AI IRL Podcast Episode 46: A Look Back at AI:IRL in 2019
I did 50 podcasts this year.
So for my last episode in 2019, I wanted to look back at what I’d learned from those conversations.
It’s been an exciting year.
We saw a lot of investment from the tech titans like Google, Amazon, and Microsoft, They’re continuing to invest in tools that make AI easier to use and more accessible.
Those platforms really help you to scale.
That being said, AI is still a challenge.
While we see all this great investment, advancement, and predictive models, there’s a lot of work to be done.
AI is not yet mainstream even though some applications of it are.
So be careful if you’re going to build something yourself and leverage a technology platform to do it. You can spend a lot of time and energy and really not see the ROI. Think about creating practical solutions.
“You can spend a lot of time building the data model and then not really get a lot of business value out of it.” — Ryan Lester
Another thing I noticed this year is teams.
They don’t look like they used to.
Now, leaders are bringing in folks that are focused on the customer experience or customer sentiment. They’re even involving parts of the organization that traditionally would have just been handed the answer.
Diversifying these teams shows a level of maturity, I think.
Pointing the Finger at Technology
As more people come in the room, though, a finger will get pointed back to the technology.
A line of business person or an expert in another area may come to a team that’s trying to build a new next-generation AI solution, and it may not go well.
That’s a bad model for technology and problem solving. The right approach is understanding what the problem is and finding the right solution set to solve it
Companies need to be very cautious about having tech becoming their scapegoat when it could be a data problem or a problem definition. Or you could just be going after the wrong problem.
“Going back to classic hypothesis/test/result is really important and not just pointing the finger at the technology because it’s very easy to do.” —Ryan Lester
AI’s Impact on a Business Overall
Chatbots and virtual agents used to be kind of a standalone discussion.
A virtual agent could sit in a contact center, for example. You call the center, and the virtual agent may be able to tell you a tracking number or route you to the right person, but they were often siloed experiences just like on a website.
They could do certain things really well, but they were often very narrow in focus. Now, though, we’re starting to see those virtual agents connect to other systems.
So an AI-powered virtual agent or conversational chatbot now will connect into a subscription service, or it may have more intelligence to actually amend or update information.
We’re moving from these things just being information repositories into something much more dynamic where they can actually act on information.
There’s an evolution that will happen with AI-developed solutions. At first they’re going to be good at knowledge management, then they’re going to start being able the act on that information.
Can they do on the user’s behalf?
Yes. Then, they’re going to start to fall into the world of agency where they’re going to have a better sense of being predictive. They’ll know what you need and go on to service that. We’re starting to see that next move into the next phase where these AI-powered solutions are now getting more and more integrated into other parts of the business where they can create more value.
They can work both in front of the curtain with the customer and behind the scenes. These systems are becoming more extensible and more connected and aren’t just a siloed system that can solve one problem.
“An AI -powered virtual agent or conversational chatbot will connect into a subscription service or a back-end order management system, or may have more intelligence to actually amend or update information.” —Ryan Lester
AI Is Reinventing
A lot of older industries use older technologies. But AI can be a real game changer.
I’ve had a number of people on the podcast in industries — real estate, manufacturing, or even agriculture — where there’s been some automation but which have mostly stayed the same for decades.
And there are new opportunities for AI to transform those industries. One that resonates with me is content management. This is often the most forgotten thing in a business. Some people still use paper knowledge bases where employees are working out of paper references, and AI is really transforming that solution by helping employees better understand what content they need to be curating and updating.
So the real takeaway for all of you out there that listen to this podcast is this: Think about your biggest pain points in your business today. Go find that problem. Be clear about what you want to solve. Know if AI is the right way to solve it. Then, build the solution in weeks or months not years. Learn from it. Rinse. Repeat.
This conversation was taken from our AI: In Real Life. If you want to hear more AI episodes like this one, check us out on Apple Podcasts here.