AI's Impact on UK Insurance, Media, Journalism, and Additional Sectors
Beyond the major sectors detailed elsewhere, AI is transforming numerous UK industries with varying degrees of impact. This page explores AI's effects on Insurance, Media & Journalism, and other significant sectors not covered in dedicated pages. The UK takes a sector-agnostic, outcome-based approach to AI regulation,[1] avoiding blanket rules for entire industries. Instead, the government focuses on understanding specific AI applications and their impacts before introducing legislation, recognizing that challenges and opportunities vary dramatically across sectors.
Some industries face immediate transformation. The health and pharmaceuticals sector[2] anticipates the most substantial AI loss potential over the next 8-10 years, followed by mobility and transport.[2] The IT sector,[2] as the first AI adopter, currently shoulders the majority of AI-related risks. Insurance leads adoption with 75% of firms already using AI[3] (Bank of England survey), using foundation models in 17% of use cases. Media and journalism employ over 313,000 people (2023)[4] with 56% of UK journalists using AI professionally weekly[4] and another 27% using it less frequently. These sectors demonstrate AI's broad reach across the UK economy.
AI's impact varies by sector characteristics. Industries involving routine cognitive tasks (insurance claims, data analysis, journalism research) experience higher automation potential, while sectors requiring physical presence, human judgment, or creative storytelling see augmentation rather than replacement. The common thread: workers who embrace AI tools and develop complementary human skills thrive, while those resisting transformation face declining opportunities. This page provides insights into sectors beyond our main coverage, helping workers across diverse industries understand AI's implications for their careers.
75% of UK insurance firms use AI for claims processing, risk assessment, fraud detection, and underwriting. AI automates routine claims evaluation, analyzes vast datasets for pricing accuracy, and detects fraudulent patterns humans might miss. Entry-level claims processors and data entry roles face displacement, while actuaries, underwriters handling complex risks, and AI specialists see growing demand.
56% of UK journalists use AI weekly, primarily for transcription, copyediting, and research. News agencies report 33% use automated text production. While AI handles routine reporting and back-end tasks, investigative journalism, original storytelling, and editorial judgment remain human-led. Concerns about jobs and trust persist as newsrooms shrink, graduate media positions down 22% in 2024.
Autonomous vehicles, predictive maintenance, and manufacturing automation transform UK automotive. Mobility and transport face significant AI impact over the next decade. Traditional manufacturing jobs decline as robots handle assembly, but engineers designing autonomous systems, EV specialists, and technicians maintaining AI-equipped vehicles see demand growth.
Health and pharma anticipate most substantial AI loss potential in coming years. AI accelerates drug discovery, analyzes clinical trials, and predicts treatment outcomes. Lab technicians and routine research roles face automation, while specialised researchers, regulatory experts, and clinical trial designers remain essential.
345,000 people work freelance in artistic, literary, and media industries (2024). AI generates music, assists with video editing, and creates visual effects, but original creative vision, performance, and cultural storytelling remain human domains. Entry-level production roles face pressure while established creatives use AI as a tool.
AI accelerates data analysis, automates experiments, and identifies patterns in vast scientific datasets. Research assistants handling routine data processing face displacement, but principal investigators, experimental designers, and scientists interpreting results and developing hypotheses remain critical to scientific advancement.
Pattern across sectors: Entry-level positions focused on data entry, document processing, routine analysis, and basic research face high automation risk. Insurance claims processors, junior journalists doing transcription, research assistants, and administrative roles decline as AI handles repetitive cognitive tasks efficiently.
Why at risk: AI excels at pattern recognition, data processing, and routine analysis. Entry-level positions serving as training grounds are disappearing as companies hire fewer juniors and expect higher initial skill levels from new employees.
Pattern across sectors: Mid-career professionals in roles AI can partially automate, underwriters, copy editors, lab technicians, market researchers, face pressure but aren't eliminated. These positions evolve, with AI handling routine aspects while humans manage complex cases and exceptions.
Why at risk: AI automates 30-50% of tasks in these roles, enabling companies to do more with fewer people. Workers who master AI tools remain valuable; those resisting technology face declining relevance and career stagnation.
Pattern across sectors: Senior professionals making strategic decisions, managing teams, handling crises, and exercising judgment in ambiguous situations remain secure. Chief underwriters, editors-in-chief, principal investigators, and department heads use AI as a tool but provide irreplaceable human leadership.
Why low risk: Leadership requires emotional intelligence, organisational politics navigation, strategic thinking in uncertainty, and accountability, capabilities AI cannot replicate. Experience and judgment become more valuable as routine work automates.
Pattern across sectors: Data scientists, machine learning engineers, AI ethicists, and technical specialists implementing AI systems face explosive demand across insurance, media, healthcare, and every sector adopting technology. Skills shortage is universal constraint on AI adoption.
Why low risk: Every industry needs people who can build, train, validate, and maintain AI systems. Technical expertise commands premium salaries across sectors, with demand far exceeding supply for qualified specialists.
Pattern across sectors: Investigative journalists, original storytellers, artists creating novel work, and researchers developing new hypotheses remain valuable. AI assists with execution but cannot originate truly creative, culturally relevant, or scientifically groundbreaking work requiring human insight.
Why low risk: Creativity, cultural understanding, ethical judgment, and original thinking resist automation. While AI generates content, humans create work with meaning, cultural resonance, and genuine innovation.
Regardless of sector, common patterns emerge for navigating AI transformation:
Key insight: AI's impact patterns are remarkably similar across diverse sectors. Entry-level routine work faces highest risk, strategic leadership and technical specialists are most secure, and workers who combine AI proficiency with uniquely human capabilities thrive. Your specific industry matters less than your willingness to adapt, learn, and position yourself in roles AI augments rather than replaces. The divide isn't between industries, it's between workers who evolve with technology and those who don't.
Understanding AI capabilities, limitations, and ethical considerations. Mastering industry-specific AI tools relevant to your sector, whether claims automation in insurance, transcription in journalism, or data analysis in research. AI literacy is becoming as fundamental as computer literacy.
Evaluating AI-generated outputs, making decisions in ambiguous situations, and exercising professional judgment. As AI handles analysis, human value concentrates in interpreting results, identifying when AI is wrong, and making wise decisions despite imperfect information.
Generating original ideas, thinking outside established patterns, and solving novel problems. AI optimizes within existing frameworks but struggles with genuine innovation. Creative thinking differentiates human workers across all industries from media to insurance.
Reading emotions, building relationships, communicating effectively, and navigating interpersonal dynamics. Industries requiring trust, empathy, and human connection resist automation. EQ becomes increasingly valuable as IQ-based tasks automate.
Staying current with evolving technology, learning new skills proactively, and adapting to changing workflows. The pace of AI advancement demands lifelong learning, workers who continuously upskill maintain career relevance across sectors.
Understanding bias, privacy concerns, accountability frameworks, and responsible technology deployment. As AI use expands, professionals ensuring ethical, compliant, and responsible implementation become essential across insurance, media, healthcare, and all sectors.
This analysis is based on research from Bank of England Surveys, Reuters Institute for the Study of Journalism, UK Government AI Framework, McKinsey Industry Reports, Prospects.ac.uk, and sector-specific industry data. Information will be updated as new research emerges and AI capabilities evolve. Learn more.
