Michael Rivera on Opportunities and Challenges of AI in Business

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In this episode of Lehigh University’s College of Business ilLUminate podcast, we are talking with Michael Rivera regarding generative AI in business and the upcoming 2nd Annual Philadelphia Operations and Technology Day, which will take place at Lehigh University on Friday, September 27th.

Rivera is an assistant professor of Business Information Systems in the Department of Decision and Technology Analytics, or DATA, at the College of Business. His current research focuses on real-time feedback, digital transformation, and digital leadership.

Rivera spoke with Jack Croft, host of the ilLUminate podcast. Listen to the podcast here and subscribe and download Lehigh Business on Apple Podcasts or wherever you get your podcasts.

Below is an edited excerpt from that conversation. Read the complete podcast transcript [PDF]. 

Jack Croft: For the past several years, Lehigh's College of Business has had what's called the Year of Learning around a theme. For the 2024-25 academic year, that theme is Generative AI in Business: Opportunities and Challenges. And, spoiler alert, that's also the focus of the cover story for the next issue of Lehigh Business magazine, which is out in October.

I talked to you for that article and thought you had some astute insights regarding generative AI. So if you could share with our listeners your view of the role that generative AI is already playing in business and what you think are some of the main potential opportunities it presents, not just for companies and organizations, but for individuals and employees.

Michael Rivera: The theme is a timely one. Generative AI is making a significant impact across various industries, transforming how businesses operate and innovate. And anecdotally, we can all recognize that. One of the most immediate roles it plays is in automating routine tasks, which allows organizations to allocate their human resources to more creative functions. So this not only boosts efficiency, but also fosters a more innovative culture within the company.

GenAI also offers tremendous opportunities for personalized customer experiences. By analyzing vast amounts of data, these systems can generate tailored content, recommendations, and even products that closely match individual preferences. This level of customization can enhance customer satisfaction and drive loyalty—two outcomes organizations hope to achieve.

I'll highlight an opportunity for the organization and the individual, just to get a little bit more specific. On an organizational level, GenAI can streamline processes such as product design, marketing strategies, and even decision-making. For instance, it can rapidly prototype new products or simulate market scenarios, giving businesses a competitive edge by accelerating the time-to-market for new innovations.

For individuals, especially those in the workforce, GenAI presents an opportunity to augment their skills. Instead of seeing AI as a replacement, it can be viewed as a powerful tool that enhances one's capabilities, whether that's automating repetitive tasks, providing new insights through the data that they're analyzing, or even assisting in creative endeavors like content creation or design.

However, with these opportunities come challenges—ethical considerations, the need for transparency, the potential for job displacement. It's clear, organizations and individuals alike must navigate through these complexities thoughtfully to really harness the full potential.

Croft: What are some of the greatest challenges? And I know this is a big topic because you kind of outlined several of the main things I think a lot of people are talking about now and looking at. But what are some of the main ones that are facing companies and employees with generative AI now?

Rivera: One of the most foremost concerns is ethical implications. Generative AI can create content, it can make decisions, it can automate processes. This raises questions about transparency, accountability, and bias. As an example, if an AI system generates biased outputs due to flawed training data, it can lead to unfair or discriminatory practices. This affects customers and employees. Companies need to ensure that their AI systems are not only effective, working, but are also ethical and transparent in their operations.

There's a couple more challenges I could highlight. There's a challenge of integrating AI into existing business processes. Implementing GenAI solutions can be complex and requires not just technical adjustments, but also changes on the human side, like organizational, culture, and ways of working. Companies need to ensure that their employees understand how these tools work effectively, and that the AI systems are aligned with the company's goals. Alignment is important.

For employees, that's the challenge of job displacement and the potential need for reskilling. As AI automates routine tasks, roles may become obsolete. This can trigger workforce reductions or shifts in job functions. This creates a pressing need for employees to adapt and acquire new skills, continually upskilling, that complement AI technologies. Companies need to recognize that upskilling and retraining programs are necessary to help their workforce transition into roles where human skills like creativity, problem solving, emotional intelligence are paramount.

And lastly - I think that this is important on the business side - there's a risk of overreliance on AI. If companies rely too heavily on AI-generated insights or decisions, they may lose that human element that is crucial for nuanced judgment and creativity.

Leveraging AI might help drive best practices, which is good, but a key strategy businesses employ is through differentiation. They don't want to lose this. They don't want to do the same things that everyone else is doing because they're using the same system with the same trained data. Striking the right balance between leveraging AI and maintaining human oversight is really key to navigating these challenges I mentioned.

Croft: One of the things that a lot of people are trying to work through now is how generative AI has altered the interaction between humans and machines. And you touched on that with your last answer there about the human side and what humans bring to the equation. So just to talk about that a little, what is it about us, as human beings, that protects us against the robots or the machines taking over the world as some people fear?

Rivera: I mean, I think it comes … in highlighting maybe a very nuanced point. Humans have judgment, and we have creativity. Those are some of our special abilities that give us an advantage. They bring something new and novel to the equation of making decisions, creating strategy, achieving goals. Our opportunity is around finding a way that we can do what we do best, and utilize systems that can complement that. And so there again, striking the balance, finding the right balance between those two is so important.

I will also say it's hard because we have jobs, we have lives, we become used to how we work and how we do things. Making this transition requires that we engage with the change management process and figure out how to shift things like culture, how to adapt in terms of ways of working. These aren't easy. All of us that have worked in organizations know that making change transitions can be just as hard sometimes as the technical system ones, but are critical to the overall success.

Croft: OK, it's crystal-ball time. And I'm wondering, how significant a role do you see generative AI playing in business in, say, 5 or 10 years? Is it truly one of the more disruptive technologies we've seen in recent times?

Rivera: Wow, 5 to 10 years, I think generative AI is poised to play a transformative role in business, period, becoming an integral part of everyday operations and strategic decision-making. We're likely to see AI not just a tool for efficiency, but as a core driver of innovation across all industries. Businesses will increasingly rely on GenAI to create new products, services, and even business models. And that really pushes the boundary of what's possible.

One significant area of impact will be in the automation of complex tasks. So we mentioned earlier today, AI handles many routine processes. But in the next decade, we can expect it to take on more sophisticated roles, such as generating detailed marketing analyses, developing intricate design prototypes, or crafting personalized customer experiences at scale. And this shift frees up that human talent to focus on higher-order work, strategic thinking, relationship building, areas where human intuition and emotional intelligence are critical.

I think GenAI will also become more collaborative. Again, nurturing that human and machine element, but refining it and maturing it. And in these business settings, AI systems will be able to synthesize vast amounts of data to generate insights, predict trends, and even recommend strategic actions. These human-AI collaborations will lead to more informed and agile decision-making, helping organizations adapt quickly to marketing changes.

So in sectors like health care, finance, and manufacturing, key industries we're often focused on, this could mean better diagnoses, smarter investment strategies, and more efficient production processes. I think GenAI will likely revolutionize personalization and the way we engage customers. I can imagine a retail experience where AI not only predicts what a customer might want, but also designs and delivers it for them.

I think, in essence, to kind of sum up, generative AI will not just change how business operates, it's really going to redefine what is possible in the business world. And at Lehigh, we're training students to enter new organizations, equipping them with the skills to help these companies embrace this technology thoughtfully, and be well-positioned to innovate and thrive within our competitive landscape.