Human and organizational considerations in “Scaling AI”

In time, most organizations will turn their attention from future readiness and establishing themselves with AI to focus instead on scaling (and sustaining) their investment in AI and the data platform upon which it depends. Put another way, one-time consolidation and readiness of data combined with a few AI-driven workloads does not a future-ready organization make.

I’ll share a short story…

Recently my wife, Ana, and I found ourselves sitting at a café in Melbourne, Australia, with most of the day left before we needed to catch a flight. My first instinct was to spend thirty minutes scouring the internet for things to do or see in Melbourne, an idea that I did not relish because I dislike being glued to my phone when in good company.

Ana suggested that I seek advice from Bing, Microsoft’s AI + chat enabled search engine. I had not thought of this, but curiously explained the situation to Bing and clarified where we were, how much time we had before we needed to go to the airport, and what kinds of sights we like to see when visiting a city. Much to my delight, in about fifteen seconds Bing suggested an entire itinerary for the day including sights to see and places to eat and drink. The itinerary was even organized according to a logical walking path from the place in the city where we were then sitting.

This capability had been in my pocket for months, but so ingrained was the impulse towards self-directed Googling that it had never occurred to me that AI-infused Bing could do the work for me so much faster. Off we went to explore Melbourne!

You see, there are non-technical organizational and human considerations that should be taken as you scale AI across the organization. This significant element of people-centric scaling and change management is required here, in other words, to scale AI by baking it into the way people work.

Join me—Andrew Welch—with HSO’s "Dynamics Matters” podcast host Michael Lonnon for part four of our AI strategy miniseries as we explore the challenges and opportunities bringing AI to your colleagues at scale, and the big obstacles that many organizations have doing so: the Use Case Death Spiral, IT Tower of Babel, and the Tyranny of the Deliverable.


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