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Update introduction to: We brought together CEOs from a range of consumer industries, including retail and publishing, to hear how their organizations were actively piloting, adopting, and implementing AI technology. Here is what we learned.
Three key takeaways from our conversation with CEOs whose organizations are actively piloting, adopting, and implementing AI technology.
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CEOs need to orchestrate organized chaos in AI experimentation |
Focusing on growth, not efficiencies, can help avoid a culture of fear around AI |
CEOs can’t delegate AI to the Chief Digital Officer; they need to lead the charge |
Because AI is changing so incredibly quickly, the people element of AI is potentially even more important than the technology.”
CEO attendee
RRA x HBS AI CEO Labs
How CEOs in consumer industries are adopting AI
To achieve customer personalization at scale. CEOs stressed the importance of using AI to provide more tailored interactions with consumers. One shared: “Five years down the road, the ones who win in this industry will be those who master the consumer journey and do personalization at scale—and AI is the biggest enabler for that.” Another CEO in the hospitality sector shared how they were planning to use AI to offer personalized member experiences.
To drive creativity. CEOs are also using AI to drive creativity and innovation across R&D and Marketing and Sales. One said: “We’ve seen incredible improvements in how fast and creative our design team can be using GenAI.” Another added: “Marketing and content is relatively low-hanging fruit when it come to AI adoption. That’s happening in real-time across a lot of organizations.”
To avoid radical disruption. Many attendees shared the risk of being radically disrupted, outperformed, or falling behind the competition. “The number one risk is being out innovated,” one CEO shared. Another added: “Our sense is that if we don't go really, really quickly, either our current competitors will do it or somebody else using the foundation models will outpace us. So, we're looking at almost every touch point of our company.
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 whose organizations are actively adopting AI
Our attendees shared the opportunities, challenges, and lessons they had faced when implementing AI across their organizations.
Lesson 1: The role of the CEO is to orchestrate organized chaos in AI experimentation
CEOs spoke about the importance of unleashing a culture of experimentation across the business.
One CEO shared how the pace of change was so fast that CEOs often “don’t have time to reflect on how they’re going to [adopt AI].” They said: “We just jumped in.” They added that after a year of experimentation, they were now looking at how to scale AI implementation. The company is currently working with multiple technology platforms, including ChatGPT and start-ups, as well as their own models. “We want to be first to market, we want to make progress, but we're also starting to think through how we build it,” they said. Key to this is sharing best practices, with the CEO sharing how they regularly exchanged notes with another divisional CEO across the company about what was working and what was not. But they acknowledged: “This all sounds organized when I talk about it, but it's not at all—it’s chaotic.”
Tuck Rickards, leadership advisor at Russell Reynolds Associates, shared how this was a common theme among many CEO conversations: “We’re hearing this concept of organized chaos, where you're unleashing experimentation, but the CEOs will organize the chaos,” he said.
Another CEO shared that while it can be overwhelming to know where to start, focusing on critical business priorities and small wins can help build confidence around. “You can apply AI basically anywhere in your business, but it makes sense to think strategically about your main business priorities for the next five years and your key pain points,” they said. “Start with a few things that are very simple and say, ‘Let’s try to have impact within two weeks.’ Then, we’ll do a few things that might take us two or three months, and then we’ll start to build more difficult things because that creates momentum.”
The 30 Percent 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 2: CEOs need to avoid creating a culture of fear around AI across their organizations
The group talked about the importance of adopting a people-first approach to AI. “We believe that because AI is changing so incredibly quickly, the people element of AI is potentially even more important than the technology,” they said. The CEO added that AI needs to be driven both top down, and bottom up, stressing the importance of not just educating and upskilling the C-suite team but also frontline employees. The goal is to ensure the C-suite understands the art of the possible (and impossible) as well as the risks—and to generate a culture of agility across the organization. “The reality is that if you start with a few small projects with the right partners, and you have a few people who are passionate about AI in your organization and become super users, you can get a very long way,” they said. “There is so much fear about AI that transformation needs to be 30% about the technology and 70% about culture.”
Other CEOs shared how they were training their workforces on AI, including asking super users to share their best practices with other teams. “The early adopters have created training videos and running sessions, rolling out their experiences to our 9,000 employees to see what other ways they can use AI to enhance our internal processes.”
Another CEO shared how they were also training all employees on AI, but added: “We are not thinking we’re going to win or lose based on productivity gains. We’ve really been focused on shipping value,” they said. Another agreed, adding that: “Before we do any cost savings, let’s focus on growth, and very visible AI applications that employees will like and benefit from. Otherwise, you just create this huge fear around AI.”
The Four Types of Employee Responses to 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.
Lesson 3: CEOs can’t delegate AI to the Chief Digital Officer; they need to lead the charge
There was agreement that AI was “everyone’s problem,” but responsibility started at the top, with the CEO. There was also discussion about the benefits of CEOs getting their hands dirty with AI to truly understand its potential and keep pace with the scale of development. As one attendee shared: “I always stay really close to the to the engineers because I know that's the frontier of what's happening. Tahey had been telling me for some time to watch the development of language models, so they were on my radar screen, but I’d never used it. And then once I did in December 2022, I was absolutely struck from the moment I typed my first prompt. Then I bought two accounts and reorganized the whole company. We’re still scrambling just to keep up with how fast things are moving.” And, as another CEO said, “The CEO needs to personally be close to the builders of AI; I’d put that high on the ‘to-do’ list priorities.”
RRA’s Tuck Rickards added: “The recommendation would be, from all of our conversations, is to build a CEO AI Cabinet made up of internal and external stakeholders to both enable the business, but also to experiment and listen and learn,” he said. “A lot of the feedback from the group is that you can't delegate this to a Chief Digital Officer, the CEO of a business needs to own the legacy of the business model and the legacy of the team.”
Changing remits and ways of working of leadership was also a hot discussion with “expectations of the leadership team [based] more around increased rate of learning, than core skillset change”. Some attendees had plans for structural change, with product and technology being pushed closer together, and “a much stronger integration of all consumer-facing departments—with Sales, Digital, Marketing, and Technology need to be a much more coherent leadership sitting under one leader or division so it’s working in a connected, agile way.”