The ITPro Podcast

We’re just over a week into 2026 but already, enterprise cybersecurity teams will be hard at work repelling attacks – and business leaders will be worrying about the year ahead.On the one hand, we’re told that AI tools are beginning to empower security teams to go further and faster. On the other, the use of AI by hackers to launch attacks also appears to be on the rise.All of this is happening against a backdrop of rising geopolitical tensions and continual attacks by state-sponsored hacking groups against businesses. How will all this come together in 2026 and beyond?In this episode, Jane and Rory are joined by Jamie Collier, lead advisor in Europe at Google Threat Intelligence Group, to explore the risks – both novel and ordinary – enterprises face in 2026.Read more:NCSC issues urgent warning over growing AI prompt injection risks – here’s what you need to knowCyber experts have been warning about AI-powered DDoS attacks – now they’re becoming a realitySalt Typhoon attack on US congressional email system ‘exposes how vulnerable core communications systems remain to nation-state actors’OpenAI says prompt injection attacks are a serious threat for AI browsers – and it’s a problem that’s ‘unlikely to ever be fully solved'OpenAI turns to red teamers to prevent malicious ChatGPT use as company warns future models could pose 'high' security riskA flaw in Google’s new Gemini CLI tool could’ve allowed hackers to exfiltrate dataGoogle says you shouldn't worry about AI malware – but that won’t last long as hackers refine techniquesNorth Korean IT workers: The growing threatNorth Korean hackers...

As we ring in the new year, we’re returning to the ITPro tradition of looking ahead and discussing the key trends that will shape the tech sector in 2026.While there will undoubtedly be surprises ahead, both exciting and concerning, it’s also possible to look at some of the standout moments from 2025 to help us understand where we’re headed.So what can we expect IT decision makers to come up against in 2026?For this new year’s edition of the podcast, Jane and Rory welcome back Ross Kelly, ITPro’s News and Analysis Editor, to discuss the key trends that will shape 2026.FootnotesAI adoption is finally driving ROI for B2B teams in the UK and EUAI is finally delivering bang for its buck, according to MicrosoftUK firms are pouring money into AI, but they won’t see a return on investment unless they address these key issuesFormer NCSC head says the Jaguar Land Rover attack was the 'single most financially damaging cyber event ever to hit the UK' as impact laid bareIf you're not taking insider threats seriously, then the CrowdStrike incident should be a big wake up callNorth Korean IT workers: The growing threatUS Department of Energy’s supercomputer shopping spree continues with Solstice and EquinoxInside Isambard-AI: The UK’s most powerful supercomputerNvidia just announced new supercomputers and an open AI model family for science at SC 2025

2025 has almost come to a close and the new year is right around the corner.At this time of year, it’s usual to reflect on the year and consider some of the biggest, most impactful things that have happened. But here at ITPro, we like to take a different approach: what didn’t happen?The tech industry can’t help but make bold promises and some just don’t pan out. What are some of the biggest targets, trends, and predictions that just haven’t come to fruition in 2025?In this episode, Jane and Rory are once again joined by Ross Kelly, news and analysis editor at ITPro, to discuss the biggest misses of the year.Read more:Is enterprise agentic AI adoption matching the hype?‘Agent washing’ is here: Most agentic AI tools are just ‘repackaged’ RPA solutions and chatbots – and Gartner says 40% of projects will be ditched within two yearsAgentic AI carries huge implications for security teams - here's what leaders should know'It's slop': OpenAI co-founder Andrej Karpathy pours cold water on agentic AI hype – so your jobs are safe, at least for nowIBM is targeting 'quantum advantage' in 12 months – and says useful quantum computing is just a few years awaySAS thinks quantum AI has huge enterprise potential – here's whySAS rejects generative AI hype in favor of data fundamentals at Innovate 2025Post-quantum cryptography is now top of mind for cybersecurity leadersWhy does Nvidia have a no-chip quantum strategy?Meta executive denies hyping up Llama 4 benchmark scores – but...

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: