AI Economics: Digitization, Efficiencies, and Value Creation

Co-authored by Mohamad Chahine, Volunteer Advisor and Faculty Member, Value Creation Innovation Institute (VCII)

The advent of artificial intelligence (AI) and its integration into the fabric of business operations is reshaping the economics of digitization. This transformation is most palpable in the realm of operational efficiencies and cost savings, particularly regarding Full-Time Equivalents (FTEs). Here, we explore the mechanisms through which AI efficiencies and values can be quantified and how AI can drive FTE cost savings at both the Private Equity (PE) and Operational Company (OpCo) levels.

AI Efficiencies and Value Calculation

Calculating the efficiencies and value generated by AI involves analyzing the reduction in time and resources required to perform tasks traditionally handled by human employees. This calculation often centers on the concept of FTE savings, which reflects the number of full-time employees that can be reallocated or reduced due to AI automation and process optimization. Key parameters in this evaluation include:

• Task Automation: Identifying repetitive, rule-based tasks that AI can perform more efficiently than humans, such as data entry, analysis, and customer service inquiries. The time saved per task, multiplied by the frequency of these tasks, equates to FTE savings.
• Process Optimization: AI's ability to streamline workflows and enhance decision-making processes leads to broader operational efficiencies. By analyzing pre- and post-AI implementation performance, organizations can quantify improvements in productivity and operational throughput.
• Predictive Analytics: AI-driven forecasting can lead to more accurate demand planning, inventory management, and financial modeling. The efficiencies gained through reduced overstock, optimized capital allocation, and improved strategic planning further contribute to FTE savings.

AI-Driven FTE Cost Savings in PE and OpCo Levels

At the Private Equity Level - examples:

• Portfolio Management: AI can significantly streamline the due diligence and portfolio management processes, allowing PE firms to manage more investments with fewer analysts. Automated data aggregation and analysis can reduce the FTE requirements for portfolio oversight, leading to substantial cost savings.
• Deal Sourcing: AI-powered tools can automate the identification and initial screening of potential investment opportunities. By reducing the need for manual research and preliminary analysis, PE firms can allocate their human capital more effectively, enhancing productivity and reducing associated labor costs.

At the Operational Company Level - examples:

• Operational Efficiency: For OpCos, AI can automate various operational processes, from manufacturing line optimization to administrative functions, thereby directly reducing the need for manual labor. This automation translates into direct FTE savings by either reducing the workforce or reallocating employees to higher-value tasks.
• Customer Service: Implementing AI-driven chatbots and virtual assistants can handle a significant volume of customer inquiries without human intervention. This not only improves service quality and responsiveness but also reduces the FTE costs associated with large customer service teams.

Addressing AI Business Leakage

One of the critical challenges in AI economics is AI business leakage, where the benefits generated by AI are not fully captured by the intended entities. This can occur due to inefficiencies, data mismanagement, or unauthorized use of AI technologies.

• Leakage Scenarios: Business leakage might happen when AI systems inadvertently share valuable insights with competitors or when AI-generated profits are not adequately taxed. These leakages can result in significant financial losses and diminished competitive advantage.
• Mitigation Strategies: To address AI business leakage, organizations must implement strict data governance policies, ensure proper licensing and usage agreements for AI technologies, and continuously monitor AI systems for unauthorized activities. Collaboration with regulators to create robust frameworks for AI governance is also essential.

The economics of digitization, fueled by AI, presents a compelling case for the transformation of traditional business operations. By calculating AI efficiencies in terms of FTE savings, organizations can quantify the tangible benefits of AI integration. At both the PE and OpCo levels, AI's potential to streamline operations, enhance decision-making, and optimize customer interactions leads to significant cost savings and operational improvements. As businesses continue to embrace AI, the ability to effectively measure and realize these efficiencies will be critical for maintaining competitive advantage and driving sustainable growth in the digital era.

For more insights and to stay updated on the latest in AI economics and innovations, visit the Value Creation Innovation Institute.

References

• Chahine, M. (2024). The AI Fortune Teller. 
• Chahine, M. (2024). Digital Private Equity.