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7 AI trends that will continue to grow in 2025

We discuss some familiar and – slightly lesser known – AI trends that are poised to shape the business landscape in the years to come.

1. Small Language Systems (SLM)

“Bigger is better” has been the mantra of many AI developers since the artificial intelligence boom was kicked off by the launch of ChatGPT. A few years later, small and medium-sized language systems (MLS) are becoming increasingly important due to their scalability and efficiency compared to larger models.

SLMs require fewer parameters to process, which means they are often able to generate answers much faster than LLMs. Their compact size and more modest computing requirements also mean that they can often run on-device as well, reducing the need to send data back and forth from the Cloud, and thereby reducing their environmental footprint.

Some of the biggest names in tech have rolled out their own SLMs this year. Microsoft launched Phi-4, a model specializing in complex reasoning, and Apple launched eight small AI models small enough to run on a smartphone. With SLM enabling startups and small businesses to scale AI at a lower cost, we can only see them becoming a technology staple in the years to come.

2. Agentic AI

Agentic AI is an autonomous AI system capable of making decisions with minimal human intervention. The artificial intelligence component can learn new data and solve complex problems by dynamically adapting to new situations.

Named the ‘major technological trend for 2025According to research and advisory firm Gartner, the trend is poised to transform automation across industries by streamlining processes with less human contact. The technology is already being used to help businesses improve efficiency, with retailers using agentic AI to personalize shopping experiences and healthcare providers using the technology to analyze patient data.

Google has already jumped on the trend by leveraging agentic AI when it launched Gemini 2.0 in December, and other tech giants will likely follow suit in 2025. However, with agentic AI growing faster than legal safeguards, we recommend that companies deploy technology cautiously, maintaining human oversight and conducting E2E testing.

3. AI Cybersecurity

Unfortunately, as advanced AI models become more accessible, the cybercrime market is expected to continue to explode through 2025 as criminals continue to exploit the technology to deceive their victims. More specifically, annual revenues from cybercrime are expected to exceed $10.5 trillion next yeardriven by the growth of AI-enabled phishingdeepfake 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 such as malware, phishing attempts, and zero-day vulnerabilities in real time. AI is also used to reverse engineer zero-day exploits, allowing developers to create security patches for vulnerabilities before they are made public.

With more than half of companies Already using AI to improve threat detection, this technology will only become more vital in 2025 and beyond as cyber risks continue to become more sophisticated.

4. AI search engines

While the search landscape is constantly evolving, the rise of AI has radically transformed the way we retrieve information in 2024.

More particularly, the search engine giant Google deployed its AI Summary Feature in May, helping to improve focus and compliance with billions of search queries. AI pioneer and Brand ChatGPTr OpenAI launched its own rival search engine – Search ChatGPT – in October, in an effort to challenge Google’s long-standing monopoly on search.

While Google’s AI search summary feature initially sparked some dislike, forcing the company to scale back some of its efforts, Google says it led most users to become more satisfied with the results – young people aged 18-24 with the highest level of engagement with the feature.

So while it’s not yet time to say goodbye to traditional search engine results pages, developments that have taken place this year, alongside rapid advances in generative AI, suggest that AI will only continue to further disrupt the way we search in the 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 analytics.

Since these chips were created with AI in mind, they are capable of handling more advanced calculations and larger amounts of data than traditional central processing units (CPUs). As a result, AI chips typically produce more accurate responses, with lower latency, making them the operand of choice for companies like NVIDA, Intel, Google, Amazon and many others.

Due to their competitive advantage, industry analysis predicts that the demand for AI chips will increase by 35% over one year in 2025reaching a potential market value of $120 billion according to Japanese investment bank Daiwa.

Additionally, with Taiwan Semiconductor Manufacturing Company (TSMC) and Samsung investing in a new manufacturing facility on its home turf, this pivot is also expected to solve supply chain challenges by reducing global dependence on Asian manufacturing hubs, suggesting AI chips will become even more plentiful. at the heart of the chip ecosystem in the future.

6. Cutting-edge AI

Edge AI refers to the combination of AI and edge computing. By storing data close to the device, without the need for an external cloud server, the solution is able to reduce bandwidth usage and latency issues, while providing an additional 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 waves in the business world, with the technology being used in the healthcare sector to improve diagnosis and treatment, in the manufacturing industry to analyze occupational hazards, and in the automotive industry to improve safety autonomous vehicles.

Going forward, the deployment of edge AI will only grow faster, with experts predicting the market will be worth a staggering price. $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 businesses.

Enterprise search tools leverage data from all major information silos, including documents, code repositories, emails, and project management tools. By containing only data relevant to specific businesses, internal search systems can revolutionize the way employees resolve queries, enabling teams to be more productive and profitable.

Although enterprise search systems have not always relied on AI, the integration of this technology has helped significantly improve search efficiency. Moving from simple keyword matching associated with traditional search mechanisms, AI-powered enterprise search tools also enable these platforms to be more conversational and intuitive, resulting in interactions more human.

So, with a new generation of new AI enterprise search systems coming out of the woods in 2024, it is almost guaranteed that artificial intelligence will continue to power traditional enterprise search processes in the years to come.