ResourcesBlogProduct Management Monday: Scaling AI for Product Managers: Governance, Risk, and Cost Optimization 

Product Management Monday: Scaling AI for Product Managers: Governance, Risk, and Cost Optimization 

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AI Scaling for Product Managers

Artificial Intelligence has unlocked new opportunities for product managers to generate value for their customers. However, investing in an AI product without carefully thinking through the business context, goals, and the costs required to scale it, can result in significant wasted development and misallocation of resources. This article provides a roadmap for product managers on how to navigate the complexities of governance, cost management, and risk mitigation strategies when it comes to scaling with AI. 

Effective Governance for AI Initiatives 

As part of your discovery process, investigate your company’s AI governance framework. If this is missing, it will be difficult to ensure that AI deployments enhance product offerings and adhere to ethical and regulatory standards. Work with your leadership to develop a governance framework. We recommend including cross functional approach as well as ethical considerations.  

  1. Ethical AI Guidelines: Create a set of ethical guidelines that dictate how AI should be used in products. This includes ensuring decisions on how to use AI are fair, transparent, and privacy-centric, helping maintain customer trust and regulatory compliance. 
  1. Set Up Cross-Functional Governance Teams: Involve stakeholders from various departments—such as legal, IT, and operations—to form governance teams that oversee AI projects at your company. A cross-functional approach is best to ensure that various aspects of AI deployment, from data usage to user impact, follow your company’s guidelines. These cross-functional tasks are a important part of the Product Managers role.

Cost Management  

Just because AI is the latest emerging technology, it does not mean that it is the right solution for all products. Managing and maintaining data, infrastructure, and the need for specialized talent can all add up. Effective cost management is vital for ensuring that AI initiatives deliver a positive ROI. This is also a great opportunity to work with the finance team on how best to invest in systems and tools and forecast resource spend. 

  1. Cloud-Based and AIaaS Solutions: There are now many cloud and AI-as-a-Service (AIaaS) platforms that are more cost effective to use. These solutions reduce the need for in-house infrastructure and talent, and are generally more cost effective at a smaller scale. 
  1. Adopt a Phased Scaling Approach: Introduce AI functionalities incrementally. Start with pilot projects or MVPs to validate the value and viability of AI ideas before full-scale implementation.  
  1. Focus on High-ROI AI Applications: Identify and prioritize AI applications that really need to be based on AI. The products should either reduce costs significantly or enhance revenue growth as a result of using the technology. If there is a way to get the same results without AI, it’s possible that AI is superfluous and should not be used. 

Risk Mitigation Strategies 

AI involves many kinds of risks such as execution risk and even organizational reputation risk. Product managers must proactively address these risks and think through mitigation strategies. Here are a few ways to mitigate risks of AI: 

  1. Monitor AI Performance Continuously: Implement tools and practices to proactively raise issues like model drift or unexpected user interactions, which could compromise product functionality or user experience. 
  1. Prioritize Data Security and Privacy: As products collect and utilize more user data to fuel AI, safeguarding this data is extremely important. Ensure that all AI solutions comply with data protection regulations and are secure. 
  1. Conduct Bias Audits: Regularly review AI models for biases that could lead to unfair or unethical outcomes. This demonstrates a commitment to responsible and ethical AI practices and products. 

For product managers, AI is an exciting way to deliver new value to customers. But the focus should be on scalable and sustainable AI solutions. This strategic approach ensures that AI technologies not only enhance product capabilities but also align with broader business objectives and ethical standards. Make sure your company takes the right steps to create a governance framework, manage costs, and think through risks early, to avoid surprises and deliver ROI. To fully get up to speed with this powerful emergent technology and see how to incorporate it into your product roadmap sign up for our AI innovation for product managers course today.  

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ABOUT THE AUTHOR
Rina Alexin
CEO

Rina, the CEO of 280 Group, has a distinguished background in finance and innovation. Starting her career as an analyst at McKinsey & Company, she specialized in credit and interest rate risk management. She further honed her leadership skills at MetLife, focusing on intrapreneurship and employee recognition in Latin America. At 280 Group, Rina excels in driving transformative change, empowering product professionals with essential skills for outstanding product management. Her leadership is characterized by a strong emphasis on continuous learning, team development, and a commitment to exceeding client expectations. Rina holds a BA with honors from Amherst College and an MBA from Harvard Business School. She is also a member of the Association of International Product Marketing and Management.

June 03, 2024