As Agentic AI takes hold, the workplace must once again consider how to adapt.
Capable of handling more complex tasks, making its own decisions, and taking action with or without human intervention, Agentic AI has the potential to redefine the workplace and create a new status quo.
However, opening new doors means venturing into uncharted territory, and unlocking AI’s potential requires not only skilled workers who trust the technology but also a reliable and secure network that can support flawless performance. Like with every disruptive technology, there are trends and challenges to consider first.
So, let’s look at some of the workplace trends and challenges for 2025.
Advancing AI beyond acceleration
In 2025, AI’s success in the workplace will hinge on its evolution from an intelligent assistant that supports conversations to an autonomous agent capable of handling more complex tasks, with or without human involvement. This increased automation will not just accelerate existing workflows but will also replace more tedious and error-prone processes entirely, allowing employees to focus on more meaningful, strategic work. To truly reach the next phase of AI innovation, businesses must master the powers of Agentic AI across their entire organisation.
However, businesses must also overcome the challenges that come with such a major transition.
Compliance is one such challenge. AI does not have ethics, and businesses will need to navigate an increasingly complex regulatory landscape with evolving data privacy laws and the need for ethical AI governance. You can’t just offload this to AI – humans are responsible for governing its use.
Security presents another hurdle. Businesses will need to integrate security and accountability into AI frameworks for maintaining trust with customers, employees, and regulators especially as the underlying data needs to be properly classified, secured and governed.
Networks also play a critical role in AI’s success. As businesses move toward the next generation of AI, deploying a robust, high-speed, and secure network will be essential to ensure optimal performance and meet the growing demands of AI systems. This is especially important as we see a trend of AI workloads increasingly being shifted back to the Enterprise Edge.
As AI is transforming the workplace, it also has the potential to transform network and security operations. To leverage the transformational power of AI in these areas, businesses can turn to platformisation – integrating key applications, including AI, security, and networking, into a unified platform that effectively supports autonomous agents. By creating a cohesive enterprise network that integrates seamlessly at the data level (rather than just the application level), businesses can streamline governance, improve compliance, and simplify operations. A platform equipped with zero-trust security further enhances this integration by proactively mitigating risks in real time, making security an intrinsic part of the network, rather than an added function.
This unified approach ensures that all components work together seamlessly, creating a scalable, efficient infrastructure that supports growth, performance, security, and innovation.
Since AI’s potential is so vast, its capabilities are often overestimated and miscommunicated, leading some businesses to underutilise its full potential. Consequently, teams must focus on applied use cases and demonstrate tangible outcomes with Agentic AI to drive real impact and move toward full autonomy, unlocking ROI through enhanced efficiency and innovation.
Investing in AI literacy
Investing in AI literacy will be essential for businesses that want to succeed in an era defined by AI. And this needs to start at the top. C-Suite leaders will need a basic level of AI literacy to effectively guide their organisation through its evolution.
They will need to know how to use it, how to guide it through complex regulations, and how to empower a team whose jobs are being impacted by its deployment. Having the right talent with AI expertise ensures that both leadership teams and employees understand AI’s capabilities, limitations, and best use cases.
These talents can also inform the company’s governance frameworks to provide ethical, transparent, and accountable deployment. All of this is essential for building trust and driving adoption.
For leadership teams, though they won’t be replaced by AI itself, they could be replaced by people with a higher level of AI literacy. Given the speed at which AI is progressing, leaders who are not well-versed in its capabilities may find it increasingly difficult to stay competitive in the next few years, making it essential to build AI literacy across all levels of the organisation.
Unlocking success with soft skills
Believe it or not, advancements in AI will force us to be even more human. Successful AI implementation will prompt us to focus on our unique human skills, such as empathy, creativity, and critical thinking.
While AI can generate insights, automate processes, and make predictions, it can’t judge context, moral implications, or make complex decisions in the same way people can. Human oversight will be crucial when interpreting AI-generated insights, spotting biases, and ensuring ethical and strategic decision-making.
As AI becomes more valuable with increased data access, the risk factor also rises. For example, our CIO study found that 71% identified network security as their top concern, with growing threats as AI adoption accelerates. This is where leaders will be called to hone their soft skill sets – emotional intelligence and critical thinking – to manage these risks effectively and help employees transition to an AI-first workplace.
This demonstrates the irreplaceable value of insight from people.
AI failure as a catalyst for growth
As Agentic AI takes root, workplaces will need to adapt. While this new generation of AI has significant potential for reshaping workforces, the need for AI literacy will become even more critical to address compliance, security, and ROI in AI implementation.
Many AI projects may encounter challenges or fall short of initial expectations, but this will serve as a springboard for growth and innovation. Businesses must learn to embrace these setbacks, discover their limitations, and make room for applied AI with clear ROI use cases.
This journey of literacy and experimentation will pave the way for fundamental AI transformation that moves beyond mere acceleration and drives operational and workflow success.
