Credera's AI Global Council presents "Keys to success with AI"

The AI Global Council is a consortium of thought leaders and industry figures from a diverse range of backgrounds who have joined together in response to the rapidly evolving landscape of artificial intelligence (AI).  

Last month, the Council met to discuss the primary keys to success with AI. A recent Forrester survey found that 90% of executives plan to use generative AI, but that same percentage reported that their initiatives never manage to progress beyond the pilot stage.

The Council members discussed how organizations can avoid this “pilot purgatory” and bring their AI solutions into production to start capturing value. 

Watch the full webinar, or read a recap of the conversation below:

Identifying the hurdles 

To kick off the webinar, the Council members shared their perspectives on why so many AI pilots fail to capture meaningful value. 

Vincent Yates, Global Chief Data Scientist at Credera, highlighted the problem organizations have as they “rush” to implement AI solutions: Many failed AI programs were pushed forward with no clear understanding of how they would drive revenue or enhance customer experiences. This lack of clarity leads to a proliferation of proof-of-concepts (POCs) that, while innovative, fail to create tangible business value. 

Alisa Miller, Chief AI Officer at Aletheia, highlighted the critical role of data and noted that data must be organized and fit for purpose to train effective AI models. However, internal conflicts over data ownership and decision-making processes often hinder progress. Miller underscored the importance of aligning AI initiatives with broader business goals to avoid creating "ornaments without a tree." 

Yates and Miller both noted that the human element is a significant barrier to capturing the full value of AI, as employees often fear job displacement and are uncertain about their roles in an AI-driven future. This necessitates a robust change management strategy to address these concerns and foster a culture of experimentation and continuous learning. 

On that point, Cecilia Dones, principal at 3 Standard Deviations, said organizations that create an AI-first culture can expect to see greater success with their AI initiatives and recommended auditing organizational attitudes, beliefs, norms, and values to foster an environment where experimentation is encouraged. Dones advocated for embedding AI into daily rituals and leveraging gamification and leaderboards to drive engagement.  

Ryan Johnson, VP of Engineering at Abre, discussed the technological challenges, particularly the inconsistency of AI model outputs. Unlike traditional deterministic programming, AI models can produce different results from the same input, necessitating extended testing and iteration periods. This unpredictability can stall projects at the POC stage.  

Moving beyond the stagnation  

Having identified the key hurdles that often cause AI initiatives to stall, the AI Global Council experts shifted their focus to actionable strategies for overcoming these challenges.   

JoAnn Stonier, Chief Data Officer at MasterCard, stressed the importance of getting the data house in order—making sure data is accessible, high-quality, and free from biases. This involves addressing data silos, ensuring data rights, and implementing robust data governance frameworks. Stonier also highlighted the need for ongoing data quality assessments to maintain the integrity of AI models.  

Adam Floyd, a retired federal patent attorney, pointed out that legal and regulatory implications are critical, especially concerning data rights and privacy. Organizations must work closely with legal counsel to navigate these complexities and ensure compliance with relevant laws and regulations.  

The panelists agreed that measuring the value of AI initiatives extends beyond traditional ROI metrics. Miller suggested AI leaders partner with their CFOs to define both direct and indirect value, considering efficiency gains and strategic benefits. Vincent Yates added that building the organizational muscle for AI experimentation is crucial, even if the immediate ROI is not apparent.  

Steps for success 

The Council provided a comprehensive checklist for organizations seeking to advance their AI initiatives:  

1. Define the problem: Clearly articulate the problem or opportunity the AI initiative aims to address. 

2. Structure POCs for insight: Design POCs to generate valuable insights and iteratively build towards the larger goal. 

3. Set clear goals and timelines: Establish specific objectives and timelines for each phase of the project. 

4. Identify decision-makers: Clarify who will make decisions at each stage of the project. 

5. Maintain foundational models: Regularly update and monitor AI models to ensure they remain relevant and effective. 

6. Check context continuously: Regularly assess the cultural, technological, and data contexts to ensure alignment with organizational goals. 

7. Foster tenacity and resilience: Build systems that support persistent effort and adaptability. 

The bottom line By addressing strategic integration, data readiness, people and process challenges, and effective governance, organizations can unlock the full potential of AI. As the panelists emphasized, success requires a holistic approach that balances innovation with compliance and fosters a culture of continuous learning and experimentation.   

To learn more, and continue to find guidance on overcoming some of these challenges, check out more content from the AI Global Council.   

Explore more about the AI Global Council   

The AI Global Council serves as a forum composed of experts, policymakers, academics, and industry leaders who engage in pressing conversations about the amorphous reality of AI and how it is shaping the world. For more information about the Council, and to stay connected to their work, follow along on LinkedIn or reach out to Credera.

• AI Global Council
• AI Strategy
• AI Governance
• AI Technology
• AI
• Generative AI