AI Requires a Measured Approach - It is not Magic

In a recent presentation by Steven Astorino, Vice President of Developments, Data and AI at IBM, Astorino has warned that new businesses adopting AI solutions for the first time may be overwhelmed by vast amounts of unsorted data.

IBM has noticed a sharp uptick in the adoption of AI across many industries, especially since the Coronavirus pandemic.

The issue does not lie in businesses embracing technological solutions to data gathering, but in the overwhelming nature of having a large amount of information and not knowing quite what to do with it all. A study by Forrester stated that just over fifty percent of businesses experimenting with AI struggle to properly sustain, scale and implement the data they receive from their AI foray. Another more pertinent fact gleaned from the Forrester study, “Challenges That Hold Firms Back From Achieving AI Aspirations,” was that up to eighty percent of data is simply stored, or is not business-ready.

To put it simply, you cannot use AI without IA (Information Architecture).

IA can help businesses become more successful in using AI, by collecting and organising data before analysis and implementation of data mined using AI solutions. IBM has flagged these issues, and is providing tools and guidance for their clients by largely automating the organisation and collection of data.

Astorino helmed a presentation concerning IBM’s approach to IA for AI at the first virtual World Summit AI Americas. He commented that “I’ll show you how enterprises can build a governed, efficient, agile, and future-proof approach to AI. I’ll also touch on the most common barriers to AI adoption faced by AI evangelists in their organizations: data complexity, the competition for AI talent, and securing c-suite trust in AI-infused business insights. Lastly, we’ll walk through IBM’s leading-edge AI tools like Cloud Pak for Data and Watson to simplify your AI journey.”

Watch the full presentation here: