4 Salesforce DevOps Predictions in 2024

By Esko Hannula

The future of Salesforce looks exceptionally fun this year. AI is rapidly shaping our work, enabling things we cannot even imagine yet and creating inflated expectations. Last year, the majority of enterprises maintained a conservative IT development budget, seeking cost reductions rather than new opportunities. 

Then, almost overnight, ChatGPT popularized large language models and complex AI technologies, opening the eyes of business leaders to see the opportunities ahead and jump on a bandwagon that’s too exciting to miss. Here are four exciting predictions that I’ll be betting on this year for Salesforce DevOps…

1. AI as a Team Member

We are witnessing the emergence of AI-enabled tools that promise to improve programmer productivity, and I’m sure most of them will deliver on that promise. Still, towards the end of the year, we’ll begin to understand that, in complex and agile software efforts, team collaboration has an even more significant impact than individual productivity and that not all individuals are programmers. 

After all, programmers spend a lot of time finding information, making sense of it, waiting for something, and fixing problems caused by someone else.

AI will undoubtedly change the development team dynamics, but it’s still unclear how. Many believe that AI will make hardcore developers obsolete as business analysts and junior developers can build applications with the help of AI. It is equally likely that AI will make low-code developers obsolete because business analysts and even business owners can describe to AI in plain English what they want, and the hardcore developer can fill in those parts that may be too hard for the AI. This is particularly possible in Salesforce, where the underlying platform takes care of a good part of the systemic complexity that AI can’t grasp yet.

I don’t believe any development role will become obsolete. Rather, AI will make competent developers much more productive, thus growing the gap between top and low performers.

2. Platform Engineering and Composability

Platform engineering has been a big fuzz in IT circles during the past couple of years, and many perceive it rightfully as the next step after DevOps. It has been less relevant in Salesforce because it already takes care of many things that may require a dedicated platform engineering team in some other environments.

Meanwhile, the complexity of Salesforce-based applications keeps growing, integrations with other systems are many, and applications contain a good amount of source code.

The idea of composability, i.e. rapidly assembling new digital business processes from existing building blocks, is a driving force behind platform engineering. Composability is also becoming more relevant in Salesforce, and technologies such as Salesforce Packaging make it practical.

I am not expecting any revolution in Salesforce application development, but many indicators suggest that Salesforce architects will benefit from learning and progressing the principles of platform engineering.

READ MORE: What Does a Salesforce DevOps Engineer Do?

3. Autonomous Software Testing

As Salesforce developers enjoy the platform’s benefits, their applications, at least the simplest ones, require less testing than many other applications. But as the complexity of applications grows, so does the need for testing. Testing is slow, expensive, and, for most people, not fun. There’s no time to test because businesses need that new feature as soon as possible. Later on, they’ll be upset because it didn’t work as expected; testing more thoroughly is imperative.

AI will make a significant impact on testing. We are moving from automated testing to autonomous testing. Eventually, but maybe not yet in 2024, testing tools can design and analyze tests rather than just execute them. AI will monitor the actions of human testers or ordinary users, learn the application, and design tests. While developers have AI assisting them, humans will assist AI in testing.

4. Greed vs. Privacy

Privacy is a big concern for anyone considering AI for serious business use, and for a good reason. While I wouldn’t say I like the idea of greed beating privacy, I predict it will happen. When cloud-based email was new, every corporation said it was too high a risk on security and privacy. Then, their CFOs saw the savings potential, and the risks magically vanished. Something similar is likely to happen with AI. The benefits businesses can reap are huge, and the cost of remaining a laggard is enormous, too. I almost hope I am wrong with this last prediction.


AI-driven advancements in DevOps, for both positive transformations and ethical considerations, will take place rapidly this year. While the emergence of AI-enabled tools promises to enhance programmer productivity, we can’t ignore team collaboration in complex projects and the growing relevance of platform engineering and composability. The excitement of going from automated to autonomous software testing will be one benefit of AI that will significantly increase productivity

But it’s no surprise. We’ve been waiting for it, right? 

READ MORE: Adopting DevOps: The 5 Steps to Success

The Author

Esko Hannula

Esko is Senior Vice President, Product Management at Copado.

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