Empowering CDAOs to Lead the AI Revolution

The Current State of AI Adoption

The rapid rise of artificial intelligence (AI) is undeniable. According to the 2024 Gartner® CIO and Technology Executive Survey, 34% of respondents report they have AI in production.

We believe, this underscores AI’s growing prominence in the business landscape. As AI changes industries, Chief Data and Analytics Officers (CDAOs) lead this transformation. They must manage the challenges of using AI and unlock its full potential.

The Rise of Dedicated AI Teams

Interestingly, the same AI survey shows that 87% of respondents in more mature AI organizations report that they have a dedicated AI team, while 75% of respondents in less mature AI organizations report that they have a dedicated AI team. Of those organizations with a dedicated AI team, 37% of respondents indicate that it reports to the CIO, 24% to the CTO and 19% to the CDO or CAO.

Let’s take a look at more of our understanding of Gartner key insights:

Key Challenges in AI Adoption

While the potential of AI is immense, its successful implementation is often hindered by several challenges:

• Skills and Talent Shortage: The demand for AI expertise continues to outpace the available talent pool. This skills gap is especially clear in organizations that use AI well. Here, roles like AI engineers and prompt engineers are crucial.

“Skills and staff shortages have dropped from position 1 to 3, but still remain a top challenge for data and analytics success, according to the 2024 Gartner CDAO Agenda Survey.”

• Aligning AI with Business Value: Demonstrating tangible ROI and ensuring that AI initiatives directly contribute to business objectives remains a challenge for many organizations. Bridging the gap between AI capabilities and measurable business impact requires strategic planning and execution.
• Organizational Structure: Choosing the right organizational model to support AI maturity and growth can be complex. It requires careful consideration of factors such as the organization's size, industry, and level of AI adoption. The wrong structure can stifle innovation or lead to inefficiencies.

The challenge today for CDAOs is to adopt AI in a way that is more scalable, valuable, and responsible. More mature AI adoption requires close collaboration between multiple business, technology, and governance teams—both existing and new. 

The pervasiveness of AI introduces complexities and uncertainties into known, existing organizational models. This necessitates a reevaluation of these models to build a robust way of working with AI that avoids potential pitfalls.

However, successfully integrating AI into an organization's DNA is no small feat. It demands a strategic approach to organizational structure, talent management, and a clear understanding of the evolving AI landscape. The aforementioned Gartner report offers invaluable insights to guide CDAOs in building high-performing AI teams and driving innovation.

Our Key Takeaways from Gartner Recommendations for CDAO Success

We think, to navigate these challenges and unlock the full potential of AI, Gartner report offers actionable recommendations for CDAOs:

• Foster Collaboration with Fusion Teams: Break down silos and encourage cross-functional collaboration by creating teams that involve diverse perspectives from business, IT, data, and AI throughout the AI lifecycle. These multidisciplinary teams, often called "fusion teams" or "pods," ensure that AI solutions are aligned with business needs and address real-world challenges.
  
  CDAOs should

"initiate and execute their AI initiatives by actively working with key business stakeholders in these fusion teams during the entire life cycle."

• Adopt AI Maturity-Based Organizational Models: Tailor your AI organizational structure to your specific stage of AI adoption. Whether you're in the early stages of experimentation with an AI lab or scaling AI across the enterprise with a hybrid model, ensure the right model is in place at the right time to foster innovation and efficiency.

"Select the best-fit-for-purpose organizational structure, aligned with a vision that is business-value-driven, to utilize AI—then select the required AI maturity and adoption phase to realize that vision."

• Build a High-Performing AI Team: Identify and fill critical AI roles, addressing skills gaps through strategic hiring or upskilling existing talent. Invest in developing a team with the expertise needed to drive AI success. Gartner highlights "must-have" roles such as Data Engineers, AI Engineers, and Prompt Engineers as crucial for effective AI implementation.
  

"Create must-have AI roles for the enterprise by identifying skills gaps using AI job descriptions, raising the level of AI literacy, and hiring talent or reskilling/upskilling existing employees."

• Cultivate AI Literacy: Promote understanding and adoption of AI across the enterprise. By fostering AI literacy, you can maximize its value, mitigate risks, and ensure that AI is embraced as a tool for innovation and growth. Gartner emphasizes that training and knowledge-sharing are essential for building a common understanding of AI and its implications.

The MicroStrategy Perspective

At MicroStrategy, we understand that while awareness of AI, particularly Generative AI, is high, successful implementation remains a challenge. Even though organizations have a great deal of awareness of GenAI, most attempts to roll this out are still in the early stages (prototype) or have rolled out unsuccessfully. Organizations will need to implement new strategies to ensure that GenAI is rolled out successfully.

This would mean creating multidisciplinary teams (Fusion teams), bringing employees from various disciplines and backgrounds together. These Fusion teams will need to be involved throughout the entire journey to ensure that AI is successfully rolled out to all departments and operations. Organizations will also need to recruit to continue to upskill and identify skill gaps.

MicroStrategy empowers CDAOs to overcome these obstacles by providing a comprehensive platform for AI-driven insights and decision-making. Our platform enables seamless integration of AI into existing workflows, fostering collaboration, and driving measurable business outcomes.

From AI Awareness to AI Action: MicroStrategy Empowers CDAOs to Lead Successful Implementations

Download the full Gartner report today to equip your CDAO with the knowledge and strategies needed to lead the AI revolution.

Explore MicroStrategy's AI solutions and discover how we can help your organization unlock the full potential of AI.

^{Gartner, How Should CDAOs Organize for AI and What Roles Are Required? By Jorg Heizenberg, Pieter den Hamer, 19 March 2024}

^{GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.}