.
Out of these 20% are using AI in their core part of business processes.
30% are looking at piloting AI in one way or another over the course of next year or so.
Current spending although holds around one tenth of budget for 58% of the firms adopting AI but this is expected to grow in next 5 years to 71%.
Most of the firms use AI in marketing and sales (52%).
Value generation quotient in AI has been prominent in manufacturing & risk analysis - 41% reporting significant value & 37% percent in marketing and sales reporting moderate value.
Primary areas of inception being robotic process automation, nlp & machine learning.
The first approach should be to think differently and move away from a siloed function centric mindset towards an integrated process centric mindset.
In order to do that, establish data points across systems to provide more streamlined flow of data across business units.
Establish a more ingrained process centric view which breaks down the approach into adoption areas based on adoption strategies for short and long term.
De-prioritize functions in favour of processes.
Think on purchasing AI services.
Processing & data management is key so approaches which allow for enhanced processing and storage management of data should be a priority.
Training data is key and initial training would need specilists supervision.
Analytics forms a key data entry point in any AI process adoption - so get your analytics right!
Although the adoption process is a long journey but above factors might be able to give a start to that path..
References & further reading - Mckinsey Reports, Forbes & O'rielly articles - AI adoption.
Question is why so let's talk about some numbers here..
As per surveys attempted by prominent survey giants 47% of firms are talking about adopting an AI focussed roadmap starting with embedding at least one AI capability in their business processes.
Out of these 20% are using AI in their core part of business processes.
30% are looking at piloting AI in one way or another over the course of next year or so.
Current spending although holds around one tenth of budget for 58% of the firms adopting AI but this is expected to grow in next 5 years to 71%.
Most of the firms use AI in marketing and sales (52%).
Value generation quotient in AI has been prominent in manufacturing & risk analysis - 41% reporting significant value & 37% percent in marketing and sales reporting moderate value.
Primary areas of inception being robotic process automation, nlp & machine learning.
With all these numbers, question is how to start progressing in the direction adoption?
The first approach should be to think differently and move away from a siloed function centric mindset towards an integrated process centric mindset.
In order to do that, establish data points across systems to provide more streamlined flow of data across business units.
Establish a more ingrained process centric view which breaks down the approach into adoption areas based on adoption strategies for short and long term.
De-prioritize functions in favour of processes.
Think on purchasing AI services.
Processing & data management is key so approaches which allow for enhanced processing and storage management of data should be a priority.
Training data is key and initial training would need specilists supervision.
Analytics forms a key data entry point in any AI process adoption - so get your analytics right!
Although the adoption process is a long journey but above factors might be able to give a start to that path..
References & further reading - Mckinsey Reports, Forbes & O'rielly articles - AI adoption.
No comments:
Post a Comment