Jul 17, 2022
1 mins read
A million pompous Tweets don't lie : Artificial Intelligence (AI) is here to stay. Ok. Good. What now? Well, before AI can truly be called a democratised technology, we have to go beyond Silicon Valley startups and implement it within small/medium businesses and governments.
And so we must ask ourselves : how does a non-tech company go about this? What are the pitfalls to avoid? Where to begin? Below are a few lessons I've learned throughout my time as a technology consultant for some of Europe's largest companies.
Identify and remove small(er) obstacles by answering the following questions
How will we ensure user adoption both internally and externally?
Is the quality of our data good enough for this project?
Are our business and IT teams close enough?
Do we have the relevant AI skills within our organisation?
Does our company have a sufficient data culture within top management? (hint : no)
Are our data management processes adapted?
Avoid the real pitfalls by tackling this challenges
Prefer “Business Pull” to “Techno Push”
Invest in the “boring” architecture and statistics capabilities
Do not make false promises
Be realistic on your skills
Don't copy Big Tech (you can't)
Start with the beginning
Define AI ambition (“Everyone else is doing it” is a terrible reason to get into the A.I game)
Define priority use cases
Gradually industrialize (“AI at scale”)
This is a short form summary of a longer article which you can find by clicking this link.