The 2021 Europe and US Data, Analytics, and Artificial Intelligence Executive Organisation and Compensation Survey, conducted by Heidrick & Struggles, examines both organisational structure and compensation for executive roles with artificial intelligence (AI) and/or data analytics responsibilities.
Data, analytics and AI responsibilities are led by executives in roles that include Chief Data and Analytics Officer, Chief Data Scientist and Head of Machine Learning/Artificial Intelligence.
Looking specifically at data leadership roles, these are valued more in the US from a cash perspective. Additionally, greater consideration needs to be given to granting equity as part of an overall compensation package, as European companies continue to seek global talent, especially from the US.
The survey looked at executives predominantly from the US and several Western European countries, particularly the United Kingdom. More than half of the roles represented worked at companies with an annual revenue of USD$5bn or more.
Findings highlighting the importance of diversity and inclusion in AI
Of those surveyed from Europe, 88% of them were male and 81% of them were white. Comparing this to the US, 76% were female and 55% were white.
Out of all of the executives surveyed, 66% of them were in global leadership roles, 77% of them being in Europe and 56% in the United States.
The reported median cash compensation for data, analytics, and AI roles in Europe was USD$409,000 and in the US it was USD$546,000.
Adding to this, Heidrick & Struggles survey found that in the US 58% of executives received sign-on equity in the form of restricted stock units (RSUs), performance share units (PSUs), or a combination of both, while the figure was only 17% in Europe.
It is also interesting to note that out of all surveyed, 52% have been in their role for less than three years and 74% were in a role that only existed in the company for less than five years.
Not only does this suggest a high level of turnover, but it also suggests a change in strategic priorities resulting in demand for a first-time executive leader.
The importance of diversity and inclusion for AI efficiency
Diversity and inclusion is an important part of any business strategy. A diverse workforce generates diverse ideas, giving companies more to work with and more often than not it improves business performance.
With AI and data roles, diversity is particularly important as AI bias continues to be an issue that holds back the technology in terms of efficiency.
The underlying reason for AI bias lies in human prejudice, conscious or unconscious and this bias lurks in AI algorithms throughout their development.
As a result, AI solutions adopt and scale human biases. These biases can be anything from racial and gender bias to age discrimination.
This diversity issue highlighted by Heidrick & Struggles means that the AI systems these executives work on could be flawed and perpetuate gender and racial biases.
Heidrick & Struggles, advisers on emerging technologies and disruptive innovation, urge that this issue is focused and improved upon. Without this change, the benefits of AI become significantly limited.