Security & Monitoring
monitoring. We can also expect to see AI reflected more in industry standards, and there may be some greater controls, especially in applications related to human safety, such as restricting the types of AI used or requiring greater explainability or fine-tuning of AI models. Those environments aside, there are already many examples of use cases in the electronics industry that could start using AI more right now, if the right governance is in place. Most teams start by adopting an AI model that is already available instead of attempting to build something from scratch, and there are lots of options available, including open-source models, which can be a launchpad to train and fine-tune.
Building an AI governance culture So, what does that mean in practice? Having experienced AI for over a quarter century and leading the Perforce AI Innovation Council, I am involved in AI’s implementation safely every single day and am experiencing fi rst- hand what does and does not work. First, while not every company is going to need a dedicated AI council, at the very least there needs to be a person or team with specifi c responsibility for AI, such as setting policies
and tracking progress. Increasingly, we are seeing job titles like chief AI offi cer (CAIO) and AI offi cer emerge.
The way AI works will also mean looking at new ways to protect intellectual property (IP). For example, rather than a software engineer writing code, they will be using prompts to get what they want from AI. Therefore, those prompts become IP, and as we are finding, can be significant in volume - for instance, covering the data that has been pulled together around a particular use case. Without special care, AI can be tricked into exposing prompts directly and therefore potentially giving IP to a competitor.
Second, there needs to be a culture where employees are encouraged to review new AI developments regularly and be open-minded about what they may have to offer. What people may have dismissed as being immature or inefficient six months ago might be perfectly fit for purpose today. So, it is important to convince people to leave their comfort zones and repeatedly take a fresh look at what AI offers regularly. That approach should also extend to the increasing range of tools that can be used to fine-tune and secure AI more effectively.
Enterprise-wide input
Also, people from across the organisation should be involved when making decisions around AI adoption and governance so that risk is considered not just on a technology level but enterprise-wide to give a 360 view. Within our own council, we have representation from legal, finance, marketing, and beyond, looking at opportunities across the company, such as how we reduce tedious, manual tasks to free up human time for more valuable activities. In addition, when I first formed the council, I carried out a series of one- to-one interviews to identify areas causing delays, barriers, or frustrations and how we could use AI to remove those limitations or friction points.
However, AI’s true potential is not at a feature or single process level. When thought of more strategically, it can be a complete game-changer. Questions we are also asking ourselves revolve around not just improving existing processes but replacing them with a better way of achieving certain objectives.
For instance, testing has traditionally been a bottleneck in the software development lifecycle. Continuous,
automated, and low-code/no-code developments in recent years have helped to some extent, but we are now looking at eliminating the need to write test scripts (in other words, code) altogether, supported by natural language processing. So, anyone will be able to carry out vast volumes of software tests without needing any skills and at near-zero touch. That represents a huge step forward.
Clearly, AI has vast potential, but it also needs a huge amount of consideration and control, and many businesses are understandably struggling to know where to start. This is why it is also important for vendors like us to provide guidance where we can, not only to build AI into our solutions but also to share our experiences so far. Increasingly, an AI-first mentality will be necessary for our collective success, with governance firmly embedded within that approach. AI is one of the most transformative steps in technology’s history, bringing benefits and risks, so we need to collaborate in order to collectively navigate its adoption as efficiently, safely and securely as possible.
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Components in Electronics
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