The latest digital transformation trends include Generative artificial intelligence (AI) and machine learning (ML), large language models enhancing automation, and cybersecurity’s shifting priorities.
According to a McKinsey Global Survey, 65% of respondents in 2024 reported that their organisations regularly use Generative AI in at least one business function – up from 33% in 2023. In 2025, managing the risks associated with Generative AI tools, including AI bias and misinformation, will be a priority.
McKinsey & Company highlighted the following developments in the Generative AI space:
- Increased use of multimodal Generative models – AI tools that combine text, images, sound, and video to produce exhaustive outputs for businesses across industries
- Open-source AI models becoming more popular
- Natural-language processing (NLP) expanding the types of accepted prompts
- Google rolling out Gemini, which offers several functions – including Deep Research for exhaustive content research, 2.0 Flash for providing quick answers, and personalisation, which uses search history to understand user interests
Additionally, machine learning is a component of artificial intelligence that enables machines to learn automatically from past data to identify and predict patterns. Machine learning uses algorithms to generate descriptive, predictive, and prescriptive insights.
Teams often lose valuable time to low-effort tasks like managing vendor invoices, searching for information, or recreating documentation. Large language models are increasingly being integrated into enterprise tools, creating opportunities for task automation.
Large language models are designed to understand and generate text in a way that mirrors human communication, requiring significant training to ensure the models adhere to brand guidelines and eliminate information bias. LLMs can infer and provide contextually relevant responses, translations, and written content based on the context, resources, and guidelines provided by humans.
Large language models can help automate:
- Text generation
- Content summaries
- Serving customers through chatbots
- Code generation
- Translation of text into different languages
Technological innovation is reshaping the cybersecurity landscape. In 2025, generative AI, machine learning, natural language processing, and large language models are pushing businesses to formalise their standards for minimising cybersecurity risks.
Cloud adoption has changed the shape of digital ecosystems and what users need. Cloud-based subscription services now bring all products and services together on a single platform, centralising information for organisations.
Data localisation – the requirement that all data is stored, processed, and managed within the geographical boundaries of a specific country – means some companies must have data centres in every region where they operate. Currently, a US data localisation law is being developed that would prohibit certain data brokerage transactions with countries of concern.
Multi-factor authentication is gaining traction as an effective way for businesses to reduce the risk of malware or ransomware compromising company or customer data. Virtual private networks have also become more widely adopted, protecting individual user IP addresses and virtual locations.
