7 AI Trends That Will Continue To Grow In 2025
We cover some familiar and – slightly lesser-known – AI trends that are on track to shape the business landscape in years to come.
1. Small Language Systems (SLMs)
‘Bigger is better’ has been the mantra of a lot of AI developers since the artificial intelligence boom was kick-started by the launch of ChatGPT. Skip forward a couple of years, and small, and medium-sized language systems (MLS) are becoming more important ever due to their scalability and efficiency advantages over larger models.
SLMs need fewer parameters to process, meaning that they’re often able to generate responses much faster than LLMs. Their compact size and more modest computing requirements also mean that they’re often able to run on the device too – reducing the need to send data back and forth from Cloud, and lowering their environmental footprint as a result.
Some of the biggest names in tech rolled out their own SLM this year. Microsoft released Phi-4, a model that specializes in complex reasoning, and Apple launched eight small AI models that are small enough to run on a smartphone. With SLMs making it possible for startups and small businesses to scale AI more affordably, we can only see them becoming more of a tech staple in years to come.
2. Agentic AI
Agentic AI are autonomous AI systems that are able to make decisions with minimal human input. The strand of artificial intelligence can learn from new data and solve complex problems by dynamically adapting to new situations.
Named the ‘top tech trend for 2025‘ by research and consulting firm Gartner, the trend is on track to transform automation across industries by streamlining processes with less human touch. The technology is already being used to help businesses improve efficiency, with retailers using agentic AI to personalize shopping experiences, and healthcare providers utilizing the tech to analyze patient data.
Google has already jumped on the trend by leveraging agentic AI in its December launch of Gemini 2.0, and more tech giants are likely to follow this lead in 2025. However, with agentic AI developing faster than legal guardrails, we recommend businesses deploy the technology with caution, by maintaining human oversight and carrying out E2E testing.
3. AI Cybersecurity
Unfortunately, as advanced AI models become more accessible, the cybercrime market is projected to boom further into 2025 as criminals continue to leverage the technology to deceive victims. Specifically, annual cybercrime revenues are projected to exceed $10.5 trillion next year, driven by the growth of AI-enabled phishing, deepfake, and malware attacks according to Cybersecurity Ventures.
However, as cyber threats continue to advance, so do the protocols designed to mitigate them. By using AI instead of traditional solutions, businesses are able to detect threats like malware, phishing attempts, and zero-day vulnerabilities in real-time. AI is also being used to reverse engineer zero-day exploits, allowing developers to create security patches for vulnerabilities before they become public.
With over half of businesses already using AI to improve threat detection, the technology will only become more vital in 2025 and beyond, as cyber risks continue to grow more sophisticated.
4. AI Search Engines
While the search landscape is always evolving, the rise of AI radically transformed the way we retrieve information in 2024.
Most notably, search engine behemoth Google rolled out its AI summary feature in May, helping to improve the focus and reverence of billions of search queries. AI trailblazer and ChatGPT maker OpenAI launched its very own search engine rival – ChatGPT Search – this October, in a bid to challenge Google’s longstanding monopoly on search.
While Google’s AI search summary feature was initially met with some aversion, forcing the company to scale back some of its efforts, Google claims it led most users to become more satisfied with the results – with younger people aged 18 to 24 having the highest level of engagement with the feature.
So, while it’s not time to wave goodbye to traditional search engine results pages just yet, developments that have taken place this year, alongside rapid advancements in generative AI, suggest that AI will only continue to disrupt the way we search more in years to come.
5. AI Chips
Artificial intelligence chips are integrated circuits designed to handle AI tasks, including machine learning (ML) natural language processing (NLP), and data analysis.
Since these chips were created with AI in mind, they are capable of handling more advanced computations and larger amounts of data than traditional central processing units (CPUs). As a result, AI chips typically yield more accurate responses, at a lower latency, making them the operandum of choice for companies like NVIDA, Intel, Google, Amazon, and many more.
Due to their competitive advantage, industry analysis predicts that AI chip demand will grow by 35% year-over-year in 2025, reaching a potential market value of $120 billion according to the Japanese investment bank Daiwa.
What’s more, with Taiwan Semiconductor Manufacturing Company (TSMC) and Samsung investing in a new manufacturing facility on home soil, this pivot is also expected to resolve supply chain challenges by reducing global dependency on Asian manufacturing hubs, suggesting that AI chips will become even more central to the chip ecosystem going forwards.
6. Edge AI
Edge AI refers to the combination of AI and edge computing. By storing data close to the device, without relying on an external cloud server, the solution is able to reduce bandwidth usage and latency issues, while providing an extra layer of security.
By enabling real-time processing on edge devices, edge AI represents a major shift in how businesses approach data processing and decision-making. Edge AI is already making major waves in the business world, with the technology being used in the healthcare industry to improve diagnostic and treatment, the manufacturing industry to analyze occupational hazards, and the automotive industry to improve the safety of self-driving vehicles.
Looking forward, the deployment of edge AI is only set to grow faster, with experts projecting that the market will be worth a staggering $62.93 billion by 2030.
7. Enterprise Search Systems
Not to be confused with AI search systems, enterprise search systems are solutions used to search for information within corporate organizations.
Enterprise search tools leverage data across all major information silos, including documents, code repositories, emails, and project management tools. By only containing data relevant to specific companies, internal search systems can revolutionize the way employees resolve queries, enabling teams to be more productive and profitable as a result.
While enterprise search systems haven’t always relied on AI, the incorporation of this technology has helped to drastically improve search efficiency. By moving on from simple keyword matching associated with traditional search mechanisms, AI enterprise search tools also enable these platforms to be more conversational and intuitive, resulting in more human-like interactions.
So, with a fresh crop of new AI enterprise search systems popping out of the woodwork in 2024, it’s almost guaranteed that artificial intelligence will continue to optimize traditional enterprise search processes in years to come.
