Embracing Pragmatism: Navigating the Path to New Technology Adoption

Pragmatic Approach Needed for Adoption of Artificial Intelligence

Introduction

The recent surge in hype around artificial intelligence (AI) has generated high expectations about its potential to revolutionize various industries. However, for AI to have a meaningful impact on organizations, it is crucial to approach its adoption in a pragmatic way, learning from past experiences with new technologies. This article draws parallels between the adoption of cloud computing and security automation to emphasize the importance of a well-defined implementation strategy for AI.

The Cloud Migration Strategy

Cloud computing was initially met with skepticism, with concerns about data security and loss of control over infrastructure. However, over time, organizations realized the benefits and efficiencies offered by the cloud. The shift in focus from “if” to “how” paved the way for the development of cloud migration strategies and implementation plans. Today, multi-cloud strategies have become the norm. This process required time and lessons learned about the best approach to adopt new technologies in order to gain traction.

Security Automation

Similar to the early days of cloud adoption, security automation faces barriers to adoption, such as lack of expertise and fear of failure. To overcome these challenges, a pragmatic approach is necessary. The author suggests the following steps for implementing security automation effectively:

1. Identify Use Cases

Organizations should first identify the specific problems they want to solve through automation. This helps in setting a clear scope and breaking down the automation process into smaller, manageable chunks.

2. Start with a Small Scope

It is important to resist the temptation to make the automation process overly complex. By starting with a small scope and focusing on atomic-level automation, organizations can gain confidence and test the effectiveness of the automation in addressing specific use cases.

3. Expand Automation Incrementally

After gaining confidence in the initial use case, organizations can gradually expand automation to other use cases. Building on contextualized data, organizations can add discrete tasks based on triggers and thresholds defined by the selected use cases. This approach allows organizations to avoid complexity and derive meaningful value quickly.

Applying the Lessons Learned to AI Adoption

As AI adoption gains momentum, it is important to reflect on the lessons learned from past technology implementations. The author emphasizes the need for a specific and pragmatic implementation approach to realize value from AI. Despite the uncertainties surrounding this emerging technology, having exciting opportunities ahead and a clear path can lead to a bright future.

Conclusion

In navigating the adoption of new technologies, pragmatism is key. Drawing lessons from the cloud migration and security automation journeys, organizations can develop solid implementation strategies for AI adoption. By identifying use cases, starting with a small scope, and expanding incrementally, organizations can overcome barriers to adoption and efficiently harness the potential of AI.