Developing Trust in AI from Automation to Autonomy: An Analysis of Agentic Artificial Intelligence Trustworthiness
In today's fast-paced business environment, the integration of Agentic AI into organizational systems is empowering companies across various industries. This new form of AI introduces autonomous agents capable of taking on complex responsibilities and interacting independently with enterprise systems, adapting to changing inputs, connecting with other agents, and supporting business-critical decision-making processes.
However, the autonomous nature of Agentic AI brings risks. Systems might drift from their intended purpose, make decisions that conflict with business rules, regulations, or ethical standards, or undermine trust and effectiveness due to agent sprawl. To mitigate these risks, a secure, governed, and end-to-end platform is essential.
Low-code frameworks are uniquely positioned to provide the necessary supervision for Agentic AI, acting as a control layer between Agentic AI and enterprise systems. Developers and IT leaders can set the rules, guide the agents, and shape how software behaves at scale with these platforms.
Transparency and traceability are non-negotiable for AI-driven processes. Leaders need to understand why decisions are made, and low-code platforms offer a reliable, scalable framework with built-in governance for developing and managing both applications and agents. This transparency ensures that decisions are made in a way that aligns with business objectives and ethical standards.
The move towards Agentic AI elevates the developer role, making them strategic orchestrators who guide how Agentic AI interacts with people, data, and business processes. Low-code provides a way to experiment with emerging tools like Agentic AI while maintaining market competitiveness and the agility to be early adopters.
Companies like Hannoversche Volksbank in Germany are already leveraging low-code platforms integrated with autonomous AI to automate and optimize business processes such as data processing and customer service. These platforms enable users without deep IT skills to develop professional applications rapidly and democratize automation by combining AI, robotic process automation (RPA), and low-code/no-code solutions.
Moreover, low-code platforms embed security practices directly into the development cycle with built-in DevSecOps. By leveraging low-code frameworks, enterprises can embrace rapid change without incurring long-term technical debt, sacrificing product quality, or exposing themselves to risks that could undermine future success and reputation.
64% of technology leaders cite governance, trust, and safety as top concerns when deploying AI agents at scale. Human guardrails, platform-level governance, and transparency are essential considerations for Agentic AI. Low-code platforms offer a solution to these concerns, ensuring that AI is used in a way that is beneficial, safe, and trustworthy for all involved.
In conclusion, the integration of Agentic AI into organizational systems is a significant step forward in automation and decision-making processes. With the help of low-code platforms, businesses can harness the power of Agentic AI while maintaining the necessary oversight, transparency, and security needed for success.
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