Process automation platform vendor Appian Corporation has announced enhancements to its platform, including support for agentic AI, the Model Context Protocol (MCP) protocol, and more. All enhancements are focused on enabling enterprises to scale their business automation safely and effectively.
In Appian’s view, embedding artificial intelligence into enterprise business processes solves key challenges faced by most businesses. These include fragmented data, inadequate governance of data usage, and unreliable AI outputs.
Smarter, Contextual AI Agents for Safe, Efficient Business Automation
One of the most significant enhancements made by Appian to its platform is the expansion of its AI agent capabilities. In Appian’s description, the platform offers improved guardrails, context awareness, and interoperability when it comes to agentic AI.
To start, the new Appian Platform integrates with MCP, a protocol that enables AI agents to interact with enterprise platforms and data in a secure manner. As a result, external AI agents can interact with Appian’s proprietary data fabric. This data fabric gives unified read/write access to enterprise data stores.
The platform also adds memory-based agent learning capability, where organizations can monitor performance of individual AI agents. They can then apply knowledge learned through these interactions throughout other workflows. This helps drive more intelligent decision-making and optimization.
Assistive AI Development Tools For Enterprise Apps
The latest Appian platform update also adds new assistive AI capabilities to the platform. Specifically, these capabilities assist in developing applications using specification-based approaches.
According to Appian, the tools integrate conversational AI capabilities with iterated development methodologies. This allows enterprise developers to rapidly create enterprise-grade applications without sacrificing governance or quality.
As Appian’s Chief Technology Officer and Founder Michael Beckley notes, these capabilities fit well with the overall vision of agentic process orchestration and enterprise automation.
Trustworthy AI and the Need for Explainability
The enterprise AI push made by Appian coincides with the rising need for trustworthy and explainable AI systems. In fact, according to research, enterprises need adaptable, explainable, and contextual awareness of AI systems. This is necessary to successfully deploy them into their operations.
Indeed, Appian itself has already been emphasizing governance and compliance aspects of its AI approach. Previously, it was referred to as “serious AI,” focusing primarily on operational business processes such as procurement, claims processing, and other government operations – and not consumer-oriented AI technology.
Examples From Enterprise Customers
One example of implementing Appian and Snowflake AI tools provided by the vendor involves Global Excel Management. This healthcare risk management provider has been using Appian Platform alongside Snowflake’s AI tools to modernize its claims process and workflow automation.
The combination of the two tools is expected to allow for improved enterprise automation capabilities while maintaining high levels of security and governance.
Why This Matters To Enterprise AI
With enterprises ramping up AI initiatives in recent years, including the adoption of generative AI and AI-powered agents, there still remain a number of barriers to widespread adoption. Among them are governance, explainability, and reliability of deployed AI solutions.
Research shows that most AI projects fail because they do not properly integrate business processes and utilize low-quality data.
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