The rise of artificial intelligence is driving a foundational shift in how organizations approach AI data readiness and structure their data. Historically, data has been siloed by department or business application, but as AI-driven insights become more sophisticated, organizations must take a more integrated approach.

Yet, simply integrating data isn’t enough — organizations must prepare it for AI. This is where Alteryx Inc. plays a critical role, according to Chief Executive Officer Andy MacMillan (pictured).

“Our goal is to show up for our customers and say, ‘You now have a preparedness problem. You need to prepare your data for something,’” he said. “ We’ve been doing that for a long time, if not through the lens of AI, through the lens of how an enterprise does it. What Alteryx really does at its core is help business analysts become sort of superheroes and super users of data … or data knowledge workers. That’s really what we help our customers do.”

Alteryx’s Andy MacMillan talks with theCUBE’s John Furrier about the changing role of business analysts, the challenges of AI data readiness and how Alteryx helps companies prepare their data for AI-driven insights.

MacMillan spoke with theCUBE’s John Furrier at the “AI & Analytics: Shaping the Future With Alteryx CEO & Tom Davenport” event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the evolving role of business analysts, the challenges of AI data readiness and how Alteryx helps companies prepare their data for AI-driven insights. (* Disclosure below.)

Alteryx: The AI data readiness canvas

Alteryx is positioning itself not just as an AI enabler, but as a critical component of AI readiness, according to MacMillan. The company helps organizations build AI-ready data architectures by integrating multiple data sources, ensuring analysts and knowledge workers can drive real business impact.

“We talk about AI in three layers at our company right now,” MacMillan said. “There’s the way you interface our product. Everybody’s creating an AI interface to their product [and] we are, too, how you get output from the product. But the third one that I think is unique to us is how the product is actually used to help companies get ready for AI.”

This shift in AI-driven analytics is also reshaping the role of business analysts. Traditionally, analysts focused on reporting data trends, often relying on spreadsheets or dashboards. Today, with the ability to integrate cloud data, third-party sources and automation tools, analysts are expected to move beyond reporting and play a direct role in implementing AI-driven workflows, according to MacMillan.

“One of the things we’ve done since the founding of the company was this idea that no matter how much you instrument something, for example, with a dashboard, you’re still going to get asked questions and have to iterate and work,” he said. “That was pretty inefficient. Now they do it in Alteryx, and that might be pulling some data out of the cloud data warehouse and might be pulling in third-party data.”

As AI becomes more embedded in business processes, analysts are increasingly tasked with training AI models, systematizing workflows and ensuring AI data readiness to enhance decision-making, according to MacMillan. Rather than relying solely on technical teams, companies seek analysts who understand business needs and data mechanics to lead this charge.

“I think what we’re going to see now is a bunch of new requests coming in [from companies] who are … rolling out AI … [and are] going to turn to that same analyst and say, ‘Go figure out how the AI thing is going to know how to do this’ for a very long time,” MacMillan said. “That analyst is going to have to figure out how to pull this data together, systematize it, turn it into a workflow and build that out.”

Where Alteryx is headed: Scaling AI-driven data readiness

Many companies struggle with fragmented data spread across multiple platforms, each governed by different rules and access permissions, making it difficult to generate meaningful insights. Recognizing these challenges, Alteryx is focusing its investments on connectivity, cloud data access and solutions designed to enhance AI data readiness, according to MacMillan. Its roadmap is evolving quickly, shaped by customer needs and new AI-driven use cases.

“The biggest area we’re investing in is … connectivity in [the] cloud,” he said. “Data warehouses continue to be a big driver of our business as people want to get more value out of the investments they’ve made in that infrastructure. The second one is exactly in line with our discussion here, which is [that] our product as it exists today is the product that solves this problem. This is not a future state we have to get to; people use our product to do data prep. This is the new data prep.”

Beyond its technology, Alteryx’s strength lies in its expansive user community, which now has over 600,000 members, including certified Alteryx ACE experts, according to MacMillan. This network is becoming an increasingly valuable resource for businesses adopting AI as users collaborate to refine best practices and share solutions for AI data readiness, positioning Alteryx as a crucial partner for companies navigating AI adoption and AI data readiness.

“What’s exciting for them is that AI’s rise will only make their skills more valuable as companies try to get their data prepared for AI,” MacMillan said. “A lot of what we’re doing is partnering not only with our customers, but also with our users to help them get ready for this and feel like this is a tailwind for their career.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the AI & Analytics: Shaping the Future With Alteryx CEO & Tom Davenport event:

You can view the full event here:

(* Disclosure: TheCUBE is a paid media partner for the “AI & Analytics: Shaping the Future With Alteryx CEO & Tom Davenport” event. Neither Alteryx Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE