AI Offers ‘Real Solutions for Real People’ Amid Pandemic

By Megan VerHelst

On paper, Matthew Lamons is an artificial intelligence strategy architect at the Intelligence Factory, the St. Louis-based company he co-founded two years ago. 

But if you ask Lamons what he does, he’ll tell you he’s two things: a translator and a storyteller. As both, he connects what he calls “two sets of very smart and accomplished people” — the engineer or scientist at his company doing amazing things with artificial intelligence, and the corporate decision-maker searching for a new set of tools to simplify operations within their company. 

Lamons does this work because he “really likes solving problems” and, as Iowa moves through what’s called the Fourth Industrial Revolution — or Industry 4.0 — companies will need to undergo a digital transformation and take full advantage of artificial intelligence in order to solve many of theirs. 

At the Iowa Association of Business and Industry Advanced Manufacturing Conference held Sept. 30, Lamons spoke on how the COVID-19 pandemic affected the urgency of this digital transformation and whether Iowa manufacturers and other industries were able to embrace artificial intelligence in order to overcome the challenges. 

The Business Record caught up with Lamons after the conference. Responses have been lightly edited for clarity and conciseness.

Many of your talks and writings focus on deep learning and artificial intelligence. To someone who’s not familiar with the concepts, what does this mean, and why is it important now? 

Artificial Intelligence — or “AI” — is basically a computer algorithmic system that learns from data and doesn’t have to specifically be rule-based. What AI fundamentally does is infer a rule based on a lot of experience with a set of data and the presentation of a “ground truth” answer. 

Today, with the super large sets of data we have and the complexity of that data, it’s impossible for people to see enough of it to make the same inference. Now, computers are being programmed to learn from the data in order to map complex functions and provide effective recommendations or predictions. 

AI is important now because information and data comes at us and into organizations too fast to be effectively dealt with by people. Now, AI applications or programs or bots can provide recommendations on how to deal with this data. This saves time, reduces risk, reduces costs in organizations, improves customer experience, increases profits and protects company margins.

How has your definition of innovation changed or evolved over the years?

I think, like most people, there was an element of “magic” that went along with the idea of innovation in the past. We often hear of the rock-star companies doing crazy things with AI or virtual reality. Really impressive things have and are being done for sure, but for me, my definition of innovation has certainly changed from what can be done to make a real positive impact to what should be done. I’m much more focused on applied AI engineering now and building real systems that do real things for real people to help solve real problems.

Where do we already see AI in our daily lives?

We see AI in search recommendations on Google and product recommendations on Amazon. We also see AI in the form of anomaly detection when we get a text from our credit card company asking if we’ve made an unusual purchase. Those are examples of complex algorithms that have created a model of a pattern of data from behavior. AI also is seen most notably on our smartphones when it wakes up with facial recognition, or when you use Siri or Alexa.

Are businesses taking advantage of AI? What reasons ultimately lead them there?

Companies are definitely starting to take advantage of AI. They see AI as a core part of their strategy to combat the effects of COVID-19 and provide for better customer engagement. AI is also being used to manage and optimize extended supply chains and procurement. Some common reasons why companies are turning to AI are to accelerate time to market, decrease costs, become more agile in their company operations and to mitigate supply chain risks.

In your presentation at the Advanced Manufacturing Conference, you talked about DX information stack. What does that mean, and how is it applicable to businesses?

The DX information stack is a summary of the entire set of information element classes an organization uses to operate. It has two groupings. There are elements like sensory data from cameras or traditional data that can be easily processed by computers. But the second half of the DX information stack are elements that are hard for a computer to process. This is brain power and categories of information like knowledge and wisdom. This second half is where decisions are made … and traditionally have a hard time getting back into digital processes. This is what we at the Intelligence Factory are working to fix with EnterpriseDaiX. This would make it possible for businesses to leverage all of their information and resources for optimal operations.

What are some real-life examples of what digital transformation can do for a business?

It makes it possible for their customers to engage in the sales process online versus in person, or it helps businesses conduct customer service online versus over the phone. These are common examples. What companies are also looking to do is get better internal synergy between their operating systems. 

What makes business and industry leaders hesitate to jump on the AI bandwagon? 

I think some of it comes from the new nature and technical exclusivity of artificial intelligence. But when leadership focuses on it as a tool, or a means to a desired outcome, things get easier. Another barrier is that data scientists and AI engineers often speak a different language than business decision-makers, so there’s translation needed to get everyone moving in the same direction.

Has the COVID-19 pandemic affected how businesses view AI? 

Yes, certainly. Ninety-seven percent of companies have accelerated their digital transformation initiatives, and that nearly always includes the implementation of AI or machine learning. This is all because of the “focus” that COVID-19 has given people to take steps necessary to improve their operations and to increase resiliency in their supply chain.

How are businesses reacting and adapting to the stress test that is the COVID-19 pandemic? 

First, businesses are cutting spending and working on digital communication to make sure they can continue operations despite the pandemic. Secondly, they are initiating DX projects to incorporate more mid-term value into their operations via AI. Last, they are looking to shock-proof their companies by increasing their supply chain resilience. 

Beyond the pandemic, what other ways will AI affect the manufacturing industry?

I think AI will drive advanced robotics and 3D printing in manufacturing. We’ll also see the ability to increase product variety and increased speed in bringing products to market because of the efficiencies from AI.

What technological challenges does the manufacturing industry face in implementing AI systems? 

The primary technical challenges come from needing to retrofit a manufacturing plant to make it ready for digital production. Sensors and equipment that generate data need to have a pipeline for that data to get where it needs to go so it can be used for training advanced control systems. 

How would a business or industry know when AI is the right solution to a challenge?

This comes from a collaboration between AI consultants and engineers and industry leaders. Not every problem needs an AI solution; it’s an analysis of how businesses would use it, the implications of implementing a data pipeline and AI system, and looking at the immediate return on investment and future enterprise capabilities that tells us when a particular project gets the green light.

What are your predictions for the future of AI in manufacturing and other areas of business?

Just like they run on electricity, every manufacturing company will be using AI to some degree in the future. This is true for every other area of business. We couldn’t imagine doing work without the PC — well, now those PCs can not only store our information, they can learn from it. And with that comes new capabilities and value that will make our companies and lives much, much better.