The latest edition of Computer Weekly takes a deep dive into the technology reforms that the Home Office is rolling out across UK policing. Under the banner of its wide-ranging modernisation programme, the government agency plans to accelerate the deployment of artificial intelligence, facial-recognition systems, and data analytics tools. These measures aim to improve crime prevention, investigation efficiency, and public safety. However, they also raise significant privacy, ethical, and civil liberties concerns that are being debated by Parliament, privacy advocates, and technology experts.
The Home Office’s strategy includes the introduction of a national police cloud platform to centralise data sharing, increased use of automated number plate recognition, and expanded live facial recognition in public spaces. AI algorithms will be deployed to analyse CCTV feeds, social media content, and crime patterns to predict and prevent offences. The reforms also call for a new digital forensics capability to handle the rising volume of digital evidence from smartphones, computers, and Internet of Things devices. Additionally, a national biometrics strategy will govern the use of fingerprints, DNA, and facial images across forces.
In parallel, the Home Office is investing in a unified command and control system that integrates emergency services communications. The Police Digital Service, a newly formed body, will oversee the implementation of these technologies, working with forces to standardise procurement and reduce duplication. Critics argue that the rapid adoption of AI and biometric surveillance without adequate safeguards could lead to disproportionate targeting of minority communities, errors in identification, and a chilling effect on lawful protest. The government maintains that all deployments will be subject to strict codes of practice, independent oversight, and compliance with the Equality Act and data protection laws.
Interview: Art Hu, Global CIO, Lenovo
In another feature, Computer Weekly speaks with Art Hu, the global chief information officer of PC, server, and storage manufacturer Lenovo. Hu explains how he is leveraging his experience of internal technology transformation to drive the company’s growing services business. Lenovo, traditionally known for hardware, is pivoting towards higher-margin offerings such as managed services, cloud solutions, and AI-as-a-Service. Hu’s role involves aligning the IT organisation with the company’s strategic goal of becoming a “solutions and services-led” enterprise.
Hu, who joined Lenovo in 2021 after leadership roles at Microsoft, Mars, and Citibank, previously led the creation of a global digital workplace and modernised the company’s supply chain using AI and Internet of Things sensors. At Lenovo, he is applying those same principles to develop service platforms that can be offered externally. For example, the company now provides a “Device as a Service” (DaaS) model that bundles hardware, software, and lifecycle management into a monthly subscription. Hu notes that the key is to build robust, scalable, and secure technology foundations that can support both internal operations and external customer-facing services.
Hu emphasises that cybersecurity is a top priority, especially as Lenovo expands its services portfolio. The company has invested heavily in zero-trust architectures, AI-driven threat detection, and DevSecOps practices. He also discusses the importance of cultural change: moving from a product-centric to a customer-centric mindset requires new skills, incentives, and leadership behaviours. Lenovo is investing in training programmes, innovation labs, and partnerships with startups to accelerate this transformation. Hu sees the biggest opportunity in helping enterprises navigate the complexity of hybrid cloud, edge computing, and generative AI deployments.
Security Think Tank: Stop buying AI, start buying outcomes
The issue also features a Security Think Tank piece urging chief information security officers (CISOs) to cut through the hype around artificial intelligence in cybersecurity. Authored by Rik Ferguson, the article argues that many vendors are adding AI features to their products without clear evidence of improved security outcomes. Ferguson advises buyers to focus on the specific problems they need to solve—such as reducing false positives, automating incident response, or detecting unknown threats—and then evaluate whether AI is the right tool for that job.
The article provides a framework for assessing AI security products. First, CISOs should demand transparency about the training data, algorithms, and performance metrics. Second, they should require evidence of efficacy through independent testing, peer-reviewed studies, or real-world case studies. Third, they must consider the operational context: how will the AI integrate with existing security tools, workflows, and teams? Ferguson warns against “AI washing,” where basic rule-based systems are marketed as advanced machine learning engines. He also highlights the importance of data quality and governance: garbage in, garbage out applies acutely to AI-driven security analytics.
Other features in this CW+ Premium Content issue include a look at how the Royal Bank of Scotland turned an IT disaster into a catalyst for digital innovation, and a story on wearable technology proving its value on the front line for emergency services and field workers. The February 2026 edition also carries insights on who should get the technology vote in the UK General Election, and a preview of the world’s largest cloud contract competition. Each article is accompanied by expert commentary, data visualisations, and links to further reading for premium members.
Beyond the main features, the issue aggregates recent coverage from across the TechTarget network. In the CIO beat, articles discuss the AI factory model—a blueprint for enterprises to operationalise AI at scale—and the hidden costs of AI deployment, including data preparation, governance, and talent. A weekly news roundup covers OpenAI launches, AI lawsuits, and Pentagon alliances. For security professionals, there are deep dives into the economics of the dark web after a breach, and the trend of decoupling SIEMs from security log data feeds. Networking articles highlight AI-driven network management, the network behind the Kentucky Derby, and how to detect shadow AI in the enterprise.
Data centre coverage features progress in quantum computing at IBM Think 2026, with companies like Boeing and Allstate piloting quantum algorithms for optimisation and risk modelling. Another article examines the balance between automation and human oversight in AI data centres, arguing that while AI can optimise cooling, power usage, and workload placement, human governance remains essential to prevent unintended consequences and ensure ethical operation. Data management stories cover the top ten vector database use cases across industries, Alation’s new AI governance suite for compliance, and MongoDB’s latest capabilities to support AI workloads.
This comprehensive issue provides IT leaders, executives, and cybersecurity professionals with actionable insights into the most pressing technology trends shaping their industries. Each article is crafted to inform decision-making, spark debate, and offer practical guidance for navigating the complex digital landscape. The Home Office police technology plans, Lenovo’s services transformation, and the AI security think tank collectively underscore the theme of responsible innovation: leveraging advanced technologies while managing risks, building trust, and ensuring equitable outcomes.
Source: Computerweekly News