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Why CDOs Make the Best Chief AI Officers

In today’s fast-moving digital space, new businesses are launched daily, people constantly face new challenges and roles, and technology changes in the blink of an eye. We see companies adopt AI in a majority of their operations, leading to the specialized leadership role of a Chief AI Officer.

The Rising Need for AI Officers in the Workplace

A survey conducted by Randstad revealed that nearly 47% of the workforce is eager to see AI implemented in their work environment. And this enthusiasm is absolutely well-deserved; in many roles and across many tasks, AI can be a powerful catalyst that can increase efficiency and productivity.

The demand for AI skills has a notable uptick, with more and more job posts listing AI expertise as a must-have. To oversee these tasks across an organization, companies are now looking for AI officers who can execute and supervise projects with the help of AI, lead AI initiatives, and foster a culture of ethical AI usage.

Now, with such a new role, the job description and skillset are still not well-defined. So who do you hire for this role? At the very least, we need someone who can upskill themselves quickly with the changing environments and has the right background and experience.

Compared to just 45% in 2022, almost 95% of CDOs have adopted AI in some form in their organization since 2023. With this, we truly believe that Chief Data Officers, and other senior data leaders, are uniquely positioned to take up the role of a Chief AI Officer. Here’s why.


Why CDOs are Best Suited for the Role of Chief AI Officers

CDOs are proficient not only in data-related matters but also in their ability to adapt to the changing trends in technology. Their skills, experience, and expertise make them among the top choices for executive AI roles.

Their Expertise in Data Management

Data is a key aspect of AI and ML, and CDOs are already experts at handling it, making them well-suited for AI projects. With their profound knowledge and expertise in data management, they often use AI algorithms to decipher and modify intricate data structures. Their expertise in handling large-scale data makes them ideal candidates for AI roles.

Case Study: IBM

A prime example is the case of the global tech giant, IBM. Their former CDO, Inderpal Bhandari, paved the way for weaving AI into IBM’s business strategy. The company uses the data-driven AI strategy for better decision-making and to improve consumer experiences.

Strategic Vision Towards Business Objectives

CDOs are not just data specialists; they are visionaries. They have the unique ability to coordinate AI strategies with the overarching objectives of the company, thus guaranteeing that the AI projects not only help with operations but also generate value.

Case Study: American Express

As the President of Information Management at American Express, Ash Gupta introduced AI and ML to accurately identify card fraud. By training fraud detection models on over 1 trillion dollars worth of transactions, AmEx developed systems that were far more accurate, and also adaptive to changing data.

Their Expertise in Compliance and Data Governance

As AI is still evolving, its implementation comes with a multitude of ethical and governance challenges. CDOs, who often manage data privacy security, and compliance challenges, are already adept at navigating these hurdles. Their experience with ethical and compliance guidelines can prove invaluable in an AI-related role.

Challenges and Opportunities for Data Leaders as Chief AI Officers

Even though CDOs are most qualified for the Chief AI Officer role, they might still face some challenges:
  • AI is a rapidly evolving field. Taking on the responsibility of a company’s AI strategy would mean that you need to constantly be aware of, adapt to, and evolve with the latest changes.
  • Even after upskilling yourself, your employees/AI teams must be consistently upskilled. Training requires time and budget, which can be difficult to negotiate in a fast-paced work environment.

Nevertheless, these challenges can present a unique opportunity to foster a culture of learning and innovation. Executives can encourage continuous learning by providing skill development opportunities. CDOs and/or CAIOs can create and foster a work environment where colleagues learn, collaborate, and grow together.

Building in-house expertise can empower employees and drive organizational growth. This can be achieved by establishing training programs, hackathons, seminars, etc. that provide hands-on experience.

JPMorgan Chase is an excellent example in this regard. The company boasts of high competence in AI. This is a result of their in-house training initiatives that aim to continuously upskill their staff. Establishing this kind of proactive learning culture is very much needed in today’s workplace.


Changing the Way We Work with AI

Many businesses are struggling to adapt to the rapid advancements in AI. This is often because the knowledge in this area is constantly evolving, and there’s a need for developing specialized skills in leadership to effectively manage these changes. Data leaders who view AI as an opportunity will be the key drivers of their company’s AI initiatives.

In light of all the developments in the field of AI, do you have what it takes to become a Chief AI Officer? What are the challenges that are stopping you from transitioning into this role?

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