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