Emphasizing “Purpose” With AI Spending in 2024

Artificial intelligence may be a powerful and productive workplace technology, but the results can depend on where you allocate AI dollars.

No doubt about it, AI is a cash cow for the creators and developers who bring artificial intelligence products to market.

Worldwide spending on artificial intelligence software, hardware, and services will increase 27% this year to reach $154 billion, according to the International Data Corporation (IDC).

Additionally, approximately half of U.S. chief technology officers say AI represents their “number one budget priority” according to a recent CNBC survey of senior IT executives.

That’s all well and good, and it certainly points to a rosy future for AI from a pocketbook outlook, but a big question remains on AI spending.

How should chief financial officers and other senior execs tasked with managing company budgets earmark AI spending?

The CFO offers a valuable tutorial on the topic this week.

“When you hear your dentist talk about the use of artificial intelligence, you know it’s permeated every aspect of our day-to-day life,” noted Brian Unruh, chief financial officer at AI-business services provider ABBYY in a January 18 analysis in The CFO. “Yet, you’ve probably already had more intense c-suite discussions about the product roadmap, resources, and the ever-important topic – budget.”
In that context, CFOs “must understand how AI can impact budgets – and not just in spending”, Unruh said.

One way CFOs can get the most bang for their buck through AI budget outlays is by prioritizing what Unruh calls “purpose-built AI spending”.

Helpful tools like ChatGPT are “constructed of large language models (LLMs) built on one trillion-plus parameter (equivalent to over 1 million books) and optimized for everything.” But that may not matter to a CFO who’s trying to solve a company-wide document management problem.

Unruh equates that scenario to having enough power to light a sizable island when that’s not what a company needs at all.

A Focus on Purpose

Moving “purpose-built” AI strategies is a smarter use of budget cash as it allows companies to steer dollars vertically, to the problems that need solving.

“Purpose-built AI narrows the context and task to the core of what it needs, so it achieves the results the business requires,” Unruh noted. “That has been tested against a focused data set of the world’s most complex documents rampant throughout enterprises. These include invoices, POs, customer correspondences, claims forms, tax forms, and hundreds of other documents that drive a business.”

Unruh advises CFOs to discuss AI budget strategies with key company (and outside) stakeholders before committing dollars to the technology.

“When talking with your innovation leaders and technology partners, ensure the AI they recommend is purpose-built for the specific business problem and has proven results that deliver consistently,” he said.

To illustrate his point, Unruh points to accounts payables.

“Using purpose-built AI to streamline the processing and timing of invoice payments and purchase orders will greatly improve cash cycle outcomes,” he noted. “In this scenario, AI-powered document processing will read, understand, and classify critical financial data into ERP systems.”

Or how about healthcare, where AI can vastly improve otherwise time- and resource-sucking review of medical records to approve patient referrals to see specialists and receive life-saving medications?

By focusing on “purpose” and not necessarily “power”, CFOs can direct AI money to projects and tasks that need help. In doing so, dollars aren’t squandered by lighting up those islands.

Instead, they’ll be lighting up the company’s bottom line.

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