How SMU Cox is Stepping into the AI Era

From a new master’s in AI for Business to fundamentals-focused teaching, the Cox School is preparing graduates to lead responsibly in an AI-driven world.

SMU Cox students sit in a classroom with stadium seating

Coxtoday

Faculty and Staff News

April 30, 2026

Author: Sam Eifling

As a self-described “IT guy,” Amit Basu looks at the business implications of relying on artificial intelligence through a particular lens. Although certain tools and platforms offer terrific promise when a company first adopts or deploys them—and makes leadership feel brilliant in the process—achieving sustainable business success with technological innovation is complicated and depends on many factors, including infrastructure capabilities that may take time to evolve.

Basu, the Carr P. Collins Chair in Management Information Systems at SMU Cox School of Business, coaches his students to think of AI tools as fluid, not static. As an AI gathers new data, it simply isn’t the same product that arrived out of the box.

“The systems are dynamic, unlike traditional information systems and applications,” says Basu, who also chairs the Information Technology and Operations Management Department. “Even after they’re deployed, they’re changing—which means that the system that was installed six months or a year ago in your company is not the same as the system that just screwed up.

“That creates a real dilemma. If you’re a leader in an organization, and the success of your organization, your reputation, and the welfare of your customers and partners all relies on the system, you have to think about how you go about this in a way that is responsible.”

Like many other technologies, Basu says, AI is transforming and disrupting the world. However, a unique facet of this technological transition, he notices, is how much the move to adopt AI has been led by everyday consumers. As just one benchmark: In January 2023, ChatGPT reached 100 million monthly users faster than any other application in history, just two months after its release.

That breakneck speed of adoption immediately led to demand from potential students and their parents to incorporate AI into the business curriculum. Today, classes at the Cox School are led by some of the top AI thinkers in their respective fields, who strive to balance the principles comprising a business education against the tremendous upside—not to mention sheer enthusiasm—of the suite of applications that have hit the market.

“Ordinary people are using AI before technicians and professionals are using AI,” Basu says. “If you think about it, how many technologies have we had like that? Where laypeople are playing with the technology before the professionals?”

The speed at which people and companies are adopting AI tools complicates many of the concerns about their effective use in business. In addition to the challenges of keeping up with the rapid pace of AI technology innovation, business leaders will have to also deal with key questions about ethics and transparency in AI use.

The “black box” nature of many AI systems is a key source of complexity. Ethically, how should leaders apply AI solutions to problems if those solutions could contain biases against underrepresented people? And how can you assure your employees that you’re making decisions in a transparent manner if you’re relying on AI tools that continually evolve in ways that you can’t readily explain?

“If you look at AI like a black box, it seems capable of doing amazing things,” Basu says. “And then sometimes when it doesn’t—what happened? That’s why we believe in training students to understand how it works, so that it can be a valuable tool, even if it is imperfect.”

The AI surge meets reality

Even if they choose not to concentrate in AI studies, students emerging from today’s universities and business schools are entering an economy that will expect them to navigate AI tools and platforms. The bets that American companies have made on AI are positively staggering. In November 2025, Goldman Sachs released a report estimating that in the previous three years—the ChatGPT era, basically—companies involved in AI tech have risen in value by $19 trillion. For a point of comparison, the gross domestic product of the United States is about $30 trillion.

The investments and valuations have outpaced the available workforce, leading to huge rewards for young AI workers. The Wall Street Journal reported in August 2025 that from 2024 to 2025, the base salaries for nonmanagers in AI-related jobs with less than three years’ experience leapt by 12%. Also, last summer, PwC found that workers with AI skills commanded a 56% premium in their wages.

Yet while companies are rewarding young AI experts, they’re also trying to use AI tools to automate tasks usually given to recent graduates. Between January 2023 and June 2025, job postings for entry-level workers plunged over 35%, per a study by the labor research firm Revelio Labs. The adoption of AI tools doesn’t explain the entire gap, but it’s a huge factor—one that is creating further incentives for students to lean into the technology.

Those huge bets by American companies and the ubiquity of the tools can lead to a false sense of inevitability, however. Venkatesh “Venky” Shankar, the Harold M. Brierley Endowed Professor of Marketing and Chair of the Cox Marketing Department, reminds his students that AI is far from infallible or even authoritative. He incorporates class exercises meant to illustrate the tools’ stochastic calculus—in short, their ability to account for randomness, a trait that, even using flawless data, will nonetheless produce unpredictable outputs.

Shankar recalls one session of his class on AI applications and marketing. He gave the students identical data sets and watched as the exercise produced different results for different students. When this happens, the professor says, the next step is to review the answers as a class and “debug” the results.

They found that the tools made different assumptions for different students. Without that insight into the process, the students would be at the mercy of whatever responses their applications spit out.

“These generative AI tools themselves are some sort of a puzzle to even their creators,” Shankar says. “They take all the previous data available and the reservoir of information on the web. Then they get trained to predict the next word if you’re asking for a textual query or next image or next pixel.”

This probabilistic modeling—making educated guesses, essentially—leads AI tools to offer up the occasional “hallucination.” That is, a highly plausible but wrong answer. Shankar explains that to make more effective queries, students will learn techniques such as retrieval-augmented generation, which allows a large language model to find authoritative data outside its training data sets.

But in many ways, the job of a student learning to push AI to its limits involves respecting those limits—and considering the ways in which the answers AI offers up could ripple outward if the people using those tools don’t approach them critically.

“As they say: ‘Trust but verify,’” Shankar says. “We must somehow find the right balance. I always learn, every time. I’m teaching this AI in marketing course for the first time, and it’s like drinking from a water hose or fire hydrant. We have to get students up to speed on basics and applications. I reflect on every exercise from every class—what went right, what went wrong, what did we learn that we could do differently as leaders or stewards of businesses and society in the future.”

Academia meets acceleration

This fall, the Cox School will welcome the first cohort into its Master of Science in AI for Business degree program. Students will be immersed in the study of analytics and other data-driven curriculum and emerge from the yearlong program with a rich understanding of machine learning and large language model technology.

“Students will gain significant exposure to cutting-edge AI skill development and business cases,” says outgoing SMU Cox Senior Associate Dean Bill Dillon. “When they enter the workforce, they’ll do so as experts in AI, prepared to drive AI innovation across industries—a bit different than the way we typically think of an entry position.”

The expectation, Cox professors say, is that students graduate prepared to use current tools and platforms while also laying a foundation that will allow them to move into leadership roles as the technology evolves.

“We hope to make this program lifechanging for many of them,” Shankar says.

The speed of technology has presented a rare level of challenge to educators. Compared to many of the companies where graduates will get jobs, academic institutions tend to be slower moving, firmly rooted in long traditions. Changes tend to be incremental.

“We rely upon the entire history of education to evolve,” Basu says. “That allows us to provide continuity.”

Then, every so often, a technological jolt comes along so profoundly and so valuable that the market insists academia adapt. The future is rushing to meet students, researchers and educators alike. The implication of AI on workers, especially, will be profound.

Utopians suggest workers might make more money for fewer hours of their time, leading to greater chances for leisure and retirement. But it’s also clear that if AI can automate certain jobs out of existence, other workers may be looking at longer bouts of unemployment or a slower on-ramp to having a career at all.

Amid the rapid change, Cox professors emphasize that the strength of the classroom includes instilling fundamentals in their students.

“For undergraduates, we are emphasizing doubling down on the first principles,” Shankar says. “Pen-and-paper tests sometimes. Critical discussion in classes. All of these things.”

Shankar cautions his students against becoming too enchanted with these new tools too quickly. He warns in a recent article published in Journal of Macromarketing that AI presents a “twin” face to many industrial sectors, offering huge opportunities to create new products and to scale up tech solutions efficiently, while also presenting threats to privacy, security, information accuracy and stability.

Yet he’s also bullish about the potential of advances. In particular, agentic AI tools—those that work on specific goals with a high degree of autonomy—which he sees as having wide and deep benefits for companies that deploy them smartly. These are systems that can process oceans of data, adapt on the fly to changing conditions, communicate effortlessly about decisions, and consistently fine-tune their responses to keep customers—that is, people—happy.

Equipping workers and leaders with tools that sophisticated promises to alter the course of business strategy for huge swaths of the economy. The rewards for graduates who successfully combine an understanding of such powerful new tools with a mastery of business fundamentals such as risk management, digital strategies and product development are potentially enormous.

“Students can go and apply that knowledge and skill set in the workforce and have a really sizable advantage, if you will, and hit the road running,” Shankar says. “Businesses want people who are familiar with the tools and applications. But they also want the strategic thinkers and reasoners who can go beyond the AI tools with critical reasoning—and help the firms lead.”