Unlocking Generative AI’s Cost-Saving Potential with Zero-Based Redesign

Introduction: The Productivity-Savings Disconnect

Generative AI is revolutionizing productivity by accelerating tasks such as decision-making, content creation, and data analysis. Early deployments have showcased AI’s ability to deliver results more efficiently and at a higher quality, with customer service, software engineering, and HR functions all benefiting significantly.

Despite these productivity gains, many organizations are struggling to translate them into cost savings. While leading companies are achieving 25% cost reductions through generative AI and end-to-end process redesign, others report savings of 5% or less, creating a disconnect that frustrates executive teams and investors alike.

To bridge this gap, companies must align generative AI-driven productivity improvements with strategic cost management goals, and zero-based redesign (ZBR) provides the roadmap to achieve this alignment.

The Barriers to Generative AI Cost Savings

Companies facing a productivity-savings disconnect often encounter three common obstacles:

1. Lack of a Day-One Cost Mission

   • Early generative AI experiments lacked a clear cost mission, such as ROI targets and accountability mechanisms.

   • This absence of upfront planning has led to isolated productivity improvements with no clear path to cost reduction.

2. Insufficient Internal Sponsorship

   • Generative AI requires collaboration between technology teams and functional leaders.

   • Without executive sponsorship, technology teams’ cost-saving predictions often fail to resonate with business leaders.

3. Outdated End-to-End Processes

   • Generative AI can amplify inefficiencies in legacy workflows unless paired with a comprehensive redesign of work processes.

   • Cost savings require organizational changes, including process simplification, targeted headcount reduction, and change management.

Zero-Based Redesign for the Generative AI Era

ZBR offers a transformative approach to align generative AI-driven productivity with cost-saving goals. Unlike traditional cost-cutting measures, ZBR involves rethinking and reconstructing business processes based on strategic priorities.

Key Steps in a Generative AI-Powered ZBR:

1. Radical Simplification

   • Identify inefficiencies and remove unnecessary or duplicative tasks.

   • Redesign workflows using generative AI to streamline processes.

   Example: In financial planning, instead of automating all manual data collection, focus only on data that drives actionable insights.

2. Capacity Reset

   • Use generative AI to augment human capabilities, automating routine tasks and enabling employees to focus on high-value work.

   • Adjust organizational capacity to match redesigned workflows.

   Example: AI tools can handle the first draft of complex forecasts, allowing finance professionals to focus on refining and interpreting results.

3. Scalable Efficiency

   • Pair generative AI deployment with organizational changes, such as reducing headcount in areas where AI takes over routine tasks.

   • Scale AI-driven workflows to maximize impact across the organization.

Case Study: A Wealth and Asset Manager’s $1 Billion Transformation

A leading wealth and asset manager turned to ZBR to achieve $1 billion in annualized savings, equivalent to 20% of its cost base. By combining generative AI with end-to-end process redesign, the company achieved:

• 40% workload reduction in finance and compliance through automated reporting and analysis.

• A roadmap for scaling generative AI across other functions, aligning productivity gains with tangible financial outcomes.

Key Questions to Drive Progress

To reconnect generative AI productivity gains with cost savings, executive teams should assess their current initiatives by asking:

1. Have we reimagined workflows in light of generative AI’s capabilities?

2. Do we have a clear ROI plan to scale generative AI experiments?

3. How will our organization evolve as generative AI advances?

Conclusion: Reclaiming Generative AI’s Cost-Saving Potential

Generative AI offers unparalleled opportunities to improve productivity and reduce costs, but realizing these benefits requires a strategic approach. By pairing generative AI with zero-based redesign, companies can achieve transformative cost savings, boost operational efficiency, and build a sustainable foundation for future growth.

For executive teams facing a productivity-savings disconnect, the path forward is clear: Embrace ZBR, rethink processes, and unlock the full power of generative AI to deliver lasting value.