I co-chaired the inaugural Fortune Brainstorm AI conference held in early November 2021 in Boston. The majority of the 150 C-level executives in attendance were heads of artificial intelligence (AI) or data for Fortune Global 500 companies, including executives from Amazon, Spotify, Unity, Kellogg’s, Mastercard and Stanley Black & Decker. AI luminaries such as Andrew Ng and Andrew Moore presented as well Noubar Afeyan, Moderna Co-founder, and Lynne Parker, Ph.D., Head of the U.S. AI initiative at the White House.
I had the pleasure of moderating several sessions on ethics and responsible AI, autonomous vehicles, and AI in the global marketplace with knowledge experts, including Margaret Mitchell, Ph.D., Chief Ethics Scientist at Hugging Face and formerly co-lead of the AI ethics team at Google, Freedom Dumlao, CTO of Zipcar, and Alok Gupta, Head of Data Science and Machine Learning at DoorDash among others.
— Rana El Kaliouby, Co-Founder & CEO of Affectiva share
For starters, it was clear that AI is inevitable. According to research done by Accenture, companies using AI to run their business generated five times more revenue than companies who are not using AI. And this applies across industries. To put this in context, 20 years ago companies debated whether they should be on the web. In retrospect, that seems like such a dumb debate. Of course, every company needed to be on the web, and those that weren’t, didn’t survive or scale. Similarly, in 10 years, we will look back and the companies that didn’t embrace AI will be behind or worse — become obsolete.
Nonetheless, for business leaders who are not domain experts in artificial intelligence, it may be unclear what value AI can bring and starting on that journey may be daunting. Here are 7 ways executives and business leaders can future proof their organizations with artificial intelligence:
1. Make AI a company-wide mandate
One thing was clear — companies that are leading in applying AI in their businesses had CEO and executive sponsorship. CEOs of the Global Fortune 500 clearly made investing in AI a priority and in many cases, the executive responsible for defining and implementing the AI roadmap reported directly to the CEO.
2. Invest in re-skilling
Invest in educating your team on AI and how it can potentially apply to your business. Executive sponsorship is one thing, but I found it interesting that change management and the challenges of getting the rest of the organization on board came up in every panel. Companies such as Levi Strauss and PepsiCo have company-wide programs where employees can take educational courses to become AI-savvy. I love that!
3. Empower your team to find low-hanging opportunities
Give your team permission to experiment with AI technologies and engage in proof of concepts or low-hanging opportunities to improve or even reimagine some aspect of your business from process automation to engaging with customers in novel ways.
4. Invest in data and an AI infrastructure
Danny Lange, EVP and head of AI at Unity (formerly head of AI at Amazon and Uber) shared how Unity’s CEO hired him specifically to build an AI infrastructure across the company, expanding its revenue and product reach. While not every organization is able to invest and go all in the way Unity did, there was a strong case made to ensure every corner of the organization can take advantage of AI capabilities.
5. Have a data strategy
I heard a lot of debate on what offers a competitive moat: is it the data you own about your customers or the AI models?My point of view is that data is certainly a moat. Getting the right data is incredibly difficult and expensive. But of course, just hoarding data isn’t enough — one has to think of unique ways to learn from and apply insights from the data, and this is where AI can be a differentiator.
6. Treat ethics as a business imperative
I have noticed a shift in the dialogue around AI ethics and governance. A few years ago, most of the conversation centered around high-level principles of AI ethics, such as fairness or accountability. The conversation is now much more pragmatic, focused on how a company should reduce these ethics principles to practice, e.g., mitigating data bias or respecting user privacy in products.
7. Human first
I may be biased, but I was pleased to see the topic of human-centric AI come up in many of the panels – from making your Alexa and Spotify more intuitive, implementing cabin monitoring in robo taxis, to building collaborative robots that work alongside humans, whether it’s on factory floors or in your kitchen! Any AI that interacts so closely with people will need to have some form of human insight AI.
Based on the thought-provoking discussions, clearly this collective collaboration and brainstorm unlocked a real need and pain point for executives. I am excited to see how we take this forward.
