Agentic AI is reshaping organisational dynamics, enabling hyper-personalised interactions, instant decision-making and streamlined operations. Unlike traditional AI systems, which follow fixed instructions, agentic AI can independently set goals, adapt to changing conditions and take initiative in complex environments, writes Murali Sastry, SVP and Head of Technology at the platform Skillsoft.
Yet, with these growing capabilities comes increased risks, particularly concerning security, governance and organisational oversight. While current conversations emphasise the potential for innovation and efficiency, a more pressing challenge is emerging: how to ensure these systems remain secure, compliant and aligned with core business values.
Organisations must understand how to adopt agentic AI responsibly. What steps can they take to secure their systems and prepare their workforce to collaborate effectively with these intelligent agents?
Establishing clear boundaries and controls
Agentic AI doesn’t just follow rules, it interprets context, adapts to change and takes initiative. This level of autonomy unlocks transformative potential for organisations, but it also introduces complex challenges around control, data access and responsible oversight.
To operate effectively, agentic AI systems often require deep integration with enterprise data. However, this increased access heightens the risk of data breaches, misuse or unintended exposure. Without strong governance mechanisms, these AI agents could access sensitive information such as personal data, proprietary assets or regulated content and use it in ways that conflict with organisational policies or legal requirements.
The stakes are high, with reputational damage, financial loss and regulatory penalties becoming real possibilities. That’s why organisations need to establish clear protocols, enforce strict access controls and build governance frameworks that ensure agentic AI operates safely and ethically.
Governance frameworks and ethical guardrails
The autonomous nature of agentic AI challenges conventional accountability within organisations. When these systems independently make decisions such as reallocating resources, generating customer responses and initiating workflows, it becomes increasingly difficult for organisations to pinpoint who is responsible for the outcomes. The distinction between human oversight and machine-driven action becomes blurred, introducing ambiguity and potential risk.
To mitigate this, organisations must establish clear governance models that clearly assign accountability for AI-driven actions. This includes specifying who is responsible for monitoring, validating and intervening when necessary. Alongside this, ethical guardrails and compliance requirements should be embedded directly into the agent’s logic, ensuring that its behaviour consistently aligns with organisational values and regulatory standards.
The human element
While robust technical controls and governance structures are critical, they represent only part of the solution. One of the most underestimated risks in adopting agentic AI lies in an unprepared workforce.
As with many security threats, internal actors often unintentionally pose the greatest risk. This risk is also seen when implementing agentic AI across an organisation. When employees are given access to powerful AI tools that can influence operations, even small mistakes can lead to significant vulnerabilities, whether at the individual, team or enterprise level.
The success of agentic AI integration depends not only on deploying the right technologies but also on equipping people with the skills to use them wisely. This means investing in both technical literacy and human knowledge and readiness. On the technical side, employees need to understand prompt engineering, data governance and compliance protocols to use AI tools safely and effectively. Equally important are power skills such as ethical reasoning, critical thinking and digital discernment, which enable individuals to assess AI outputs, challenge assumptions and make informed decisions.
These skills aren’t just helpful, they’re foundational. Without them, even the most advanced technical controls may fall short. Empowering the workforce with the right knowledge and mindset is essential to ensuring agentic AI is used ethically, responsibly and in alignment with organisational values.
Building a continuous learning culture
To successfully implement agentic AI, organisations must foster a culture of continuous learning that empowers both leadership and employees to adapt, grow and lead in an agentic AI environment. This means going beyond technical training to prioritise both reskilling and upskilling, while also cultivating essential human skills such as communication, adaptability and ethical judgment.
One of the most effective ways to develop these skills is through scenario-based learning. By simulating real-world challenges in a safe and supportive environment, teams can practice critical decision-making, strengthen their confidence and build the skills needed to navigate complex AI-driven workflows.
In today’s landscape, upskilling is no longer optional; it’s the first line of defence. Learning and development (L&D) strategies must adapt to prepare not only employees but also the AI agents they will supervise. This includes training staff to guide, monitor and collaborate with agentic AI systems in ways that align with organisational values and regulatory standards.
As business leaders move quickly to reap the benefits that agentic AI presents, the need for quick adoption must be balanced with responsibility. Organisations that embed upskilling into their AI adoption strategy will be better equipped to manage risk, ensure compliance and unlock the full strategic value of agentic AI.
Building success on strong frameworks
As organisations race to unlock the full potential of agentic AI, the challenge lies in balancing rapid innovation with responsible implementation. Deploying these systems without a strong governance framework or a well-prepared and equipped workforce can result in serious consequences, from data breaches and regulatory violations to reputational harm.
The organisations that will succeed are those that act with both urgency and intention, laying the groundwork for secure, scalable adoption through robust infrastructure, clear policies and continuous workforce development.
By embedding governance at the core of their AI strategy, organisations won’t just mitigate risk but lead with foresight. Successful organisations will be those that combine agility with accountability and treat learning as a strategic imperative in their AI journey.
