Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI Adoption Manager

Wellington
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Product Manager - Machine Learning and AI

AI and Machine Learning Trends 2025: A UK Hiring Outlook

Senior Machine Learning Engineer

ML (Machine Learning) Engineer

Engineering Program Manager, Machine Learning

Data Science Manager - Logistics Operations

About the Role

We are seeking an experienced and innovative AI & Innovation Specialist to join our client. In this role, you will be responsible for identifying, exploring, and implementing AI-driven solutions that can enhance our business operations. As a key member of our team, you will bridge the gap between technical capabilities and business impact, driving the adoption of AI technologies to support our growth and success.

Key Responsibilities:

Identify AI opportunities: Conduct research and evaluate potential AI use cases that can drive efficiency, automation, or competitive advantage.
Collaborate across teams: Work closely with production, R&D, and commercial teams to understand business needs and how AI can enhance processes.
AI Implementation Support: Assist in developing and testing AI-driven solutions, working alongside external AI consultants and internal teams.
Data & Insights: Support data analysis efforts to assess trends, performance, and AI model effectiveness.
AI Training & Awareness: Help upskill internal teams by explaining AI concepts and ensuring effective adoption of new tools.
Monitor AI Trends: Stay informed on the latest AI developments and assess how they could be applied within the business.

What We're Looking For:

Degree in Computer Science, Data Science, AI, Business Analytics, or a related field.
1-3 years of experience in AI, data science, or technology-driven innovation.
Understanding of AI tools, automation, and machine learning concepts (hands-on coding experience is beneficial but not essential).
Strong problem-solving and analytical skills with a commercial mindset.
Ability to communicate AI concepts to non-technical stakeholders.

Nice to Have:

Experience in manufacturing, production, or supply chain optimisation.
Exposure to working with AI consultancies or external data teams.
Understanding of business process automation

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.