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You are at:Home»2024 Predictions»Will 2024 see the advent of the chief AI officer?
2024 Predictions

Will 2024 see the advent of the chief AI officer?

In 2024 many organizations will appoint a chief AI officer to oversee the safe and responsible use of AI, says Bernd Greifeneder…
November 30, 20233 Mins Read
a board meeting in progress. A seat is empty where risk reporting should be.

In 2024, organizations will increasingly appoint senior executives to their leadership teams to ensure readiness for AI’s security, compliance, and governance implications. The chief AI officer, or an equivalent senior executive, will become commonplace.

As employees become more accustomed to using AI in their personal lives, through exposure to tools such as ChatGPT, they will increasingly look to use AI to boost their productivity at work. Organizations have already realized that if they don’t empower their employees to use AI tools officially, they will do so without consent. Organizations will, therefore, appoint a chief AI officer (CAIO) to oversee their use of these technologies in the same way that many have a security executive, or CISO, on their leadership teams. The CAIO will focus on developing policies and educating and empowering the workforce to use AI safely to protect the organization from accidental noncompliance, intellectual property leakage, or security threats. These practices will pave the way for widespread adoption of AI across organizations. As this trend progresses, AI will become a commodity, as the mobile phone has.

Code generated by generative AI could be the cause of major digital service outages

An aspect of the increased use of generative AI in 2024 may be major digital service outages due to insufficiently supervised software code, as developers turn to generative AI for help with code development.

Developers will increasingly use generative AI-powered autonomous agents to write code for them, exposing their organizations to increased risks of unexpected problems that affect customer and user experiences. This is because the challenge of maintaining autonomous agent-generated code is similar to preserving code created by developers who have left an organization. None of the remaining team members fully understand the code. Therefore, no one can quickly resolve problems in the code when they arise. Also, those who attempt to use generative AI to review and resolve issues in the code created by autonomous agents will find themselves with a recursive problem, as they will still lack the fundamental knowledge and understanding needed to manage it effectively.

These challenges will drive organizations to develop digital immune systems, combining practices and technologies for software design, development, operations, and analytics to protect their software from the inside by ensuring code resilience by default. To enable this, organizations will harness predictive AI to automatically forecast problems in code or applications before they emerge and trigger an instant, automated response to safeguard user experience. For example, development teams can design applications with self-healing capabilities. These capabilities enable automatic roll-back to the latest stable version of the codebase if a new release introduces errors, or automated provisioning of additional cloud resources to support an increase in demand for compute power.

The author

Bernd Greifeneder is founder and CTO of Dynatrace

Africa Asia Asia Pacific Australasia Europe Middle East North America UK
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