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We brought together CEOs from a range of geographies and industries, including financial services, media, IT software and services, and biopharmaceuticals, to hear how they were actively piloting, adopting, and implementing AI technology. Here is what we learned.
Three key takeaways from our conversation with CEOs who are actively piloting, adopting, and implementing AI technology.
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It’s important for CEOs to fully lean into AI transformation. |
CEOs need to work to address knowledge gaps and adopt a learning mindset. |
Tech transformations typically fail at the frontline, so managing AI resistance is key. |
My entry point to transformation is always culture. Organizational change can be made within five minutes on a piece of paper. Cultural change takes longer and is the most difficult thing to get right, but it’s critical to success.”
CEO attendee
RRA x HBS AI CEO Labs
How CEOs are adopting AI
01. To create efficiencies. CEOs shared how they were using AI to execute mundane tasks and drive efficiencies. One said, “Many of our employees do a lot of processing, a lot of typing, and inputting, which we know they don’t like to do. So, figuring out how to use AI on these tasks is the first thing we’re looking at.” RRA’s Chief Digital and Data Analytics Officer, Harpreet Khurana, added, “The more CEOs can take busy work and automate it, the more they can focus on the EQ work.”
02. To future-proof their organizations. CEOs shared how disruption was the biggest risk of AI. “It’s no different to Internet or Mobile—you can be doing great with today’s technology but if somebody comes along with new technologies you face the risk of disruption,” they said. “If you don’t embrace AI, you’re going with your own risk.” Another CEO added: “Our CRM is going to be completely redefined in the next five years… so we’re going to get disrupted if we don’t stay on top of the curve.”
Where AI thrives—and stumbles
In 2023, Karim Lakhani, a professor at Harvard Business School, launched a joint research study with Boston Consulting Group that looked at whether AI could tangibly improve the productivity and efficiency of elite knowledge workers. The study of 758 BCG consultants found that:
- Consultants who used AI were 25% faster and completed 12% more tasks than those who weren’t using AI tools. The impact wasn’t just felt from a speed perspective—the study also found that 40% of the group using AI also yielded higher-quality results.
- Consultants who were deemed below-average performers benefited most from AI augmentation—with an increase of 43% in performance. However, above-average performers also noticed a 17% boost in performance by using AI.
- There was a fall in performance when it came to using AI to complete complex tasks, such as the triangulation of financial data in a spreadsheet that contained errors or analyzing a retail strategy using interview notes. In these scenarios, consultants were 20 percentage points less likely to produce correct solutions compared to those who were not using AI.
Key lessons from CEOs actively adopting AI
Our attendees shared the opportunities, challenges, and lessons they had faced when implementing AI across their organizations.
Lesson 1: AI transformation requires radical, not incremental, change
While some CEOs said they didn’t want to move too fast on AI—because “the organization isn’t ready, neither are leaders, and neither are employees”—others were mindful that there was little time to waste.
One CEO shared how they had moved fast on AI after previous digital investments hadn’t always paid off, advocating the importance of ensuring “there was an appetite to fully lean into AI.” They said: “We didn’t have digital infrastructure or a data pool, so we had to make decisions about how to increase the capability of that function. We also needed to paint a picture to the employees about what was going to happen to the market and why we had to move with it. We find that if we tell people the why and the what, you get much better results. You’ve got to bring everyone along.”
Some CEOs are working with external partners to spur change and accelerate action. One had recently worked with consultants to rethink their governance structures but added that it was hard to find the right partners. “We are inundated with tech sales calls each day,” they said. Another CEO, who aims to use AI to speed up productivity and workflows, added that they had chosen to work with ecosystem partners, explaining, “We are trying to select the AI solutions that will help us best, then embed them in our systems. It’s a total waste of time to level up ourselves instead of working with the best and most relevant partners.”
The AI Factory
An excerpt from Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World by Marco Iansiti and Karim R. Lakhani.
The AI factory is the scalable decision engine that powers the digital operating model of the twenty-first-century firm. Managerial decisions are increasingly embedded in software, which digitizes many processes that have traditionally been carried out by employees. No human auctioneer gets involved in the millions of daily search-ad auctions at Google or Baidu. Dispatchers do not decide which car is chosen on DiDi, Grab, Lyft, or Uber. Sports retailers do not set daily prices on golf apparel at Amazon. Bankers do not approve every loan at Ant Financial.
Instead, these processes are digitized and enabled by an AI factory that treats decision making as an industrial process.
Analytics systematically convert internal and external data into predictions, insights, and choices, which in turn guide or even automate a variety of operational actions. This is what enables the superior scale, scope, and learning capacity of the digital firm.
Lesson 2: CEOs need to work to address knowledge gaps and adopt a learning mindset
Attendees also discussed the specific role CEOs can play in driving transformation—and how there was a need for CEOs to upskill on the AI conversation if they are to drive adoption and implementation across their organizations. As Marco Iansiti and Karim R. Lakhani share in their book: “[Transformation] starts at the top, with motivating and grooming a generation of leaders to do the hard work involved … A better collective outcome hinges on each enterprise and its management team doing its part. No organization should be standing still.”
Attendees went on to discuss how pilots and experiments were critical to better understanding the potential of AI. As one CEO shared: “We make the greatest leaps when we run innovation experiments. It’s hard to get tech fluency as a CEO when you have a day job, but it helps greatly if there’s a experiment going on and the organization is learning from that.”
The group also discussed how CEOs can draw on the knowledge and resources of other teams further down the organization. It was felt important for CEOs to spend significant time with teams three levels down in their organizations to get updates on what’s going on with AI, creating deadlines on critical AI projects, getting their hands dirty, and understanding the issues to drive change in the organization. As one CEO made clear: “You can’t look at AI from a C-suite level altitude. You have to really get into the details, so working three levels down is super critical. You can’t just CEO this thing.”
The 30% Rule
An excerpt from The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI by Paul Leonardi and Tsedal Neeley.
A digital mindset is the set of approaches we use to make sense of, and make use of, data and technology. This set of attitudes and behaviors enable people and organizations to see new possibilities and chart a path for the future.
And here’s the good news: you only need about 30 percent fluency in a handful of technical topics to develop your digital mindset. We call this the 30 percent rule.
To understand the 30 percent rule, think about learning a foreign language. To demonstrate mastery of the English language, a nonnative speaker must acquire roughly 12,000 vocabulary words. But to be able to communicate and interact effectively with other people in the workplace, all they need is about 3,500 to 4,000 words—about 30 percent of what it takes to achieve mastery.
In practical terms, a nonnative speaker does not need to master the English language to work effectively with others. Similarly, to work effectively with a digital mindset, you don’t need to master coding or become a data scientist. But you do need to understand what computer programmers and data scientists do, and to have proficient understanding of how machine learning works, how to make use of A/B tests, how to interpret statistical models, and how to get an AI-based chatbot to do what you need it to do.
Lesson 3: Tech transformations typically fail at the front line
The CEOs were clear that cultural change is one of the biggest levers CEOs have to accelerate successful AI adoption and implementation. One said: “My entry point to transformation is always culture. Organizational change can be made within five minutes on a piece of paper. Cultural change takes longer and is the most difficult thing to get right, but it’s critical to success.”
CEOs discussed how, despite the benefits of AI to productivity, efficiency, and creativity, workforce resistance can be high. Success factors included creating a culture where innovation can flourish, and also bringing everyone along on the journey.
As Paul Leonardi and Tsedal Neeley wrote in their book, “Without widespread buy-in from employees, any major change initiative will wither and die. That’s why the first step in a successful effort is to explain the benefits of digital change to the workforce.
It shared an example of one company that was pushing forward with digital transformation where 40% of potential users decided not to use the technology, even though it was mandated by their direct supervisor. “That’s a big number—big enough, in fact, to derail a digital transformation,” they wrote.
The Four Types of Employee Responses with Digital Transformation
An excerpt from The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI by Paul Leonardi and Tsedal Neeley.
We recommend a deceptively simple adoption framework that we have used to help leaders at many companies to influence people’s behaviors so that they are motivated to engage with a change program that requires learning new skills:
Do I have buy-in such that people believe digital transformation will be beneficial for them and the organization? And can I learn what I need to in order to succeed in this transformed organization?
Mapping the answers to these two questions produces four types of responses you’ll typically see and suggests what you need to do to make transformation successful.
The good news is that leaders and managers can move individuals from one quadrant to another.
To shift people from oppressed or indifferent to inspired, you first must increase buy-in by helping everyone believe that learning digital competencies is good for them and their organization.
Three factors are crucial to promote buy-in:
- Increase messaging from leadership that stresses the importance of digital transformation as a new and critical frontier for the company.
- Launch internal marketing campaigns to help employees imagine the positive potential of a company powered by digital technology.
- Promote a shift in people’s identities; that is, encourage people to view themselves as contributing members of a digital organization.
After establishing buy-in, leaders can shift individuals from frustrated to inspired by boosting confidence in their capacity. Three factors contribute to people’s confidence in learning digital skills:
- People’s past experience with digital technologies—whether it was through education, employment, or work—tends to give them the confidence they need to succeed in this task.
- Vicarious experiences of others, including peers and managers, influences beliefs in one’s own capabilities.
- Persuasion and encouragement from managers and executives promotes confidence in employees.