Author: Sadan
In recent years the rise of agentic artificial
intelligence has begun shaping the future of science and technology in a
profound way. Unlike earlier AI tools which required constant human oversight,
agentic AI refers to systems that can reason, plan and act with greater
autonomy. According to research from Gartner, the top strategic technology
trends for 2025 include agentic AI, spatial computing, hybrid computing and
post-quantum cryptography. In practical terms this means AI systems which don’t
just generate text or images, but take multi-step actions, collaborate with
other agents and perhaps even decide when and how to act.
One of the major shifts brought by agentic AI is
the acceleration of productivity and the transformation of workflows. As
described in an article by MIT Sloan Management Review, organisations are
beginning to measure results from generative AI, focusing on unstructured data,
and grapple with how to incorporate autonomous agents in their operations.
Where traditional AI might assist a user to draft an email or summarise a
document, agentic AI might coordinate a series of tasks: draft the email, check
schedules, coordinate with other systems, send follow-up, and learn from the
response.
At the same time, the convergence of agentic AI
with other emerging domains is amplifying its potential. For example, the
global list of emerging technologies for 2025 from World Economic Forum
highlights that new materials, industrial sustainability, next-generation
biotechnologies and trust in AI are all intertwined with this wave of
autonomous systems. In effect, agentic AI becomes the operational layer that
uses breakthroughs in data, materials and computing to deliver real-world
impact.
In summary, agentic AI is not just the next step in
artificial intelligence, it’s the step toward machines that act, learn and
collaborate with minimal human direction and that transition is already
underway in the science-tech landscape.
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