Welcome to our 2021 Europe and US Data, Analytics, and Artificial Intelligence Executive Organization and Compensation Survey, which examines both organizational structure and compensation for executive roles with artificial intelligence and/or data analytics responsibilities.

For this report, Heidrick & Struggles compiled compensation data from a survey fielded in Fall 2021 of 179 executives in predominantly Europe and the United States. The executives who responded to the survey came predominantly from the United States. Several Western European countries were also well represented, particularly the United Kingdom. More than half of the roles represented were at companies with an annual revenue of $5 billion or more. (See charts, “Respondent locations and company information,” on page 4 of the full report.)

What titles do data, analytics, and artificial intelligence leaders have, and what are their backgrounds?

Data, analytics, and artificial intelligence responsibilities are led by people in roles that include chief data and analytics officer, chief data scientist, and head of machine learning or artificial intelligence.

In terms of experience, data, analytics, and artificial intelligence leaders most often had experience in financial services and consumer, retail, and media (the same industries they most often work in today). Across Europe and the United States, financial services was the most common source of experience. However, consumer, retail, and media came second in the United States, at 42%. Technology and telecoms was second in Europe, at 38%, compared to 33% in the United States. (For the full regional breakdown, see chart, “Sector experience,” on page 5 of the full report.)

Role (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 179

Notably, more than half of the executives we surveyed, 52%, have been in their role for less than three years, and nearly three-quarters, 74%, are in a role that has existed at their company less than five years. Longevity in a role could suggest a few different things, a high level of turnover, perhaps, or a change in strategic priorities resulting in demand for a first-time executive leader responsible for the function, moving the responsibility from a manager or director.

Time in current role (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 179

Time role existed at company (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 179

Demographics

The data, analytics, and artificial intelligence function is historically one that has been lacking in diversity, though we have observed a number of initiatives to introduce greater diversity in terms of gender, race and ethnicity, and sexual orientation. The majority (65%) of data scientists in the United States are men.¹ The ethnicity statistics are even less promising: in the United States, Black professionals represent just 5% of the tech workforce and 3% of tech executives.²

Most respondents to this survey were male and white, although the executives who responded in the United States are markedly more diverse than those in Europe. While the share of non-white executives was 45% in the United States (with Asian and Asian Americans the most well-represented, at 33%), the share of non-white executives was only 19% in Europe. The share of women in these roles, while low everywhere, was in the United States double that of those in Europe. (For a full breakdown of the demographics by region, see pages 7 and 8 of the full report.)

Ethnicity (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 179

Gender (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 179

What data, analytics, and artificial intelligence executives do all day

Most of the executives who responded to our survey, 66%, were in global leadership roles (77% in Europe and 56% in the United States). The regional difference may be because the US economy is larger than European economies; it may be that far more countries headquartered in Europe have more global operations than those in the United States. (For more, see chart “Role remit” on page 9 of the full report.)

Executives in data, analytics, and artificial intelligence roles said that they work most often with the marketing and customer engagement functions, followed by operations and sales/go-to-market. This held true across Europe and the United States. Most executives reported teams of 25 people or fewer, though in the United States there was a wider variety of team sizes, ranging from 1 to more than 200. (For more, see charts “Team background” on pages 9 and 10 of the full report.)

While the large majority of data analytics and AI leaders are responsible for data science, artificial intelligence and machine learning, business intelligence, and analytics functions, reporting structures often dictate additional functional responsibilities.

We can speculate that data architecture, platform, and warehousing roles more likely sit in the core IT organization. If the data analytics leader sits in the business, those functions sit elsewhere. If instead, they report to technology, it’s more likely they have ownership for these technical functions.

No matter who the data, analytics, and artificial intelligence executives report to, the large majority of them are responsible for data science, artificial intelligence and machine learning, and business intelligence and analytics. We begin to see some variation in reporting lines when it comes to data governance and data privacy—more of the executives who report to the chief operating officer or chief administrative officer are responsible for those functional areas, while the executives responsible for data warehousing are more evenly split between the CFO, COO or chief administrative officer, and the chief information officer in terms of who they more often report to. The executives responsible for data platforms far more often report to the chief information officer, while those responsible for data architecture more often respond to the CFO, followed by the COO, or chief administrative officer.

In both regions, the United States and Europe, companies recognize a competitive advantage by building up top-notch AI organizations that enable them to have the right access and use of data. (For more, see chart, “Which functional areas report to you,” on page 11 of the full report.)

Globally, data, analytics, and artificial intelligence executives most often report to the CEO. However, there is a notable regional variance. In the United States, they most often report to the CTO or senior engineering executive, followed by the CEO and then the CIO. In Europe, the CEO was followed by the COO or chief administrative officer. This difference in reporting lines could be related to the function being relatively new in Europe, whereas it is more established in the United States.

That means that in the United States, data ownership has historically sat in the technology function, and it is still slowly moving out of IT and into the business, as CEOs and boards increase their focus on the importance of data and analytics. In Europe, with stronger regulations about the use of data, as well as less historic time with the role, it appears that data leadership roles have been integrated into the business faster than those in the United States. (For more, see charts “To whom do you report?” and “Functions that report to them by who they report to,” on pages 12 and 13 of the full report.)

Data, analytics, and artificial intelligence compensation: A brief global comparison

Reported median cash compensation for data, analytics, and artificial intelligence roles in Europe was $409,000. In the United States, it was $546,000. Median total compensation, including any annualized equity grants, was $616,000 in Europe and $914,000 in the United States.

The data leadership role seems to be valued more in the United States, both from a cash perspective and an equity perspective—only 17% of respondents reported receiving some form of sign-on equity in Europe. As European companies continue to seek global talent, especially from the United States, greater consideration needs to be given to granting equity as part of the overall compensation package.

In terms of equity, 34% of executives received annual equity in the form of restricted stock units (RSUs)—30% did so in Europe and 38% did in the United States.

Equity form overall: Annual equity (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 169

Equity form overall: Sign-on equity (%)

Source: Europe and US artificial intelligence and data analytics executive organization and compensation survey, 2021, n = 116

In the United States, 58% of executives received sign-on equity in the form of RSUs, performance share units (PSUs), or a combination of both, while the figure was only 17% in Europe. (See charts “Equity form: Europe” and “Equity form: United States” for full annual equity breakdown and pages 18 and 21 of the report for full sign-on equity data by region.)

Format of sign-on equity

By industry, there was a significant difference in compensation between Europe and the United States.

Across Europe, the industries with the highest total compensation were financial services, consumer, and industrial, respectively, with those in financial services receiving a median total compensation of $721,000. In the United States, the industries with the highest total compensation were technology, healthcare and life sciences, and consumer, respectively, with those in technology receiving a median total compensation of $1,201,000.

For the breakdown of data, analytics, and artificial intelligence executives’ compensation in Europe, see pages 16–18 of the full report.

For the breakdown of data, analytics, and artificial intelligence executives’ compensation in the United States, see pages 19–21 of the full report.

About the authors

Ryan Bulkoski (rbulkoski@heidrick.com) is a partner in Heidrick & Struggles’ San Francisco office and the global head of the Data, Analytics & Artificial Intelligence Practice.

Kristin van der Sande (kvandersande@heidrick.com) is a partner in the Frankfurt office and a member of the Global Technology & Services Practice.

References

¹  “Data scientist statistics by gender,” Zippia, September 9, 2021.

²  “The Black technology workforce: Designing a more inclusive future,” The Kapor Center, February 2021.