Introduction

Managing AWS commitments, such as Reserved Instances and Savings Plans, while running an AWS Organization, is far more complex and risky than it might seem. Many companies rely on MSPs to manage these commitments, but the reality is that a lot of companies face unexpected challenges in commitment management.

A comment from an IT manager at a large enterprise really stood out:
"I had no idea AWS commitment management was this complex and risky. At first, I just thought it was about getting a discount..."

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1. The Reality of Commitment Management, Backed by Real Data

1.1 Surprising Numbers

A recent study revealed some surprising facts about how companies manage their AWS commitments. On average, the utilization rate for commitments is just 73%, meaning that 27% of purchased commitments are unused and wasted. Furthermore, companies often dedicate about 2.3 staff members to manage these commitments, and they spend an average of 48 hours per month making related decisions. This leads to delays, even in time-sensitive situations requiring urgent scaling.

1.2 Real-World Case: A Company's Commitment Management Failure

One real-world case illustrates the cost of poor management. Company A, which spends $500,000 monthly on AWS, suffered a $180,000 loss due to over-purchasing 3-year commitments. Additionally, they incurred $120,000 in extra on-demand costs because they couldn't predict changes in usage patterns. In total, they wasted $300,000, or 5% of their annual IT budget.

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2. Why Does This Happen?

2.1 Complex Decision-Making Structures

The first issue many companies face is the complexity of decision-making. Managing AWS commitments requires several teams to analyze, decide, and purchase, often leading to inefficiency. The process can take up to 1-2 weeks to complete, especially when each step requires coordination between development, infrastructure, finance, procurement, and post-purchase management teams.

2.2 Unpredictable Business Changes

Another challenge comes from unpredictable business changes. Company B, for instance, made a large 3-year GPU instance purchase in January 2023 to support an AI project. However, by August, project direction changed and GPU demand dropped by 70%. As a result, they ended up with $50,000 per month in unused commitments, totaling a loss of $1.8 million over 36 months.

2.3 Hidden Labor Costs

Furthermore, there are hidden labor costs. Managing these commitments often involves several people spending up to 150 hours per month on tasks like usage pattern analysis, coverage monitoring, and decision-making. This results in an annual labor cost of about $180,000 per person, which increases significantly with additional staff.

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3. The Impact of Commitment Management, Backed by Real Data

3.1 Manual Management vs. Automated Management Comparison

A comparison between manual management and automation reveals significant differences in efficiency and cost management:

• Manual Management:
  Companies using manual methods typically see a commitment utilization rate of around 68%. This means that 32% of purchased commitments are unused, leading to monthly wasted costs of about $320,000. Manual management often requires more human resources, with an average of 3 people dedicated to managing commitments.
  
  
• Automation:
  In contrast, companies that implement automation achieve a much higher commitment utilization rate of 94%, significantly reducing wasted costs to approximately $60,000 per month. The need for dedicated management staff also drops drastically, with companies requiring only 0.5 person to manage the system, improving efficiency and reducing labor costs.

3.2 Real-World Example: Company C

Company C, which had a monthly AWS spend of $600,000, implemented automation to streamline its commitment management. Before automation, the company faced $400,000 in on-demand costs and $80,000 in unused commitments, totaling $480,000 in monthly expenses. However, after adopting automation, their on-demand costs dropped to $120,000, and unused commitments fell to just $15,000. As a result, Company C saw $65,000 in monthly savings, representing a 9.6% decrease in their AWS costs.

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4. Limitations of the Existing Approach and a New Solution

4.1 MSP Dependency Dilemma

Many companies still rely on MSPs for commitment management, but MSPs often manage these commitments manually, which leads to difficulties in reflecting real-time business changes. There's also a lack of optimization due to standardized approaches that are not tailored to specific needs.

4.2 The Impact of AWS Policy Changes in 2025

In January 2026, AWS will implement a new Partner Commitment Sharing Policy, which will limit the benefits MSPs currently offer. This change will drive companies toward independent commitment management, requiring a fundamental shift in their existing approach.

4.3 The Rise of AI-Based Automation

AI-driven commitment management solutions are emerging to address these challenges. With real-time usage pattern analysis, future demand forecasting, and automatic commitment adjustments, companies can avoid waste and reduce risk proactively.

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5. Real Transition Case: Success Story of Company D

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Company D, which spent $400,000 monthly on AWS for its e-commerce platform, faced challenges managing seasonal traffic fluctuations. After analyzing their existing commitments and implementing an automated system, they transitioned gradually over three months. Six months later, their commitment utilization rate jumped from 71% to 96%, with monthly savings of $80,000 (a 15% reduction in costs). Additionally, their staff dedicated to commitment management dropped from 3 to just 0.5 person.

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6. The Solution: OpsNow AutoSavings

OpsNow AutoSavings is designed to solve all of these problems through AI-based automation. 

6.1 Key Features

1. AI-Based Full Automation

• 24/7 real-time usage monitoring
• Machine learning-driven commitment optimization recommendations and operations
• Automatic commitment purchasing and adjustments

2. Zero-Risk Guarantee

• Automatic reallocation of unused commitments
• Integration with AWS Marketplace for automatic sales
• Real-time optimization to minimize waste

3. Transparent Management

• Real-time dashboard
• Detailed cost analysis reports
• Expected savings simulation

6.2 Benefits of Adoption

Immediate Benefits:

• 90% reduction in commitment management staff
• Guaranteed commitment utilization rate of over 95%
• Monthly cost savings of 15-25%

Long-Term Benefits:

• Automatic response to AWS policy changes
• Real-time adaptation to business changes
• Sustainable cost optimization

6.3 Risk-Free Adoption Model

The pricing model for AutoSavings is entirely performance-based. There is no upfront investment, and no fixed costs. Companies only pay a percentage of the actual savings generated, making it a low-risk solution. Example of Actual Cost Structure

• Original Monthly AWS Cost: $1,000,000
• After AutoSaving Implementation: $800,000
• Actual Savings: $200,000
• OpsNow Fee: A percentage of the savings
• Net Savings for Customer: $140,000–$160,000

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Conclusion

Managing AWS commitments within an organization is far more complex and risky than it appears. Given the limitations of manual management, the unpredictability of business changes, and upcoming AWS policy shifts, it’s clear that a new approach is needed. OpsNow AutoSaving addresses all of these issues with AI-based automation, allowing companies to focus on their core business while experiencing true cloud optimization.

For more information and a customized simulation, please contact the OpsNow team.