In our rush to create volumes of data, we have become awash in it to the point of madness. But, when you have the mindset and goals to leverage “Data + AI”, then you have a powerful combination.
Additionally, data + AI can accelerate insights and decision-making that would have been impossible in the past. The efforts in the realm of AI are now focused on accelerating, augmenting, and collaborating with humans. So, what’s on the horizon?
Joining me on this episode to discuss this is Thomas “AI Nerd” Helfrich. He is the CEO of instarel.ai, an advisor to the SwissCognitive, content contributor to The AI Journal and Entrepreneur Media, and an official member of the Forbes Technology Council.
Highlights
01:31 – AI has significantly grown, as there has been rapid adoption of AI across companies in several industries. However, there are still some who don’t see its full potential. So, has an AI overload caused people to be overwhelmed and not fully understand this technology?
04:44 – There’s a misconception that AI is going to replace people. But the human element is still critical to AI success. Rather than taking jobs, AI will create exponentially more opportunities and high-paying jobs.
06:45 – There’s still inherent bias, as humans are the ones writing the algorithms. Often, it’s just a bias that appears because something wasn’t accounted for. It’s not intentional, but it requires humans to correct it.
08:45 – In order to build trust in the system, you must be able to explain why decisions are being made based on the outcomes of that system or algorithm.
09:28 – When patterns of bias arise on both sides of your model, you can refigure the model to eliminate areas of unfairness if you have the transparency to make revisions. However, there’s a greater issue if the unfair model is hyper-profitable or accomplishes the business’ goal. While there needs to be transparency, there will also still be a gray area in how to address perceived bias.
11:52 – Although machine learning is intended to improve the customer experience, it can also hurt the customer experience. How can there be a counterbalance to using machine learning?
16:48 – Modern-day AI systems need to be built for purpose. If you’re going to use these technologies to enhance the customer experience, they need to be equipped to process information that will enable them to help customers.
18:11 – AI helps with initial engagement, but does it help improve the business process? Does it provide data that suggests ways to improve the system?
20:09 – Small and mid-market companies may have to navigate AI tools and leverage them in different ways, as a higher level of AI may seem out of reach for them. Fortunately, as AI continues to develop, it will become more accessible and easier to use.
22:05 – Along with the rise of cloud technology, there has also been a recent rise with AI clouds being purpose-built for certain industries. It has shifted more to customization versus just building a system.
25:30 – Intelligent automation, AI, and other advanced technologies, nowadays, have to be part of your strategy, as it enables businesses to make informed decisions faster.
27:26 – When it comes to expectation versus reality with AI, realistic components are that it’s built for purpose, looks at big picture items, and integrates well within your system. Additionally, AI is a tool to be intentional with and should be a part of your core foundational strategies.