Artificial intelligence has moved from experimentation to everyday business use. At the same time, organisations are strengthening cybersecurity, investing in better data infrastructure, and developing the digital skills needed to remain competitive. As we look ahead to 2027, understanding these trends will help organisations prepare for the next phase of digital transformation.

For UK employers, the challenge is no longer whether to embrace these technologies, but how to adopt them safely, effectively, and at scale. At the same time, professionals are expected to develop new technical and analytical skills to keep pace with an increasingly digital workplace.

In this article, we look at the key data and technology trends expected to shape 2027, what has changed over the past 12 months, and the practical steps organisations can take to prepare for the future. Kaplan's data and technology apprenticeship programmes are designed to help employers build the skills needed to succeed in this rapidly evolving landscape.

Why this matters

The organisations that succeed over the next few years won't necessarily be those adopting the most technology, they'll be the ones adopting it most effectively.

Investing in AI, digital skills, and modern data infrastructure can help organisations improve productivity, strengthen cybersecurity, make better use of data and respond more quickly to changing customer and business needs. At the same time, developing the right skills within your workforce will help ensure new technologies are implemented responsibly, securely, and with long-term value in mind.

Whether you're planning your organisation's digital strategy or looking to future-proof your own career, understanding these trends can help you make more informed decisions and prepare for what's next.

Key takeaways from the past 12 months

1. AI has moved from experimentation to everyday business use across UK organisations.¹
2. Responsible AI and governance have become business priorities.¹
3. Cybersecurity remains a major focus for organisations protecting data and digital infrastructure.
4. Strong data foundations are essential for successful AI adoption.
5. Sustainability continues to influence technology investment decisions.
6. Demand for AI, data and digital skills continues to grow across the UK workforce.²

What does the mainstream adoption of generative AI mean for organisations in 2027?

Generative AI refers to artificial intelligence that can create content, analyse information, write code or generate insights from natural language prompts. Organisations are increasingly embedding AI into everyday workflows to improve productivity, automate repetitive tasks and support better decision-making.¹

Examples include:

• Financial services – summarising reports and identifying trends in large datasets.
• Software development – generating code suggestions and supporting testing.
• Customer service – powering AI assistants to answer routine enquiries.

Successful adoption depends on skilled people, effective governance and high-quality data.

Why will data privacy and cybersecurity remain business priorities in 2027?

Cybersecurity is the practice of protecting systems, networks and data from unauthorised access, cyber attacks and data breaches. As organisations become increasingly reliant on AI, cloud computing and connected technologies, strong cyber resilience has become a business necessity rather than simply an IT concern.

Over the past 12 months, the UK's cyber threat landscape has continued to evolve. The National Cyber Security Centre (NCSC) reports that cyber attacks are becoming more frequent and sophisticated, with threat actors increasingly using AI to enhance phishing campaigns, automate vulnerability discovery and improve social engineering techniques. At the same time, organisations are under growing pressure to protect sensitive data, meet regulatory requirements and build trust with customers³.

The challenge isn't just defending against attacks, it's ensuring that new technologies, including AI, are deployed securely from the outset. The NCSC has responded by working with industry and government to develop guidance and security standards for AI systems, recognising that innovation and security must go hand-in-hand⁴.

What does this look like in practice?

Cybersecurity is becoming a strategic priority across every sector, with organisations investing in technologies that help them detect threats earlier, protect sensitive data and build greater resilience against increasingly sophisticated threats.

• Retailers are using AI-powered threat detection and behavioural analytics to identify unusual purchasing patterns, account takeovers and payment fraud in real time, helping security teams investigate suspicious activity before it affects customers.
• Healthcare providers, including NHS organisations, are strengthening identity and access management, encrypting sensitive patient records and expanding staff cyber awareness training to protect critical services and personal data from growing cyber threats.
• Banks and financial institutions are combining AI with behavioural analytics to monitor transactions, identify potential fraud more quickly and strengthen anti-money laundering (AML) processes, while maintaining a seamless customer experience.

As cyber threats continue to evolve, organisations are recognising that technology alone isn't enough. Building a strong culture of cyber awareness and ensuring employees understand data protection, responsible AI and information security are now essential components of effective cyber resilience.

Kaplan's UK data and technology apprenticeship programmes help learners develop practical skills in data governance, cyber awareness, risk management and responsible AI, enabling organisations to innovate confidently while protecting their people, systems and data.

Why are data infrastructure and edge computing becoming more important?

Data infrastructure is the technology that enables organisations to collect, store, manage and analyse data effectively. This includes cloud platforms, databases, networks, and edge computing - where data is processed closer to its source rather than in a central location.

As organisations continue to adopt AI, the quality, availability and security of their data have become critical. AI systems rely on accurate, well-managed data to generate meaningful insights, meaning businesses are placing greater emphasis on building strong data foundations before expanding their use of AI¹.

At the same time, edge computing is becoming increasingly important as connected devices generate larger volumes of real-time data. By processing information closer to where it's created, organisations can reduce delays, improve reliability and respond more quickly to changing conditions.

What does this look like in practice?

Organisations are investing in modern data infrastructure to improve performance, reduce costs and unlock new opportunities for AI.

• Manufacturing: Smart factories use sensors and edge computing to monitor equipment in real time, helping identify maintenance issues before they lead to costly downtime.
• Retail: Connected stores analyse customer behaviour, inventory levels and sales data instantly, allowing stock levels and pricing to be adjusted more efficiently.
• Transport and logistics: Fleet operators process vehicle and traffic data closer to the source, enabling faster route optimisation, improved fuel efficiency and more accurate delivery times.

For many organisations, the focus is shifting from simply collecting more data to ensuring it is accurate, secure and accessible. Strong data management enables better reporting, supports AI initiatives and helps organisations make faster, evidence-based decisions.

Kaplan's data and technology programmes help learners develop practical skills in data analysis, data engineering and AI, enabling organisations to build the digital infrastructure needed to support future innovation.

How will green technology support sustainability in 2027?

Green technology (or GreenTech) refers to digital solutions that help organisations reduce their environmental impact while improving efficiency and supporting long-term sustainability goals. From AI-powered energy management to cloud optimisation and smarter supply chains, technology is playing an increasingly important role in helping businesses achieve their environmental, social, and governance (ESG) objectives.

As organisations continue to invest in digital transformation, sustainability is becoming a key consideration alongside performance, cost and security. Businesses are looking for technologies that not only improve productivity but also reduce energy consumption, minimise waste and provide greater visibility into their environmental impact⁵.

Technology is also helping organisations meet growing stakeholder expectations around ESG reporting by improving the collection, analysis and reporting of sustainability data.

What does this look like in practice?

Organisations are using digital technologies to support more sustainable ways of working.

• Manufacturing: AI-powered monitoring systems optimise energy consumption across production lines, helping reduce waste and improve operational efficiency.
• Supply chains: Blockchain technology is being used to improve supply chain transparency, enabling organisations to trace products more accurately and demonstrate responsible sourcing.
• Commercial buildings: Smart building management systems automatically adjust heating, lighting and ventilation based on occupancy, helping reduce energy use while maintaining comfortable working environments.

Technology is a powerful enabler of sustainability, but lasting progress depends on combining digital innovation with skilled people, effective governance and informed decision-making.

Whether you're looking to improve data-driven decision-making or better understand the role technology plays in ESG reporting, developing digital skills will be increasingly important as organisations balance innovation with sustainability.

Which digital skills should professionals develop for 2027?

As AI, automation, and digital technologies continue to evolve, employers are increasingly looking for professionals who combine technical expertise with strong analytical, communication, and problem-solving skills. While technical knowledge remains important, organisations also need people who can interpret data, collaborate across teams, and apply technology to solve real business challenges.

Research continues to show strong demand for digital and data skills across the UK economy, with employers investing in workforce development to address skills shortages and support digital transformation⁶.

Rather than replacing jobs, AI is changing the way many roles operate. Professionals who understand how to work alongside AI, interpret its outputs and apply critical thinking will be well placed to succeed.

Which skills are becoming increasingly valuable?

Organisations are looking for professionals who can:

• Use AI tools safely, responsibly and effectively to improve productivity.
• Analyse and interpret data to support informed business decisions.
• Communicate technical information clearly to both technical and non-technical audiences.
• Understand data governance, cybersecurity, and responsible AI practices.
• Manage digital projects using agile ways of working.
• Continuously learn and adapt as technology evolves.

What does this look like in practice?

Across every sector, organisations are investing in digital capability to prepare for future growth.

• Finance: Professionals are combining AI tools with data analysis to improve forecasting, identify trends, and support strategic decision-making.
• Public sector: Teams are using automation to reduce administrative workloads, allowing employees to focus on delivering higher-value services.
• Professional services: Businesses are using AI to streamline research, summarise complex information, and improve knowledge sharing, enabling employees to spend more time on client work.

Developing these skills isn't just about keeping pace with technology - it's about building the confidence to use digital tools effectively, think critically, and deliver greater value to employers.

Kaplan's UK data and technology apprenticeship programmes help learners build these future-focused skills through practical workplace learning, combining technical knowledge with real-world application. Whether you're looking to develop expertise in AI, data analysis, business analysis, or digital product management, our programmes are designed to prepare learners for the evolving workplace.

2025 vs 2026: What's changed?

The pace of change in data and technology means today's priorities look very different from those of just a year ago. While many of the trends identified for 2025 continue to shape the industry, organisations are now moving beyond exploration and into implementation.

These changes highlight a clear shift in focus. Rather than asking whether organisations should adopt AI and digital technologies, the question is now how to implement them responsibly, securely and effectively while continuing to invest in the skills people need to succeed.

Action plan: your next 90 days

Whether you're an employer planning your digital strategy or a professional looking to future-proof your career, taking small, focused steps can help you build momentum.

1. Identify one AI opportunity

Choose a single business process where AI could improve productivity, reduce repetitive tasks or enhance decision-making.

Success measure: Define a pilot project and identify how success will be measured.

2. Review your data and cybersecurity practices

Assess whether your organisation has the right governance, security measures and data quality processes to support future AI initiatives.

Success measure: Complete a gap analysis and prioritise areas for improvement.

3. Evaluate your digital infrastructure

Review whether your existing systems can support AI, automation and growing data requirements.

Success measure: Produce a roadmap outlining opportunities to improve data management or infrastructure.

4. Identify your organisation's digital skills gaps

Consider which skills your teams will need over the next 12–24 months, from AI literacy and data analysis to business analysis and digital product management.

Success measure: Create a learning plan aligned to your organisation's priorities.

5. Invest in professional development

Support employees to develop the practical skills needed to work confidently with emerging technologies through structured workplace learning.

Success measure: Enrol learners on a relevant training programme or apprenticeship and agree clear learning objectives with measurable business outcomes.

By taking action now, organisations can build the confidence, capability and resilience needed to adapt to the next wave of technological change.

Preparing for the future of data and technology

The pace of technological change shows no signs of slowing down. As AI becomes embedded in everyday business operations, organisations that invest in the right technology, build strong data foundations and develop digital skills will be better placed to adapt to future challenges and opportunities.

Success isn't about adopting every new technology. It's about making informed decisions, building the right capabilities and giving people the confidence to use digital tools effectively and responsibly.

Whether you're looking to introduce AI into your organisation, strengthen your data capabilities or develop the next generation of digital talent, investing in practical learning today can help prepare your workforce for tomorrow.

Take the next step

For employers

Whether you're looking to upskill existing employees or recruit new digital talent, Kaplan's UK data and technology apprenticeship programmes can help you build the skills your organisation needs for the future.

Explore our data and technology apprenticeship programmes, compare the options available and speak to our team about the best route for your organisation.

Related pages:

• Data and technology apprenticeship programmes
• Apprenticeship funding for employers
• Contact our employer team

For learners

Whether you're starting your career or looking to build new digital skills, Kaplan offers programmes that combine expert teaching with practical workplace experience.

Explore our current apprenticeship vacancies to find opportunities in AI, data, business analysis, digital products, and more. If you're looking to develop specialist knowledge through shorter professional courses, explore our full range of digital and technology training.