This week's issue of the technology publication goes deep into the most pressing developments in the IT landscape, focusing on three major stories that are reshaping how organisations approach security, digital transformation, and artificial intelligence. The lead feature examines the Home Office's ambitious blueprint for modernising UK policing through technology, while an exclusive interview with the global CIO of a leading hardware manufacturer reveals how the company is pivoting toward services. Rounding out the issue, a special Security Think Tank article provides practical guidance for buyers navigating the crowded AI security market.
Home Office Unveils Sweeping Police Technology Overhaul
The Home Office has announced a comprehensive reform programme that will significantly expand the use of artificial intelligence and facial-recognition technologies across UK policing. The plans, part of a wider effort to modernise law enforcement, include new funding for AI-driven analytics tools that can process vast amounts of surveillance data in real time, as well as a national framework for the ethical deployment of facial recognition.
Under the proposals, police forces will gain access to advanced algorithms that can automatically flag suspicious behaviour from CCTV feeds, predict crime hotspots, and streamline administrative tasks. The Home Office argues that these technologies will free up officers for frontline duties and help reduce the time spent on paperwork. However, civil liberties groups have raised concerns about the potential for bias in AI systems and the impact of mass surveillance on privacy rights. The reforms also include a new code of practice for the use of live facial recognition, requiring forces to obtain judicial approval before deploying the technology in public spaces.
Industry analysts have noted that the announcement reflects a broader global trend toward algorithmic policing, with similar programmes underway in countries such as the United States, China, and Singapore. The UK’s approach, which emphasises a balance between innovation and oversight, may serve as a template for other nations. The Home Office has committed to a public consultation process before implementing the most controversial measures, and a parliamentary committee is expected to scrutinise the plans in the coming months.
The move comes at a time when UK police forces are under pressure to improve efficiency amid budget constraints. Proponents argue that AI can help close the gap between rising demand and limited resources, while sceptics warn that rushing to adopt unproven technology could lead to costly mistakes and erosion of public trust. The issue also highlights the need for robust data governance and transparency, as the success of these reforms will depend heavily on public confidence in how the technology is used.
Interview: Lenovo’s Global CIO on Building a Services Powerhouse
In a revealing interview, the global CIO of Lenovo outlined his strategy for transforming the company from a hardware-centric manufacturer into a major player in IT services. Art Hu, who oversees technology across the $70 billion corporation, discussed how his team is leveraging internal digital transformation initiatives to build scalable services offerings for external clients.
Hu, who has held the role since 2021, previously led IT at Hewlett Packard Enterprise and brought a services-oriented mindset to Lenovo. He noted that the company’s services business now accounts for roughly 30% of revenue, up from less than 15% five years ago. This growth has been driven by a combination of managed infrastructure services, device-as-a-service models, and cloud consulting. Hu emphasised that the key to success has been treating internal IT as a proving ground for new offerings, allowing the company to refine its approach before taking it to market.
One of the most significant initiatives under Hu’s leadership has been the migration of Lenovo’s own enterprise systems to a hybrid cloud architecture, which has reduced application deployment times by 40% and cut infrastructure costs by 25%. These internal wins have been packaged into a set of services that Lenovo now sells to other large enterprises facing similar modernisation challenges. Hu also highlighted the role of AI in the services portfolio, with tools that automate IT operations and provide predictive maintenance for hardware.
Looking ahead, Hu sees the biggest opportunity in helping clients manage the complexity of edge computing and remote work environments. He argued that many organisations are struggling to secure and manage distributed devices, and Lenovo’s combination of hardware expertise and service delivery capabilities gives it a unique advantage. The interview also touched on the challenges of scaling a services business in a competitive market dominated by players like Dell, HPE, and IBM. Hu believes that Lenovo’s cost structure and manufacturing scale provide a differentiator, but he acknowledged that cultural change within the company has been essential to the transition.
The conversation underscores a broader shift in the technology industry, where vendors are increasingly moving from one-time product sales to recurring revenue models. For Lenovo, the bet on services is a bet on long-term customer relationships and higher margins. The company’s experience offers lessons for other hardware manufacturers seeking to diversify their revenue streams in an era of plateauing PC sales.
Security Think Tank: How to Buy AI Security – Focus on Outcomes, Not Technology
The Security Think Tank feature in this issue tackles a question that is top of mind for every CISO: how to separate genuine AI-driven security solutions from the hype. With hundreds of vendors claiming to use artificial intelligence, the article argues that the smartest approach is to stop focusing on the technology itself and instead demand clear evidence of the outcomes it delivers.
Written by a veteran security researcher, the piece draws on years of experience evaluating security products and advises buyers to ask three critical questions before making a purchase: What specific problem does the AI solve? How is the AI trained and validated? And can the vendor provide case studies showing measurable improvements in detection rates, response times, or cost savings? The article warns that many products simply rebrand traditional machine learning algorithms as “AI” without adding meaningful new capabilities.
One of the key insights is that AI is most effective when applied to narrow, well-defined tasks such as malware classification, phishing detection, and user behaviour analytics. Broad claims about AI being able to “stop all cyberattacks” should be treated with deep scepticism. The article also highlights the importance of explainability, noting that security teams need to understand why an AI flagged an alert in order to investigate and respond effectively. Black-box models that provide no reasoning are a liability in high-stakes environments.
The piece also covers the operational realities of integrating AI into existing security stacks. It points out that AI tools often require significant tuning and ongoing maintenance, and that organisations should budget for the necessary expertise. Some vendors are now offering managed detection and response services that include AI as part of a broader human-led service, which can be a more practical option for smaller teams.
For CISOs building a security budget, the article recommends starting with a small proof of concept focused on a single use case, using clear success metrics tied to business outcomes such as mean time to respond or reduction in false positives. This approach, the author argues, will yield better results than trying to deploy a large-scale AI platform without a clear strategy. The takeaway is clear: AI is not a magic wand, but a powerful tool when deployed with discipline and a focus on measurable results.
Source: Computerweekly News