Shervin Khodabandeh, a BCG managing director and senior partner, and Sam Ransbotham, a professor of business analytics at Boston College and AI editor at MIT Sloan Management Review, are the cohosts of Me, Myself, and AI, a podcast that explores how experts in various fields are bringing innovation to life with AI.

Who would think the noise of a coffee machine could enhance automotive design?

That’s what happened at Porsche, where one AI developer built a sound recognition algorithm that could tell a cappuccino from an espresso—a technology that turned out to be perfect for fine-tuning car-door seals to prevent exterior noise.

At Delta Air Lines, a career-pathway program prepares flight attendants, baggage handlers, and other frontline workers for analytics roles within the company. Home Depot is using AI to help online customers choose the right items for their repair projects, while travel booking companies like Expedia and Airbnb are using AI to limit fraud and ensure the safety of travelers.

These are just a few of the stories we’ve covered on the Me, Myself, and AI podcast. Coproduced by BCG and MIT Sloan Management Review, the podcast—now wrapping up its eighth season—offers an episode-by-episode look at AI’s ongoing evolution. The experts we’ve interviewed, and the organizations they represent, aren’t just putting AI into services and workflows—they're redefining how companies create value with artificial intelligence.

Key Insights from AI Experts

Our guests have offered a wealth of guidance that can help leaders in any industry engage AI with confidence instead of uncertainty. Here are some of the common themes.

Learn from—and with—AI. Many guests have spoken about their deployment of powerful machine-learning solutions. But they’ve also emphasized the significant advantages created when humans and AI learn from each other, confirming similar findings from MIT Sloan Management Review and BCG. And learning itself can be an AI use case—as demonstrated by language training service Duolingo, which uses AI to create personalized curricula for customers. Elsewhere, LG Nova, a startup incubator at LG Electronics, is exploring the use of augmented reality in upskilling.

Commit to continuous improvement. Gina Chung, formerly a vice president of innovation at DHL and now vice president of corporate development at Locus Robotics, stressed that “the first day for AI is the worst day.” In other words, improvements will snowball. Consider an algorithm during the initial pilot phase: as it ingests more and more data while learning from workers, it becomes so accurate that those same workers soon embrace it as a core element of their jobs.

Experiment early and often. A spirit of experimentation, and even play, should guide your company’s AI efforts. When your people try out pilots and test deployments, they’ll find plenty of value—even in places where they didn’t expect the technology to offer advantage.

Once in the sandbox, developers will build algorithms and solutions that could turn out to be useful—and in more ways than one. “[Systems] are showing tremendous capacity to adapt themselves to novel circumstances,” said Capital One’s Prem Natarajan. “We can start using them in our pet projects and our enterprise-wide initiatives.”

Keep an open mind about AI. The podcast has highlighted some eye-opening, ambitious use cases. NASA’s Perseverance rover captures images of the Mars landscape with onboard AI technologies. UC Berkeley researchers analyze imaging and electronic health records to determine why some individuals get cancer and some don’t. Meanwhile, researchers at Harvard Business School and Microsoft are using large language models to simulate focus groups and provide marketers with an enhanced view of customer preferences across broad populations.

The bold use of AI technology doesn’t stop there; guests have described deploying AI to personalize services, fight fraud, and protect endangered species. Other potential GenAI use cases could bolster operations, research, HR, marketing, and product development.

Like Porsche’s use of sound algorithms in car design, the link between AI and a task isn’t always obvious. But keeping an open mind about what’s possible with the technology can lead to unexpected results. Take Jumpcut, an entertainment-industry startup, which deploys AI technology to help film and television producers identify scripts with the potential to resonate with large audiences—and in the process gives fresh, diverse voices a better chance of breaking through in Hollywood.

Make the most of human-AI collaboration. A person working without AI isn’t as effective as they could be, and AI’s capabilities often fall short without human guidance. But an organization can flourish when the two elements are joined. Research by BCG and MIT Sloan Management Review found that when AI is in place, workers are happier and collaborate more effectively—a link the podcast frequently examines.

Aflac uses AI to handle routine insurance claims, freeing its staff to focus on serving customers with more complex claims. Intel, meanwhile, is exploring the very nature of human-AI collaboration, with a social sciences department that interviews the company’s technicians about their experiences using AI to learn how to make the technology more helpful.

While many leaders are starting to prioritize human-AI collaboration for greater efficiency, they must also make this union systematic and ongoing. Create multiple ways for people and AI to interact regularly—as LinkedIn does, flexing its “collaboration muscle” by frequently having different teams and functions work together to make the most of data and AI solutions.

Prepare your talent for AI. People drive the effort to reshape functions and create new business models with AI. Their technical abilities must fit the task, but recruiting the perfect candidate with the perfect skill set can’t be the sole objective of an AI talent management strategy. You don’t need an AI unicorn, as Colin Lenaghan of PepsiCo pointed out; instead, organizations should bring people with different skills together.

But engaging AI to the fullest takes more than technical skills. Curiosity and a collaborative mindset are just as important. When it comes to finding employees who work well with AI, Amit Shah, a board member at Blue Apron and formerly the president of 1-800-FLOWERS, told us that he emphasizes a learning quotient, a capacity to adapt to new conditions. Staff with this capacity are well-equipped to ask questions that go beyond functional competency and probe the ethical and strategic implications of the technology.

For leaders, developing the AI expert of the future means breaking away from traditional ways of thinking. Don’t box people in, because talent can come from anywhere—as our ensemble of podcast guests makes clear.

Address risk and trust with responsible AI. Deploying AI is not only about optimizing workflows. Users of AI face the risks of misuse, bias, abuse, and ethical challenges. The importance of implementing responsible AI principles and guidelines has been a constant theme of the podcast, and our guests are applying those principles to help their organizations manage a spectrum of potential threats.

Instagram uses machine learning and advanced analytics to assess the sentiment of user conversations, the tone of posts and interactions, and the content within images—countermeasures that help safeguard users from offensive content that other technologies might miss. Expedia focuses on preventing fraud and abuse of trust, which impacts the safety of all travelers; in one year alone, the company saved over $2 billion by identifying and blocking fraud attempts. Another travel company, Airbnb, regularly gathers disparate teams focused on data privacy, information security, antidiscrimination, and trust to discuss AI risks.

Use AI for good. You need to manage AI’s risk to boost revenue and find efficiency. But the obligations—and benefits—don’t end there. You can also achieve wider societal benefits when you engage the technology. For example, Instagram’s AI-fueled social media platforms give us troves of data on issues like teen literacy—data that we’ve never had access to before, let alone analyzed.

Guest Damini Satija of Amnesty International spoke of democratizing access to technology, envisioning an ideal future “where we’re able to give power to those who typically have not had a voice in what technologies are developed—and how [the technologies] are used to their benefit.”

“We really have to think globally about how AI is deployed on behalf of humans and what makes us human,” said Kay Firth-Butterfield, formerly head of AI at the World Economic Forum. “And where we want to be maybe in 15 or 20 years, when AI can do a lot of the things that we are doing currently.”

---

Over eight seasons, Me, Myself, and AI has covered the many ways that humans and AI are evolving together. But it always comes back to people. Diverse, energized, open-minded professionals who have made technology innovation their career are at the forefront of society’s use of AI. Leaders everywhere can follow their example and innovate with bold new AI implementations that elevate human potential.

Subscribe to our Artificial Intelligence E-Alert.

Subscribe

Click to Manage Your Subscriptions.