Wharton School announces new AI for Business initiative

What does this project include?

AI for Business will support students, faculty, and industry. For students, we are focused on developing new courses and experiential learning opportunities. In addition, we will support students who are interested in recruiting into AI-related jobs and companies. For faculty, we plan to support faculty research focused on business applications of AI. Finally, AI for Business will offer online and executive education programs for current industry professionals.

Talk about how the immediate pressures—both practical and financial—may make it difficult for companies to think more strategically about how to use AI.

The current economic strains will put financial pressures on companies and tempt them to move their investments away from long-term strategic projects built around AI. That would, however, be a mistake. We believe there is a practical way for companies to approach AI.

First, while many people perceive artificial intelligence to be the technology of the future, AI is already here and companies should lean in and determine areas that are best suited for AI applications within their organization.

Secondly, the key is to view AI as a tool, not a goal, and focus on the role AI can play in supporting the broader strategy of the company with a close eye for the problems that AI is uniquely equipped to solve. 

Finally, companies should be aware of new risks that AI can pose and proactively manage these risks from the outset. Initiating AI projects without an awareness of these unique risks can lead to unintended negative impacts on society, as well as leave the organizations themselves susceptible to additional reputational, legal, and regulatory risks.

Where do the real gains from AI lie?

Many companies are focused on using AI for cost-cutting efforts. These are low-risk projects and companies will see short-term benefits from these. But it won’t give them competitive advantages, especially when competitors can easily mimic these efforts. Real gains lie in using AI for high-risk opportunities that revolve around customer satisfaction or other revenue generating activities. 

Also, what separates the AI projects that succeed from the ones that don’t often has to do with the business strategies organizations follow when applying AI. For example, machine learning algorithms bring distinct strengths in terms of their predictive power given high-quality training data. Companies can start by looking for existing challenges that could benefit from these strengths, as those areas are likely to be ones where applying AI is not only possible, but could actually disproportionately benefit the business. 

For example, the application of machine learning algorithms for credit card fraud detection is one example of where AI’s particular strengths make it a very valuable tool in assisting with a longstanding problem.

Streaming platforms such as Netflix and other entertainment companies face a dilemma because social distancing has disrupted their content creation pipelines. How can the entertainment industry turn to AI to create content again?

In the past few months, demand for content has grown dramatically as more people are at home and are not able to pursue other forms of entertainment. At the same time, social distancing creates a major supply constraint for the industry. This presents an interesting opportunity for AI. While Hollywood studios will find it hard to shoot projects that require a large crew or that need to be shot in downtowns or other crowded locations, computer vision advancements can help. Special effects software such as frame.io and others will need to be adopted by these studios. VFX software will allow directors to shoot footage in simple locations such as green rooms and with small crews, and yet appear like there is high-production value behind it.

How will students benefit?

In addition to having access to new AI-focused courses, students will be able to apply classroom learning to real life business challenges through an analytics accelerator project, AI focused datathon, Wharton’s Venture Lab Business Challenge, Industry speaker series, and AI focused business treks.

What is the future of AI in business?

The future is very bright, including innovative methods for data collection, content creation, and large-scale automation that are opening new opportunities for business with the use of AI applications. While many companies will fail in their early AI efforts, AI itself is here to stay. The companies that persist and learn to use AI well will get ahead, while those that avoid AI after their early failures will end up lagging behind. 

Any final thoughts?

Given that AI is a new field, it is largely inevitable that companies will experience early failures. Early failures should not discourage companies from continuing to invest in AI. Rather, companies should be aware of, and resist, the tendency to retreat after an early failure.

Anyone interested in learning more about Wharton’s new AI for Business center is encouraged to visit the AI for Business website.