For decades, OSS has followed the same pattern: design, then keep adding lots more “baked-in” capabilities into a complex OSS UI, process inputs, generate outputs. At incredible scale. We made them faster, (somewhat) more automated, and vastly more scalable. But we never made them think. Until now… If… (we’ll come back to the if shortly).
But first, I’d like to share a concept from Greg Isenberg that is the inspiration for today’s article:
“Excel could crunch a million numbers but couldn’t tell you what they meant. Photoshop had infinite features but couldn’t suggest which ones to use. Salesforce could track every customer interaction but couldn’t tell you why deals were slipping.Even the “AI features” were just matching patterns. Spotify wasn’t understanding music – it was just copying what similar humans liked.Everything was garbage in, garbage out. Software was only as smart as the human using it.Then 2022 happened.For the first time, software started thinking. Actually thinking.”
OSS have traditionally been rule-based, relying on predefined (and pre-designed – by humans) sequences of workflows, thresholds and alarms to manage network operations. These systems have always excelled at processing vast amounts of telco data, but it’s safe to say that those algorithms never truly understood it. Every action was dictated by those human-defined rules.
However genAI tools have introduced an important shift. OSS can potentially now go beyond static rules and start thinking. Instead of simply executing commands based on if-then logic, AI-driven OSS can:
We stand on the precipice of OSS no longer just being a tool for executing predefined operations – it’s evolving into a cognitive system that can interpret, learn, and act dynamically (even largely autonomously).
Automation has been a core principle of OSS evolution since the first OSS began to appear around 50 years ago. They were built around the foundational principles of reducing manual effort and increasing operational efficiency. However, there’s one significant drawback – traditional automation is limited – it still requires humans to understand all the nuances / variants of a workflow. From there, the human needed to define process maps, set thresholds and interpret outputs. AI changes this by enabling adaptation and iteration rather than just prescribed automation.
This transition means OSS don’t have to have baked-in capabilities – via static automation scripts. They can evolve and respond to an ever-changing telecom landscape without requiring constant human intervention. AI doesn’t just execute processes; it has the potential to evolve and adapt to them.
We bang on about complexity A LOT here on this blog. As an industry, we seem to have a hard-wired need to add layer after layer of complexity into our modern telecom networks. Since OSS are largely downstream of those architectural and procurement decisions, sophisticated decision-making has become an increasingly critical imperative for OSS to cope with. Arguably an imperative that static rules are struggling to keep pace with. Traditional systems process vast amounts of data but lack the ability to derive meaning and make intelligent in-flight decisions at scale. AI introduces a new paradigm where OSS doesn’t just manage data—it interprets and acts on it intelligently.
AI has caused such a profound change that if nothing else, it should be a trigger point for OSS buyers and sellers to totally revisit and reframe their OSS strategy (see our previous article on the hows and whys of conducting a reframing exercise at the start of any project). We have the opportunity to think in different patterns – to think about designing systems and user interfaces that aren’t constrained by predefined rules and human interpretation like OSS of the past. To start looking through the lens of OSS being truly intelligent systems – one that can think, learn, and evolve.
The move from Yahoo to Google to GenAI to find answers to your questions is a perfect example of re-framing.
The video below is another example:
The shift is already happening. As AI capabilities continue to proliferate, OSS will no longer be about processing telco data at scale – they will be about understanding, anticipating, and optimising telecom operations – thinking in ways that were never possible before.
The age of the thinking OSS has begun. The question is no longer if AI will transform OSS, but how fast and how much you / me / we will inspire it to happen.
There’s no doubt we’re at an important crossroad right now. In the words of legendary AFL Coach Allan Jeans,
“In every game there is going to be a crossroad and when you get to that crossroad you either step up or you step down”
We’ll be announcing more details shortly, but last week PAOSS established a partnership agreement with an organisation with unique skills across AI, Web3.0 / smart-contracts, telco and energy. Together we aim to step up and help bring more AI-infused, thinking OSS into operation for network operators globally.
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