Designing the C-suite for generative AI adoption
As gen AI adoption evolves, technical and regulatory skills are now often table stakes for the C-suite. How can organizations equip leaders with the skills to navigate new AI demands?
Brenna Sniderman
Aditya Narayan
Timothy Murphy
Natasha Buckley
Deloitte’s recent examination of the evolution of C-suite skills, “How the drive for data, technology, and financial skills is reshaping the chief strategy role,“ explores how skills requirements for chief strategy officers are shifting to more quantitative backgrounds in research, analytics, and finance. But this shift in skills requirements is not just limited to strategy roles, according to our analysis of more than 46,000 job postings (see Methodology). We also observed the elevated importance of a strong quantitative background and the ability to navigate risk and regulatory environments for almost every role in the C-suite.
This shift in skill focus aligns with the ongoing impact that technological advances are having on business models. Nearly 90% of respondents to the World Economic Forum’s 2025 Future of jobs report expect AI and information processing technologies to drive business transformation in the next five years.1 As the potential grows for emerging technologies—including generative AI—to transform business operations and strategy, companies appear to recognize the need for their C-suite to possess increased levels of technical and regulatory understanding.
The skills gap and barriers to gen AI adoption
The race to embed gen AI across the enterprise is only gaining speed. According to unpublished data from Deloitte’s first quarter 2024 State of Generative AI in the Enterprise survey, 66% of leaders surveyed said they expect the technology to transform their industry in the next three years.2 In the fourth quarter survey results, 73% of leaders surveyed said they expect the technology to transform their industry in the next three years. Further, 24% of leaders in the fourth quarter survey said they have allocated 40% or more of their AI budget for gen AI.3
However, the increased investment and urgency to realize value are not without challenges. In Deloitte’s fourth quarter 2024 State of Generative AI in the Enterprise report, leaders surveyed suggested the biggest barriers to deploying their gen AI initiatives are driven broadly by three challenges: regulation and risk management, lack of technical talent, and lack of a governance model (figure 1).
These challenges demonstrate that organizations are working to understand gen AI as it evolves rapidly. Further compounding the issue, governments and regulators around the world are also trying to understand its implications. Regulations—what will be regulated, to what extent, and when—thus remain unclear, making it challenging for organizations to plan their strategies accordingly. This may be one of the reasons why regulatory compliance has emerged as a top barrier to gen AI adoption.
Upskilling the C-suite
Our analysis of job postings, which included chief operating officers, chief information officers, chief financial officers, chief human resource officers, chief strategy officers, and chief revenue officers, shows that organizations are already shifting their hiring strategies to help address these common barriers to gen AI adoption. They are seeking executives with the experience to help them better manage regulatory risks and are looking for C-suite leaders who possess deeper technical skills to support the complex governance and technical needs of gen AI adoption (figure 2).
An increased need for regulatory and compliance skills
Our research found that job postings requiring regulatory and legal skills across all six C-suite roles increased by more than one-third between 2018 and 2023. Demand for risk management backgrounds is also on the rise. In 2018, 16% of CFO role postings included risk management in the description; by 2023, 24% of the postings included risk management (a 50% increase). For CFOs, using gen AI to analyze highly sensitive financial data comes with a set of risks that finance leaders will need to weigh when considering finance-related use cases. This can include confirming that personal data used to inform the models adheres to privacy regulations and that the outputs of any of these tools are reliable, accurate, and, when necessary, explainable (for an audit, as an example).
Similarly, as conversations around the interaction between gen AI and talent management continue to grow, CHRO role postings have seen labor compliance skills double over the same six-year period (from 9% in 2018 to 18% in 2023). For talent leaders who are increasingly managing a blended human and AI workforce, many will need to understand what types of machine-human dynamics are compliant with labor laws, as some unions and trades negotiate how gen AI can acceptably integrate with their work.4
Technical skills as a universal requirement
Technical skills are also increasingly expected for leaders, as each C-suite role analyzed in our study required greater representation of skills pertaining to data, analysis, and research. For instance, a call for greater general science and research backgrounds increased by 55%, on average, across the six executive roles, from 11% to 17%. More specifically, CHRO role postings went from 5% of postings including data analysis in 2018 to 15% in 2023; and chief revenue officer postings saw business intelligence backgrounds grow from 4% to 12% in the same period. The impact of technologies like gen AI on a broad range of enterprise use cases is becoming increasingly evident. Research indicates a strong relationship between high levels of quantitative expertise and the successful integration of AI solutions. These solutions are particularly prominent in areas such as marketing, sales, customer service, and product development.5
In examining each of these areas, a more complete picture begins to emerge. Organizations are increasingly seeking to bolster their C-suite with quantitative skills that can equip leaders with a greater understanding—and ability to implement—more advanced technical expertise in the organization. This ability is likely critical for instilling greater gen AI talent and governance across the enterprise.
Infusing the C-suite with new capabilities
Equipping the C-suite with skills to overcome the common challenges to implementing new gen AI initiatives will most likely require a multifaceted approach. In that spirit, leaders can consider the following approaches to help the C-suite build the skills they need to help drive gen AI adoption:
- Invest in programs—and time—to upskill the C-suite. While it may sound obvious that leaders need to gain greater fluency in tech and regulations, time and day-to-day fire drills can limit leadership teams from making progress unless they intentionally commit through formal initiatives. A number of technology companies are already taking steps to address this. For example, one global professional services firm announced plans to enroll as many as 85% of its senior leaders in core artificial intelligence and applied AI leadership programs by the end of 2024.6 One software provider developed an AI Adoption Accelerator Program under which its leaders can learn about mindset, practical skills and engineering for innovation. The program also conducts various in-person AI boot camps for the company’s leaders.7
- Gain a greater grasp on regulation with AI. Just as AI can improve operations and enhance end products, it can also offer a sharper and more dynamic perspective on planning. This is often true when navigating the potential impacts of regulation and risk. Some companies are already leveraging scenario planning solutions to foresee how regulations might affect their strategy. With gen AI tools, decision-makers can experiment with different initiatives, predicting their success based on various factors like cyber laws, proposed regulations, workforce makeup, and data security standards.
As organizations embark on their journey of adopting gen AI, it’s important to understand—and build—the evolving skills C-suite leaders need to steer their organization toward effective gen AI adoption and ultimately gain a competitive advantage.
Research methodology
To understand how organizations are pursuing executive talent, we analyzed publicly available job postings that cover an array of industries in both the public and private sector (60 unique industries represented).
To benchmark what these roles looked like prior to the pandemic, we opened our sample to include postings from 2018 to 2023 (the last full year of data).
Finally, we leveraged a skills and backgrounds taxonomy (more than 32,000 different skills categorizations represented within the database) to see which types of expertise were most often pursued (for example, experience with managing budgets would be categorized as “budget management”). All taxonomies and analyses leveraged the Lightcast Open Skills Taxonomy database.
