Biggest opportunities & risks leaders see in a "new era of AI"

Individually, over 90% agree that AI represents an opportunity for them in their roles, and 85% of leaders are confident that AI will benefit their organisation.

A new report has shown the need and demand for employers and employees alike to be prepared for a new era of AI.

The report, titled Leadership in the age of AI and published by Kearney in partnership with Egon Zehnder, noted that a monumental shift — one that already sees AI driving bottom-line results across multiple sectors — will change the way people behave and communicate.

According to the results, 91% believe that AI represents an opportunity for them in their roles, rather than a risk. Simultaneously, 85% of leaders are confident that AI is an opportunity to improve their organisation’s capabilities.

While this was so, leaders are also identifying the risks that come with this technology — both for individual roles and on an organisational level, with the biggest being workforce displacement and dependence & reliability.

Here is an expanded list of the types of opportunities and risks that participants recognised on both levels:

The report also showcased the four common risks that are commonly associated with the use of AI: 

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 the 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 was clear, even though it was not addressed 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.

Commenting on the report findings, Arjun Sethi, Regional Head and Chairman, APAC, Kearney, noted that it highlights the "prevailing sentiment among leaders when it comes to AI is optimism."

"The challenge now lies in translating this optimism into tangible action," he said, adding: "Keeping pace with AI through personal learning and continuous exploration are pivotal steps for leaders to not only embrace this transformative technology but also ensure sustained success in an ever-evolving landscape."

 Keeping pace with AI through personal learning and continuous exploration are pivotal steps for leaders to not only embrace this transformative technology but also ensure sustained success in an ever-evolving landscape.” he adds.

The survey involved 100 executives in the US, Japan, the UK, and Germany.

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Lead image / 123RF

Infographics: Leadership in the age of AI