AI Transformation, Toolbelts, Talent, Time & Teawork

Pearls of wisdom from the AI & Intelligent Automation podcast episodes 51-55

Seth Adler

Industry transformation– AI decentralization

Episode 51: Thomas Birr, Innogy

It will not be a disruption for the consumer, so the consumers will at the end of the day, they will only realize that there is more convenience, more comfort, more security in the grid's more sustainability. But transformation from a central system to a decentralized system is a disruption for the actors in the market at the end of the day.

Thomas happens to be discussing the transformation of the global energy infrastructure. But within the interview, he points out that Artificial Intelligence is at that heart of that industry transformation. Is there a signal here for other industries? Is there a signal here for every industry? The decentralization of the global economic infrastructure through the universal adaptation of Artificial Intelligence- only time will tell.


AI in your toolbelt– sensor in your mind

Episode 52: Najam Baig, Nissan

Whether we’re working on autonomous vehicles or our data centers, we e focus on the business problem. We try to find an opportunity to do something machine learning or AI techniques. But sometimes we don't even need the fancy technologies; we can do a lot using simple sensors.

Simple sensors are the source for IoT. And the data that comes from IoT solutions could be fed into a machine learning algorithm to provide true artificial intelligence. Or that could be a gargantuan waste of time based on the business problem at hand. You don’t always need a 5oo year old samurai sword. Even if your shed includes the most impressive of tools, sometimes you just need a butter knife. 


AI job loses and best talent promotions

Episode 53: Glenn Skarott, Macquarie

No one wanted to talk about the fact that jobs were being sent offshore; no one wanted to talk about the jobs that may be lost. But it happened. It occurred. What we're trying to do is make everyone aware. We ensure that they know that they're in a changing environment– they work with that. Someone that comes in and rearranges a task or process, and we take out five FTEs, that person doesn't need to worry about losing a job. That person should be promoted. It's celebrating that success and showing the opportunities that are still going to exist in the organization. We need a diversity of the skill sets. So, actually bringing in people with IT skills, into finance, bringing in people with certain data skills, data scientists, mathematicians, those different skill sets also bring in a different way of looking at things, which is really helpful when we're doming to think about problems that we have.

People will lose their jobs if they don’t evolve. Glen is sharing the fact that it’s a disservice to the enterprise and to any non-evolving employee not to have that discussion loudly and out in the open. The best talent with broad skills who are willing to adapt have no reason to worry. Unless you aren’t having an honest conversation within the organization about the talent that will absolutely stay and the talent that will absolutely go. They’ll go– either because they don’t have a big enough ego, or because they’re fearful for the fate of your enterprise.


Digital transformation one day at a time

Episode 54: Mark Beaumont, Cycled around the world in 80 days

I started to hypothesize about the 80 days: I need about five hours sleep minimum. To go around the world in 80 days, that's 75 days riding, three days for flights, two days of contingency. Break that down. 75 days. That's going to be 240 miles a day, so about 380 odd kilometers. You need to average about 25 kilometers an hour average, about 15-16 miles an hour. In an hour-by-hour, day-by-day metric, it's totally possible. 240 miles is not your best day where you start fresh and you nail it. 240 miles is your average day. You have to do that every single day for two and a half months. You never do better than what you set out to do.

Admittedly Mark Beaumont is a super-human. But the biggest thing he did to ensure he cycled around the world in 80 days was to boil down is ridiculously expansive goal to what he needed to do today.  He knew that he was able to accomplish the daily task. He then simply needed to repeat that task 75 times in a row. Sure, you could make the analogy that he’s doing robot’s work and should be automated. Or you could realize that he transformed humanity’s understanding of what was possible. And you could realize that your organization needs to transform to be able to deliver what humanity will need from it in a decade. What can you do today?


Business + IT = AI

Episode 55: Panel- IT to Business, Business to IT

When you have a group of IT people working closely with your business people it forces you to have at least a decent knowledge for the actual business, not just the technology.

It turns out the best way to break down the siloes is to not work in siloes. Some centers of excellence are already aware of this ethos. And the business vs. IT issue in intelligent automation has come along way in less than 12 months. But the ‘us vs. them’ mentality does still exist in some global corporate enterprises. ‘Who owns what’ is still a question that is asked. If that department doesn’t have some people that at least sit in this department, change that. And if you can’t change that, you’re in the wrong place.