The year 2025 will see AI make greater strides as tech companies learn from their initial forays into the new tech
ChatGPT, launched a little over two years ago, has made artificial intelligence (AI) a household name. Not only has AI deeply embedded itself in our homes and offices, it has also divided the community. On one hand, it’s a phenomenal enabler that has saved millions in both man-hours and resources. But on the other, it has raised concerns about ethics, as well as the penetration of fake news and content.
While experts debate and worry over the advancements in AI, one thing is for sure. The year 2025 will see AI make greater strides as tech companies learn from their initial forays into the new tech.
Read: Understanding major data risks in AI projects
Here are some AI trends we are likely to see in 2025:
Agentic AI will get stronger
Agentic AI refers to an AI system that acts autonomously, adapts in real time, and solves multi-step problems. These systems are built of multiple AI agents that leverage large language models (LLMs). Enabling AI agents with LLMs enhances decision-making and natural language understanding, facilitating more effective and intuitive user interactions.
Over the past year, AI models have become faster and more efficient. Today, large-scale “frontier models” can complete a broad range of tasks from writing to coding, and highly specialized models can be tailored for specific tasks or industries.
In 2025, models will do more — and do it even better.
Generative AI will keep delivering
Generative AI already has a lot on its plate. It’s writing articles, creating music and generating images. Yes, humans can easily determine if the text or image has been generated by AI, but that line is fading fast. As AI models learn more, they are refining themselves. The usual cues in AI-generated text are getting harder to find. Images, too, are more life-like.
Read: No longer a choice, AI is the blueprint for business growth in the Middle East
Explainable AI
This AI model allows human users to comprehend and trust the results and output created by machine learning algorithms.
Explainable AI is used to describe an AI model, its expected impact and potential biases. It helps characterize model accuracy, fairness, transparency and outcomes in AI-powered decision making. It is crucial for an organization in building trust and confidence when putting AI models into production.
As AI becomes more advanced, humans are challenged to comprehend and retrace how the algorithm came to a result. The whole calculation process is turned into what is commonly referred to as a “black box” that is impossible to interpret.
For instance, imagine you are using an AI tool to sift through job applications or approval requests. Without explainability, the user will not know how the decision was made.
Workplace productivity AI will see a boost
AI is already speeding up and enhancing our work, especially when it comes to automating time-consuming or repetitive tasks. As AI gets sharper, it will take away several more mundane tasks, leaving workers with more time for creativity.
Ethics and regulation
As AI becomes stronger, we will need stronger regulations to ensure AI tools are used responsibly. Without regulation, data manipulation, misinformation, bias, and privacy risks can arise and pose greater societal risks.
