Businesses are increasingly investing in artificial intelligence, but many remain in the early stages of deployment, facing challenges in data management and leadership.
AI in Strategy – But Without Mature Structures
Organizations worldwide are actively experimenting with AI implementation, but few consider themselves technologically mature. A Heidrick & Struggles survey of 318 data and AI executives reveals most companies are still in the pilot and testing phases.
Despite AI becoming a key strategic topic, organizations are still learning how to effectively utilize the technology at scale.
The Growing Role of Data and AI Leaders
The report highlights the increasing importance of leaders responsible for data and artificial intelligence. Initially, AI initiatives were often assigned to technology departments under the CTO.
Today, dedicated positions like Chief Data Officer and Chief AI Officer are becoming more common.
However, 40% of respondents indicate they serve as the primary data and analytics leader in their organization, with many of these roles several levels below the CEO.
Chaotic Development of AI Functions
The development of these functions often occurs chaotically. Instead of creating new roles, companies frequently expand the responsibilities of existing positions to include AI-related tasks.
This leads to ambiguity in both responsibility and expectations for leaders.
Salaries Rise Faster Than AI Maturity
Uncertainty regarding the role of AI leaders isn’t hindering salary growth. In fact, compensation is increasing faster than organizational maturity in AI utilization.
Compensation Levels
In the United States, the average total cash compensation for data and AI leaders is approximately $380,000 annually, with additional components like stock or long-term incentive programs averaging $498,000. In Europe, the average cash compensation is around €272,000, with additional equity components around €178,000.
The financial sector and large public companies offer the highest salaries, due to intense competition for technology leaders.
Data, Not Algorithms, Is the Biggest Barrier
While public debate focuses on generative AI’s capabilities, organizations still face fundamental challenges: data quality, security, and regulatory compliance.
These three areas are most frequently cited as the main barriers to scaling AI projects. Companies are realizing that AI implementation requires rebuilding processes, competencies, and data management, not just implementing new tools.
A Dynamically Changing Skills Market
The report shows that the demand for AI-related skills is rapidly evolving. Skills in change management and cloud engineering are gaining importance, as they are crucial for deploying AI across the organization.
Some skills previously considered strategic, such as prompt engineering, are losing relevance with the development of AI tools themselves.
As a result, the talent market for data and artificial intelligence remains one of the most dynamic segments of the job market. Companies are actively seeking leaders who can not only develop the technology but also translate its potential into real business transformation.
—Łukasz Kiniewicz, Managing Partner for Poland and Central & Eastern Europe at Heidrick & Struggles.
