Insight
Attitudes toward AI are positive — leaders see it as an opportunity more than a risk
Executives are keenly aware of the opportunities that AI could present. Specifically, these opportunities relate to AI applications that could support or replace office jobs, including machine learning, natural language processing, expert systems, and generative AI. More than 90% agree that AI represents an opportunity for them in their roles rather than a risk. Leaders are also confident that AI is an opportunity for their organization, with 85% seeing AI as an opportunity to improve their organization’s capabilities (see Figure 1).
“Nobody has a real clue about AI’s true magnitude and end-state.”
Martin Brudermüller, BASF
“AI is not about disruption, it is about opportunities.”
David R. Hardoon, Aboitiz
On the one hand, the significant opportunity identified by leaders, both for their role and for their organization as a whole, was the increased efficiency that the effective use of AI could bring; around three-quarters identified this as an opportunity for their roles, with a similar number identifying it as an opportunity for their organization. Other AI opportunities that executives identified included more effective decision-making, improved risk management, and the creation of innovative products and services.
On the other hand, respondents were alert to the potential risks associated with AI. ‘Workforce displacement’ and ‘data privacy & security’ emerged as the two main concerns for leaders—with regard to both their individual roles and their organizations (see Figure 2).
For me in my role/position, I see AI primarily being a:
Sources: Kearny and Egon Zehnder analysis
Figure 1
For my organization’s capabilities, I see AI as primarily being a:
Sources: Kearny and Egon Zehnder analysis
Figure 1
Role
Chance (% of participants)
Efficiency
73
Decision-making
57
Risk management
48
Innovative products/services
47
Competitive advantage
44
Consumer experience
36
Other
7
Risk (% of participants)
Workplace displacement
5
Dependence & reliability
5
Bias & fairness
5
Data privacy & security
5
Transparency & interpretability
3
Other
2
Regulatory compliance
1
Sources: Kearny and Egon Zehnder analysis
Figure 2
Organization
Chance (% of participants)
Efficiency
78
Innovative products/services
60
Competitive advantage
57
Consumer experience
54
Decision-making
51
Risk management
43
Other
5
Risk (% of participants)
Workplace displacement
10
Data privacy & security
10
Dependence & reliability
8
Bias & fairness
8
Regulatory compliance
6
Transparency & interpretability
6
Other
2
Sources: Kearny and Egon Zehnder analysis
Figure 2
“The fear of [AI’s] failure is a concern, but is heavily outweighed by the opportunity it promises.”
Mark Rose, Avison Young
“AI is going to be big and will impact everything!”
Lior Ron, Uber Freight
“Regulators need to set the right frame, which is a risk-free environment to test and scale and then pair with appropriate incentives and regulation at real-life adoption.”
Martin Brudermüller, BASF
“Every human working with AI has not only the power but also the responsibility to evaluate content generated by AI critically.”
Carsten Knobel, Henkel
With so many risks and considerations, where should leaders focus their concerns? Amidst the challenges of the current poly-crisis, it can be difficult to identify and focus on the myriad of risks associated with the current wave of AI. Through our experience with clients and research, we have identified four key risks leaders should look out for (see Figure 3).
- Data hallucination. While generative AI models are highly accurate, they remain 100% confident, even when wrong. This proves the inevitable need for a “human-in-the-loop” process to verify model outcomes continuously and is confirmed by our survey results indicating a concern around ‘dependence and reliability.’
- Ballooning costs. As the data volumes stored by AI platforms rise, so do the collection, storage, and processing costs. More efficient data management techniques can help mitigate some impact. The concern around costs clearly emerged from our conversations with leaders, even though we did not address it in the survey.
- Risks from third-party (3P) services. Relying on 3P services for handling sensitive data and compliance can expose businesses to risks, particularly if security measures are lax or standards are inconsistent. To safeguard against these vulnerabilities, conducting due diligence on 3P providers carefully is essential, as well as enforcing strong data protection practices and contracts that clearly define roles and responsibilities.
- AI’s bias. The quality of an AI model’s output is directly linked to the data it’s trained on. If the training data is not a balanced reflection of the real-world diversity it is trying to represent, the AI may generate biased results. Ensuring that AI operates fairly involves selecting training datasets comprehensively representing the target outcomes, thus promoting unbiased and reliable outputs.
Four Common Risks
Figure 3
Insight
Executives believe that significant change within their organizations is on the horizon, but less for their individual roles
Business leaders expect AI to be a major disruptive force in the near term, with 70% of respondents agreeing that AI will disrupt their organization within the next five years. However, fewer executives expect the same level of disruption when it comes to their own roles. Less than half agree that AI will disrupt their role in the next five years, while a third expect no disruption (see Figure 4).
Moreover, our conversations with leaders revealed anticipation of a transformational wave within their organizations, spurred by AI; leaders predicted it would reshape future business landscapes. Despite recognizing the disruptive potential of AI, especially in streamlining operations and enhancing strategic decisions, many do not foresee their individual roles undergoing significant change. The sentiment across the board suggests an awareness of the necessity to adapt, with a hint of caution regarding the full scope of AI’s implications yet to be fully grasped. This reflects a measured optimism about AI’s role in driving efficiency and competitive edge, while leaders also acknowledge the gaps in their own understanding of AI’s future impact.
Business leaders expect AI to be more disruptive to their organization than to themselves and their position in the next 5 years
43
70
36
21
21
9
Agree
Disagree
Neither Agree/Disagree
Role
Organization
Note: Percentages may not resolve due to rounding.
Sources: Kearney and Egon Zehnder analysis
Figure 4
“AI has a huge potential to be truly disruptive. But I don’t believe it will fundamentally change the way we operate our business; rather, it will create a huge value-add and bring ammunitions for efficiency, faster decision-making, and other business outcomes.”
Rebecca Oldfield, Infineum
“Data-driven job profiles, which already leverage insights based on machine-driven decisions, will only experience little changes for their leadership through AI.”
Rolf Schumann, Schwarz Gruppe
“In my role as CEO, I need to be a role model and a driver for change. Change always starts at the top. This is a crucial belief in our cultural transformation, and I think you can transfer this to the adoption of disruptive technologies as well. We need to be ready when it comes to all kinds of disruptions, especially when they have an impact in the magnitude of Gen AI.”
Carsten Knobel, Henkel