It seems we can no longer trust our own eyes and ears. For years, the tech industry has been on a relentless march, promising a future of seamless digital interaction. Well, that future is here, and it’s brought along a rather nasty, shape-shifting party guest: the deepfake. The very artificial intelligence that has given us incredible creative tools is now being used to generate hyper-realistic fake videos and audio clips designed to deceive, defraud, and disrupt. This isn’t some far-off science fiction plot; it’s the new reality, forcing a critical need for AI deepfake detection and turning our digital world into the front line of a new kind of conflict.
At the centre of this storm are the companies tasked with keeping us safe online. And one of the old guard, Gen Digital—the behemoth behind Norton and Avast—is making some very loud noises about its new arsenal. But in this escalating AI-fuelled war, can a legacy titan really keep pace?
The Escalating Cybersecurity Arms Race
Let’s be clear: the notion of a cybersecurity arms race isn’t new. It’s been a cat-and-mouse game between hackers and security firms for decades. But AI has thrown a massive canister of petrol on that fire. We’re now in a state of AI versus AI. Malicious actors are using generative AI to create phishing emails so perfect they could fool a linguistics professor, and deepfakes so convincing they could start a family argument or, more frighteningly, a geopolitical incident. The game has been fundamentally upended.
This is where the concept of content authentication moves from a niche academic interest to an absolute necessity. How do you prove that the person on the other end of that video call is actually your boss and not a digital puppet asking for an urgent bank transfer? How does a bank verify a caller’s identity when their voice can be cloned from a five-second clip posted on social media? Traditional security, like antivirus software that scans for known malicious files, is like bringing a sword to a drone fight. It’s completely outmatched. The response, therefore, must also be AI-driven. Security software now needs to be intelligent, learning and adapting in real-time to spot the subtle, almost imperceptible flaws in faked content.
Why Spotting the Digital Forgery Matters
So, what exactly is AI deepfake detection? Think of it like a digital art authenticator on overdrive. For centuries, experts have verified masterpieces by analysing brushstrokes, the age of the canvas, and the chemical composition of the paint. They look for the tiny, tell-tale signs of a forgery that a casual observer would miss. AI detection tools do something similar, but for pixels and soundwaves. They analyse video for unnatural blinks, strange lighting inconsistencies on a person’s face, or bizarre digital artefacts where the AI has ‘painted’ something incorrectly. For audio, it listens for the flat, non-human cadence or the lack of subtle background noise that betrays a synthetic voice.
The risks if we get this wrong are monumental. We’re not just talking about embarrassing memes. We’re talking about sophisticated fraud. Imagine a CEO’s voice being cloned to authorise a multi-million-pound transfer. Or a politician’s likeness being used in a fake video days before an election to spread disinformation. This technology strikes at the very heart of trust, the invisible thread that holds our digital society together. Without reliable content authentication, every video call, voice note, and image becomes suspect. An environment of zero trust is not a functional one.
Gen Digital’s Big AI Bet
This brings us to Gen Digital (GEN). To many, the company is synonymous with the pop-ups for Norton Antivirus that have graced our computer screens for what feels like an eternity. But as a recent analysis from Simply Wall St. highlights, the company is desperately trying to shed its old skin. Gen Digital has recently rolled out a suite of new AI-powered tools, including its own AI deepfake detection service and an expanded version of Norton Scam Protection. It’s a very public declaration that they intend to fight on this new AI-driven battlefield.
The market, however, seems a little uncertain. The company’s stock price has taken a hit, dropping around 7% in the past month. But is this short-term jitters, or a sign of deeper trouble? Look at the bigger picture, and the story changes. Gen Digital has delivered a 27.6% total shareholder return over the past three years and an impressive 48.7% over the past five. This isn’t a company on the verge of collapse; it’s a company in the middle of a painful but potentially lucrative transformation.
Analysts seem to agree. The same Simply Wall St. report points to a fair value estimate of $33.74 for Gen Digital’s stock, suggesting a potential upside of over 26% from its current price. Why the optimism? It’s all about the strategy.
The Inevitable Shift to Subscriptions
Gen Digital, like so many others in the software world, is going all-in on subscriptions. This is less of a clever business pivot and more of a survival imperative. The old model of selling a box with a CD-ROM in it (or its digital equivalent, a one-time download) is dead. Cybersecurity isn’t a product you buy once; it’s a service you need continuously. The threats evolve daily, so the defences must too.
A subscription model creates a recurring, predictable revenue stream, which investors absolutely love. More importantly, it creates a direct, ongoing relationship with the customer. It transforms the company from a simple vendor into a security partner. This model allows Gen Digital to constantly update its services, pushing out new detection algorithms for the latest deepfake generation techniques and refining its Norton Scam Protection to recognise new phishing tactics. This ongoing revenue and customer lock-in is a huge part of why analysts see long-term value, even with the recent market turbulence. It’s what makes a company defensible in a brutally competitive market.
But Is It All Smooth Sailing?
Of course not. This is the tech industry, after all. AI is not some magical pixie dust you can just sprinkle on an old business model. There are significant hurdles that Gen Digital must navigate.
– A Messy Integration: Gen Digital is the product of the massive merger between NortonLifeLock and Avast. It has also been integrating other technologies, like a financial wellness platform from MoneyLion. Melding different company cultures, legacy codebases, and sprawling product portfolios is an enormous- and often underestimated- challenge. Will these moving parts work together seamlessly, or will they just create a bloated, inefficient organisation?
– The Weight of Legacy: Can a company of this size and age truly innovate at the speed required? The cybersecurity arms race is being fought by nimble, hyper-focused startups that were born in the AI era. Gen Digital has the scale and customer base, but it also has the baggage of a corporate giant. Agility is not typically its strong suit.
– Fierce Competition: Let’s be honest, everyone is bolting “AI” onto their security products. From Microsoft, which is building security directly into its operating system, to a thousand hungry startups, the market is incredibly crowded. Gen Digital will have to do more than just offer AI deepfake detection; it will have to prove its solution is materially better than everyone else’s.
This is the central tension in Gen Digital’s story. It is making all the right moves on paper: embracing AI, shifting to subscriptions, and tackling the most modern threats. But execution is everything. The road ahead is littered with risks that could easily trip them up.
The battle for digital truth is only just beginning. The moves by companies like Gen Digital show that the established players are taking the threat of AI-generated fakes seriously. Their success or failure will have profound implications for all of us. But this isn’t just their fight. As our lives become increasingly digitised, we all have a stake in ensuring that we can still believe what we see and hear.
The proliferation of these tools means that the
responsibility for content authentication will inevitably fall, at least partially, on us as individuals. We will need to become more critical consumers of media, armed with both scepticism and the right tools. The question is no longer if you will encounter a deepfake, but when. How prepared will you be when you do?
