Both end users and companies are excited about incorporating AI into their daily tasks. We are witnessing a shift from digital transformation to agent-based transformation, and some companies are thriving as a result.
What follows is a familiar pattern. Organizations that use a platform to manage their data pipelines, security, and governance of all digital assets, including APIs, can more easily identify and utilize trusted data to develop their AI frameworks. They are seeing real results. These organizations can gain insights spanning all their critical application ecosystems because they have begun to unlock the potential of their connected data.
Orchestrate your own agents
Organizations with low-code platforms can orchestrate their own agents and easily incorporate necessary safeguards. They know that changes can be made quickly and transparently through the low-code platform. By applying governance to the tools used by the agents (e.g., APIs) and monitoring the agents themselves, these organizations gain the confidence they need to move forward in an unpredictable world.
Boost through GenAI
In the past year alone, we've seen incredible advances in GenAI, including improved LLMs, a greater focus on protocols (MCP, A2A, ACN, and ACP), enhanced inference methods, and the democratization of GenAI through the proliferation of open-source models. Artificial intelligence and GenAI will continue to develop in ever-shorter innovation cycles. Data volumes will increase exponentially, and new forms of cyberattacks will emerge. To harness the power of GenAI and its associated competitive advantages, it is crucial to protect corporate data and automated processes through a governance framework that begins at the integration stage.
Responsible AI
Promoting the use of AI in all areas of business is becoming increasingly significant, as is considering responsible AI, data security, and governance. In sensitive areas such as audits, recruitment, and pricing, the human workforce must be held accountable for the actions of their AI agents. As technology continues to evolve, building composable AI agents—modular, flexible AI systems—can enable rapid implementation without committing to a specific model or framework.
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