Agents Conquer Corporate AI

End users and companies alike are excited about integrating the benefits of AI into their daily tasks. We are seeing the digital transformation turning into an agent-based transformation. And some companies are thriving.

What follows is a pattern we already know. Organizations that take a platform approach to managing their data pipelines, security and governance for all digital assets, including APIs, are better able to identify and leverage trusted data that serves as the foundation for their AI frameworks. And they are seeing real results. These organizations are better able to gain insights that span all of their critical application ecosystems - they have begun to unlock the potential of their connected data.

Orchestrate your own agents

Organizations with low-code platforms can also orchestrate their own agents, easily building in the necessary safeguards, knowing that changes can be made quickly and transparently through the low-code platform. By applying governance over the tools used by the agents (for example APIs), as well as monitoring the agents themselves, they gain the confidence they need to move forward in a world that is sure to have a few surprises in store.

Boost through GenAI

In the past year alone, we've seen some incredible advances in GenAI - from improved LLMs to a greater focus on protocols (MCP, A2A, ACN, ACP) to improvements in inference methods and an even greater 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 cyber attacks will emerge. Harnessing the power of GenAI and the associated competitive advantages lies in protecting corporate data and automated processes through a governance framework that starts at the integration stage.

Responsible AI

Promoting the use of artificial intelligence in all areas of business is becoming increasingly significant and it has never been more important to consider responsible artificial intelligence, data security and governance in all areas. In scenarios, particularly in sensitive areas such as audits, recruitment and pricing, the human workforce must continue to be accountable for the actions of their AI agents. As the technology landscape continues to evolve, building composable AI agents - modular, flexible AI systems - can enable rapid implementation without the need to commit to a model or framework.