Fisent Technologies enhanced its BizAI solution with the introduction of BizAI Actions, a comprehensive set of intelligent generative artificial intelligence (AI) powered functions designed to simulate and automate human-dependent tasks.
BizAI Actions provide organizations with a library of intelligent capabilities that can split, classify, extract, verify and analyze information from any format, quickly automating countless repetitive business processes that otherwise slow the pace of business, according to the announcement.
Generative AI can enhance process automation in several transformative ways, going beyond traditional rule-based automation like robotic process automation (RPA) by introducing capabilities for intelligent decision-making, content creation and dynamic interaction.
Orchestrating process automation through 5 core actions
The enhanced Fisent BizAI solution includes the following five core actions that can be orchestrated to automate business tasks that would typically absorb valuable human time and talent.
- Split: Intelligently segment complex documents or content into targeted sections, preparing them for further processing.
- Classify: Automatically identify and categorize content types with high accuracy.
- Extract: Precisely pull specific data points from various content sources.
- Verify: Cross-reference and validate extracted information against predefined criteria.
- Analyze: Provide contextual insights, answers and recommendations based on processed content.
“Actions demonstrate Fisent’s commitment to making a product that can easily apply generative AI to process automation across a variety of use cases and industries,” said Adrian Murray, founder and CEO of Fisent. “By creating these modular, intelligent functions, we’re empowering organizations to quickly automate complex process workflows across any division of the company.”
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How generative AI enhances process automation
Generative AI enables smarter, more adaptive and scalable automation by handling tasks that require comprehension, generation or human-like interaction, opening new frontiers in efficiency and productivity.
For example, traditional automation struggles with unstructured inputs such as emails, PDFs and images. Generative AI can interpret and extract meaning from natural language, images or audio, enabling automation of tasks like invoice processing, document summarization or customer support from emails or chat logs.
Likewise, generative AI-powered chatbots and virtual assistants can understand and generate human-like responses, automating tasks such as appointment scheduling, helpdesk triage or responding to common queries. When combined with RPA or low-code platforms, generative AI fills in the gaps where logic-driven automation falls short and while traditional bots require frequent manual updates, generative AI models can adapt to changing inputs, preferences and contexts.
However, while the potential for generative AI to transform process automation is vast, behind the momentum lies a critical enabler of sustainable AI success – data governance. As businesses accelerate generative AI adoption, strong data governance becomes non-negotiable.
Many organizations lack effective data governance strategies generally, let alone those specifically focused on the integration of emerging AI. This is a trend that must be addressed if businesses are to extract meaningful and consistent value from generative AI adoption.
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