The ITPro Podcast

Cybersecurity teams are facing a double edged sword of challenges and opportunities. On the one hand, AI tools offer a great deal of autonomous working and the promise of automating some of the more laborious tasks that a cybersecurity team has to undertake.On the other hand, attackers are also using AI to launch large scale attacks such as sophisticated phishing campaigns and identity theft. To fight this threat, cybersecurity teams will need to unify data like never before and take advantage of as many new technologies and processes as they can.How can they go about this? And what does a unified cybersecurity strategy really look like in 2026?In this episode, Rory is joined by Mandy Andress, chief information security officer at Elastic, to explore how businesses can evolve their threat detection and security posture, as well as how AI is lowering the barrier to entry for attackers.Read more:In the age of AI threats, the future of security is unifiedAI-generated code is now the cause of one-in-five breaches – but developers and security leaders alike are convinced the technology will come good eventuallyAI-generated code risks: What CISOs need to knowAgentic AI carries huge implications for security teams - here's what leaders should knowThe NCSC touts honeypots and ‘cyber deception’ tactics as the key to combating hackers — but they could ‘lead to a false sense of security’

In the race to train and deploy generative AI models, companies have poured hundreds of billions of dollars into GPUs, chips that have become essential for the parallel processing needs of large language models.Nvidia alone has forecast $500 billion in sales across 2025 and 2026, driven largely by Jensen Huang, founder and CEO at Nvidia, recently stated that “inference has become the most compute-intensive phase of AI — demanding real-time reasoning at planetary scale”. Google is meeting these demands in its own way. Unlike other firms reliant on chips by Nvidia, AMD, and others, Google has long used its in-house ‘tensor processing units’ (TPUs) for AI training and inference.What are the benefits and drawbacks of Google’s reliance on TPUs? And how do its chips stack up against the competition?In this episode, Jane and Rory discuss TPUs – Google’s specialized processors for AI and ML – and how they could help the hyperscaler outcompete its rivals.Read more:

HPE Discover Barcelona 2025 was in full swing this past week, with thousands of attendees descending on the Fira Barcelona to hear the latest news on the networking, servers, storage, supercomputing – and, of course, AI.It’s a pivotal time for the firm, as it consolidates its hardware partnerships and heralds a recent acquisition, while laying out its strategy to help customers not only meet demand, but expand their networks and adopt new technologies.What are some of the biggest things HPE announced – and what does the firm have lined up for 2026 and beyond?In this episode, Rory interviews Jane live on the ground to unpack all things HPE.

As a business leader, you’d like to believe that your staff are entirely trustworthy. Effective enterprises run on workforce confidence – but in some cases, that trust can be misplaced.In November, CrowdStrike admitted one of its own employees had provided screenshots of internal systems to hackers in exchange for a sizable payout. Industry experts have told ITPro the incident should act as a wake up call to the all-too-serious risk of insider threats.Earlier in the month, websites all over the world went offline after a major outage at the content delivery network service provider Cloudflare. What was the cause of the incident: had Cloudflare fallen victim to the kind of DDoS attack it’s famous for preventing?In this episode, Jane and Rory welcome back Ross Kelly, ITPro’s news and analysis editor, to explore some of November’s biggest stories.FootnotesIf you're not taking insider threats seriously, then the CrowdStrike incident should be a big wake up callNearly 700,000 customers impacted after insider attack at US fintech firmAI means cyber teams are rethinking their approach to insider threats‘Insiders don’t need to break in’: A developer crippled company networks with malicious code and a ‘kill switch’ after being sacked – and experts warn it shows the huge danger of insider threatsEverything you need to know about CloudflareThe Cloudflare outage explained: What happened, who was impacted, and what was the root cause?Cloudflare says AI companies have been “scraping content without limits” – now it’s letting website owners block crawlers and force them to paySecurity experts issue warning over the rise of 'gray bot' AI web scrapersCloudflare is fighting back against AI web scrapersNearly half of all digital initiatives still fail – here’s how you can learn from the ‘digital vanguard’ and deliver successSubscribe to the IT Pro newsletter

It seems that everywhere you look these days, businesses are implementing AI features, tools, chatbots, and pilots. But researchers keep coming to the same conclusion about the benefits of enterprise AI adoption – that return on investment is slim to none.While this isn’t the case for every business, it’s certainly a worry that hangs over discussions of the technology. The secret to making AI projects succeed is knowledge that every leader is after right now – and knowing what not to do is just as important.Where are businesses going wrong with AI adoption? And how can they apply the learnings of the past few years to ramp up return on investment?Today, we’re joined by Alan Trefler, founder and CEO at Pegasystems, to unpack the main hurdles businesses face when it comes to AI adoption – and why AI failure is becoming such a widespread concern.In this episode, Jane and Rory speak to Alan Trefler, founder and CEO at Pegasystems, to unpack the main hurdles businesses face when it comes to AI adoption – and why AI failure is becoming such a widespread concern.