In this BSA series – “Why AI?” – enterprise software leaders explain in their own words how artificial intelligence (AI) is having a positive impact on individuals, businesses, and organizations worldwide. In this submission, Alteryx Chief Product Officer Suresh Vittal writes about the launch of AiDIN and the importance of empowering non-technical users to build and automate processes without needing to write code.
1. Why AI?
At Alteryx, our AI journey began in 2017 with the integration of Language Models into our Intelligence Suite. These models fuel our text mining, PDF data extraction, and Natural Language capabilities. And all crucial components for processing large volumes of unstructured data and deriving actionable insights from documents at scale. From there, we launched products like Alteryx Auto Insights and Alteryx Machine Learning with AI-embedded capabilities.
With the massive opportunity that generative AI has presented to broaden our AI strategy further, we recently launched Alteryx AiDIN. AiDIN is the AI engine that combines the power of AI, machine learning, and generative AI within our Alteryx Analytics Cloud Platform and across our product portfolio.
Recent AiDIN innovations include:
- Workflow Summary: Automatic documentation in Alteryx Designer so organizations do not have to worry about their IP leaving the company even when employees do.
- Magic Documents: Auto generates email and PowerPoint summaries via Auto Insights so the narrative matches the audience.
- Open AI Connector: Automates content generation in Alteryx Designer.
These innovations are designed to enable anyone – including non-technical users – to capture the competitive advantage of AI and ML and unlock an entirely new way of using data-driven insights to solve complex business challenges.
2. Can you give an example?
Use cases for AI-driven analytics are endlessly diverse. We often see customers get great value from prescriptive modeling, such as predicting rates of failure, forecasting inventory needs, or solving time series problems.
During the pandemic, for example, one Alteryx customer sought to leverage real-time shipping data alongside internal supply chain data to adjust inventory levels and reorder times automatically. Using Alteryx Machine Learning to put accessible, repeatable AI-driven insights into the hands of non-technical users not only saved the company money but helped stabilize critical supply chains by identifying potential risks and taking proactive steps to mitigate them.
We are also seeing tremendous early interest on our generative AI tools, especially when organizations put accessible AI into the hands of employees and empower non-technical users to build and automate processes without needing to write code.
3. Where can we learn more?
At Alteryx, we not only believe in the enormous potential of AI, but also in the responsibility of AI developers, deployers, and users to interact with the technology responsibly and ethically. We describe our commitment to responsible AI here.
I also encourage readers to check out our company blog for a recent post about how companies are currently using generative AI and plan to in the future.
For more information about Alteryx AiDIN visit our Alteryx website.
About the author:
Suresh Vittal is the Chief Product Officer for Alteryx, where he is responsible for the strategic vision of Alteryx’s leading analytics and data science innovation, and plays a critical role in the company’s cloud, data science and analytics automation product strategy.
