Luca Maraschi is the cofounder and CEO of Platformatic.
Customer-facing applications and operations often receive the lion’s share of attention, but backend operations are the lifeblood of many companies, products and services. As a result, backend operations are prime for reinvention, using AI to make them more innovative, efficient and smarter.
Despite the promise of using AI to drive the modern intelligent digital platform, many companies still struggle to make the various pieces fit together in a way that can benefit them. To overcome this challenge, there are several things leaders must keep in mind.
AI Will Not Replace People
The common debate about AI is whether or not it will replace human beings. This makes some leaders reluctant to adopt it, while others are racing to—all depending on which side of the debate they fall on.
The reality is that AI will not replace humans wholesale. Instead, it will empower tech teams, enabling them to make decisions and take action more efficiently. We believe this is the biggest opportunity for implementing AI, helping guide developers and engineers as they transform operations.
Use AI To Automate Operations
Let’s face it: operations can be boring. Operations usually involve a slew of repetitive tasks that can take their toll on the developers and engineers. In contrast, AI excels at handling repetitive tasks, presenting an opportunity to use it to streamline operations.
Using AI in this manner benefits the entire organization. CTOs and tech leaders gain improved efficiency, scalability and resource optimization. For developers and engineers, rather than being replaced, AI frees them to do more creative and rewarding work.
Predictability: The Cornerstone Of Backend Operations
Predicting scenarios is another area where AI excels, and where humans traditionally struggle. AI can use vast quantities of data to spot trends and extrapolate possibilities at a fraction of the time it would take a human.
Backend operations should employ AI to do just that, using data analytics and predictive modeling to anticipate issues and take measures to address them before they become a problem.
For example, it’s a common belief that you can’t make fast changes to backend infrastructure without breaking things. My co-founder and I wrote a white paper illustrating how AI can help organizations do just that by analyzing the maze of interconnected apps, services and dependencies and predicting the impact changes would have. Using AI for this type of application breaks the mold, giving companies the ability to make quick changes without disrupting their operations.
Similarly, AI excels at predicting what customers want, presenting an opportunity to use it to serve personalized content and experiences.
Reduce Variance And Ensure Consistency And Reliability
Just as AI is an ideal solution for repetitive behavior, it is also the ideal tool to reduce variance and ensure consistent and reliable outcomes. This is especially true when paired with standardized protocols and procedures.
The real-world implications of this include improved system stability, security and performance, especially in backend operations where those factors often matter most.
AI is here to stay and represents a monumental leap forward for backend operations. Rather than replacing people, the technology can and will be used to automate repetitive tasks, free up personnel for more important things, provide predictive analysis and reduce variance. In short, AI is redefining backend operations in a way that was previously unimaginable.
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