What Is the Future of AI?
By Professor Eric T. Bradlow (@ebradlow) (GBK Collective and the Wharton School)
I recently had the pleasure of hosting a 10-part Wharton podcast series called “AI in Focus” discussing the impact of AI as adoption continues to grow. I interviewed Wharton faculty experts across a wide range of business domains — from health care and neuroscience to sports and the auto industry — to learn how AI will impact these fields moving forward, and what we can do to stay ahead of the curve.
Among the questions we explored in the series: What is the future of AI? How is it transforming industries and organizations? How will AI affect the future of work? What role should it play in decision-making for leaders? And what are the best practices for leaders in applying generative AI with their teams?
In this blog post, I share some of my thoughts and key takeaways from the podcast episode with Wharton Professors Kartik Hosanagar and Stefano Puntoni, Faculty Co-Directors of AI at Wharton. I also touch on some related findings from GBK’s extensive new study on “The Rise of Generative AI Across Enterprises”, co-directed by Prof. Puntoni, and GBK President Jeremy Korst.
The rise of generative AI
As a Bayesian statistician and Vice Dean of Analytics at Wharton, I’ve had a front-row seat to see the rise of artificial intelligence and its growing impact on data science and other fields. Much of my career has focused on understanding customer behavior and improving statistical estimates applying better data and algorithmic models.
Traditionally AI and machine learning were used as a way to make predictions with data. Now with the rise of generative AI, we’re not only able to predict outcomes based on data but also use those predictions to innovate, develop ideas, and create novel solutions.
As my colleague Wharton Professor Kartik Hosanagar shared in our Wharton podcast, “People tend to underestimate the nature of exponential change. I’ve been working with GPT-2, GPT-3, the various models of this, and every year it changes by an order of magnitude.”
“Generative AI today can already match humans,” continued Hosanagar. “But human plus AI today beats both human alone and AI alone. For me, the big opportunity with generative AI is that we are going to see productivity boosts like we’ve never seen before in the history of humanity. And that kind of productivity boost allows us to outsource the grunt work to AI, and focus more on creative things, and derive joy from our work.”
GBK’s new study, based on a survey with 672 senior leaders from U.S. enterprises, each with annual sales surpassing $50 million, shows that generative AI adoption has reached a tipping point. Not only do the majority of enterprise leaders now use generative AI at work, leaders across functional areas also plan to increase spending on generative AI by 25% in the next 12 months.
THE RISE OF GENERATIVE AI ACROSS ENTERPRISES -> CLICK HERE TO GET THE FULL REPORT
“We were stunned by many of the findings of our study including the number of business leaders already using generative AI in their work and the widespread use cases” notes Prof. Puntoni. “This is not a technology that's ‘around the corner’. It's already here.”
“With generative AI, we are going to see productivity boosts like we’ve never seen before in the history of humanity. And that kind of productivity boost allows us to outsource the grunt work to AI, and focus more on creative things, and derive joy from our work.” - Wharton Professor Kartik Hosanagar
How will generative AI augment or replace human talent?
AI models are quickly becoming indispensable co-pilots in the workplace. In the next 3-5 years, senior leaders across functional areas agree that generative AI will be broadly used for generating data analysis (89%), marketing content and creation (text, images, video) (87%), as well as researching customer & competitive insights (84%). The use of generative AI in software development, particularly coding, was also cited as a top use case.
As Prof. Puntoni shared, “generative AI offers organizations the opportunity to help employees find more meaning in their work and creativity. The goal isn't about replacing humans or making them obsolete; it's about allowing humans to flourish.”
The results of GBK’s study echoed this sentiment. Senior leaders currently using the technology are more likely to state that generative AI will enhance employee skills versus replace them (48% vs. 36% strongly agree). Moreover, most enterprise leaders don’t believe generative AI can completely substitute human talent. It can, however, improve work quality.
The importance of human-AI collaboration
As we break down jobs into automatable tasks or those needing AI assistance – from data analysis and coding to content creation – we're rapidly progressing toward a future defined by seamless human and machine collaboration. But making this transition will be easier for some than others.
"Our brains fundamentally struggle with exponential change,” said Prof. Hosanagar. “But people need to recognize that change with generative AI is happening fast and start experimenting and learning. And people need to start upping their game and reskilling and get really good at using AI to do what they do. Reskilling is important.”
Recommendations for leaders using generative AI
As the impact of generative AI continues to grow, organizations also need to put the right guardrails in place to make sure they are harnessing the benefits of generative AI, while mitigating the risks. The first step is “adopting an intentional ‘test and learn’ approach, ensuring there is a method to the madness”.
“Every organization needs to develop learning processes and assign individuals the task of understanding AI's capabilities (and limitations) and how it will impact individuals, teams, and workflows,” continues Puntoni. “The focus should be on re-engineering ways of working that maximize human potential alongside AI."
“Every organization needs to develop learning processes and assign individuals the task of understanding AI's capabilities and how it will impact individuals, teams, and workflows.” - Wharton Professor Stefano Puntoni
Last, but not least, companies need to have a system in place for how they apply AI-generated output or data. As my colleague GBK President Jeremy Korst notes, “Generative AI, while revolutionary, is not immune to errors,” said Korst. “It's crucial for leaders to have strong quality control mechanisms in place to monitor and validate AI-generated output from data analysis to content. This not only ensures accuracy but helps to mitigate risks and maintain the integrity of the brand.”
Ultimately generative AI should be viewed as a decision-making support tool. AI can process vast amounts of data to inform decisions, but data quality still matters. It’s up to individual leaders and teams to understand the subtleties and value of the output.
For more insights on latest emerging trends with generative AI, I encourage you to check out GBK’s study, as well as the Wharton’s “AI in Focus” podcast series.