Alteryx unveils AI assistant aimed at improving efficiency

An assist from AI

Aidin Copilot, now in preview, is designed to simplify the use of Alteryx’s tools to help make data engineers and architects more efficient. In addition, the AI assistant has the potential to make its tools accessible to less technically proficient users.

The vendor declined to provide a timeline for the AI assistant’s general availability.

Once available, Aidin Copilot will become part of Alteryx Designer, the vendor’s primary tool for preparing data for analysis, in a move that will be significant for Alteryx users, according to Mike Leone, an analyst at TechTarget’s Enterprise Strategy Group.

Data engineers and data architects, in particular, stand to benefit from the AI assistant, he said.

“Alteryx is delivering a copilot experience that is focused on the backend data workflows that eventually enable analytics and data exploration,” Leone said. “These are stakeholders like data engineers and data architects that are overburdened and need the efficiency improvements promised by GenAI.”

Donald Farmer, founder and principal of TreeHive Strategy, similarly said Aidin Copilot is a significant new tool for Alteryx users.

Like many data management and analytics platforms, Alteryx’s suite is complex. Though it has made ease-of-use a priority of product development in recent years, it still takes experience and expertise to manage and prepare data using Alteryx’s tools.

As a result, an AI-powered assistant that simplifies use of Designer has the potential to be a powerful addition.

“Aidin Copilot is an attempt to simplify some processes for users so integration with the Alteryx Designer canvas is a good move,” Farmer said.

Once GA, Alteryx’s AI assistant is designed to provide the following:

• Greater efficiency by placing tools directly on the Designer canvas, reducing the amount of time users spend on manual configurations and speeding the time it takes to prepare data for analysis.
• Chat capabilities that enable users to ask questions about creating analytics workflows in Designer and receive responses that provide best practices.
• Governance built on Alteryx’s Responsible AI Principles that protect both end users as well organizations themselves as more employees engage with data.

The real world

While Aidin Copilot aims to help Alteryx customers navigate Designer, the AI assistant is not geared as much toward enabling new users as it is assisting those already using the platform, Farmer noted.

And that is likely the right approach for Alteryx to take with the AI assistant, he continued.

Each vendor’s generative AI assistant is different.

Some are narrow in scope such as one introduced by DBT Labs on May 14 that automatically provides workflow documentation and generates tests to save engineers time during the development process. Others, such as Tableau’s copilot, are broader, providing conversational capabilities aimed at enabling new users to query and analyze data as well as make existing users more efficient.

Aidin Copilot’s chat capabilities, which Alteryx said provides best practices to guide users when creating workflows in Designer, are more a guide for using Designer than a tool for analyzing data, Farmer noted. They can theoretically enable some new people within organizations to use Designer but more concretely are designed to make existing users more efficient.

“When they say users can chat with Aidin Copilot, the answers are not analytic answers to your data questions,” Farmer said. “This is … a tool for data engineers and analysts, not business users.”

Meanwhile, the focus more on efficiency than adding new users aligns with the reality of AI assistants so far, he continued.

Despite the promise of some assistants to reduce the need for data literacy training, getting the most out of working with data still requires training no matter what tools are available to users.

“Feedback suggests that AI assistants are indeed making strides in simplifying complex tools and improving efficiency,” Farmer said. “But there are issues. Users still need training to get the best from these tools — they do not provide an instant solution, despite the hype. Alteryx is being … more transparent about this than some [other vendors].”

As a result, though Alteryx may appear to be offering less with Aidin Copilot than some other vendors are offering with their AI assistants, by embedding the AI assistant in Designer and focusing on improving efficiency, Alteryx’s approach is sound.

Leone likewise said Alteryx’s focus on helping data experts addresses real need.

While enabling new users is perhaps more flashy than easing burdens on existing data workers, it’s the engineers and architects dealing with increasing volumes and more complex forms of data who most need the help generative AI can provide.

“Most vendors are focused on enabling more of the business to ask questions of the data, but what seems to get lost are the underlying workflows that make the right data available to the analytics and business intelligence tools,” Leone said.

Looking forward

As Alteryx develops generative AI capabilities, customer feedback is helping shape the vendor’s roadmap, according to Asa Whillock, Alteryx’s vice president and general manager of artificial intelligence and machine learning.

Ultimately, just as it is embedding Aidin Copilot in Designer, the vendor plans to embed AI capabilities throughout its platform.

“The goal is to make the Alteryx portfolio powerful, easy to use and efficient for customers to do their job,” Whillock said. “This will show up in AI embedded features … all while ensuring proper guardrails so customers can use our products in a governed and trusted manner.”

In addition, Alteryx plans to provide customers with a choice of LLMs to use with their enterprise data, he continued.

Vendors such as Databricks and Snowflake are already building environments for customers to develop and fine-tune language models. That includes integrating with a variety of LLMs so users can decide which works best for their needs and train the models with proprietary data so the models can inform business decisions.

Alteryx hopes to follow suit, according to Whillock.

“We are taking steps for customers to be able to use LLMs in their enterprise environment,” he said.

Farmer, meanwhile, suggested it would be a good move for Alteryx to continue developing Aidin Copilot so that it does more to aid employees within organizations not yet using Alteryx. In time, if the AI assistant could help business users responsibly work with advanced features, it would further evolve the vendor’s generative AI capabilities.

In addition, geospatial analytics, which was once a primary focus for Alteryx but is now merely part of the vendor’s offerings, is an area where the vendor could apply AI as it develops new tools, according to Farmer.

“I’d like to see Alteryx playing to its original strengths in geospatial analytics,” he said. “AI could help a great deal [with geospatial analysis] as many of the principles and practices are not familiar to non-specialist analysts who nevertheless need to integrate and work with geospatial data.”

Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.