The latest digital transformation trends include generative artificial intelligence (AI) and machine learning (ML), large language models enhancing automation, and cybersecurity’s shifting priorities.
1. Advancements in generative AI and large language model capacity.
According to a McKinsey Global Survey, 65% of respondents in 2024 said their organizations are regularly using generative AI in at least one business function, which is up from 33% in 2023. In 2025, mitigating the risks associated with using 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 generate 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 has several functions, such as Deep Research used for exhaustive content research, 2.0 Flash that is effective at providing quick answers, and personalization, 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 utilizes algorithms to generate descriptive, predictive, and prescriptive insights.
2. Large language models (LLMs) enhance automation.
Teams are often hindered by the time spent on low-effort tasks, such as managing vendor invoices, searching for information, or recreating documentation. Large language models are being increasingly integrated into enterprise tools, creating opportunities for task automation.
Large language models are designed to understand and generate text in a manner similar to human beings, requiring a substantial amount of training to ensure that the models used 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
3. Cybersecurity’s shifting priorities.
Technological innovation is changing the focus of cybersecurity. In 2025, generative AI, machine learning, natural language processing, and large language models are compelling businesses to formalize their standards for minimizing cybersecurity risks.
Cloud adoption has altered the composition of digital ecosystems and user needs. Cloud-based subscription services now make all products and services accessible through a single platform, centralizing information for organizations.
Data localization, the requirement that all data is stored, processed, and managed within the geographical boundaries of a specific country, in some cases requires companies to have data centers located in all operating regions of a company. Currently, there is a US data localization law being created that would prohibit certain data brokerage transactions with countries of concern.
Multi-factor authentication is becoming a popular way for companies to reduce the likelihood of malware or ransomware accessing company or customer data. Additionally, virtual private networks have become more widespread, shielding individual user IP addresses and virtual locations.
