Are You Gauging ROI on AI Investments?

Corporations are investing heavily in artificial intelligence, with worldwide spending projected to top $2.5 trillion this year, according to Gartner, Inc. However, the question still remains: What value exactly are businesses receiving in return for their investments? That is, what is the ROI on AI?

A survey conducted by RGP found that only 14 percent of CFOs have seen a clear, measurable impact from their AI investments. In a separate survey conducted by PwC, just 12 percent of CEOs said they have experienced higher revenue and lower costs by implementing AI technology and 55 percent saw no benefit from AI at all.

This is not a verdict against AI — far from it. Rather, it’s a verdict against how many organizations are implementing AI and failing to track its benefits. AI is delivering real value primarily for businesses that apply the same rigor to implementation and ROI analysis as they do any other capital allocation decision.

Where AI Value is Occurring

For businesses that are seeing real value in their AI investments, this ROI is occurring mainly in three areas:

1. Operational efficiency
This includes accounts payable and accounts receivable automation, invoice processing, expense reconciliation and acceleration of financial close.

2. Financial planning and analysis (FP&A)
AI systems that can synthesize large data sets, model scenarios at speed and surface anomalies in real time are enabling finance teams to produce more accurate forecasts, identify cash flow risks earlier and make better capital allocation decisions.

3. Risk reduction
AI is delivering measurable value to businesses in highly regulated industries through improved compliance monitoring, enhanced fraud detection, reduced audit preparation time and the avoidance of regulatory incidents.

Establish Baseline Metrics

To successfully measure return on your AI investments, it’s important to establish baseline metrics before deploying AI initiatives. It’s much more difficult to calculate ROI without establishing a defined performance benchmark upfront. The most effective ROI measurement frameworks operate on three levels:

Level 1: Efficiency metrics
Metrics such as error rates, hours of manual labor displaced and cost per transaction are fairly accessible and should be tracked from the beginning to gauge operational payback.

Level 2: Outcome metrics
While they may take longer to measure, these metrics — such as increased revenue, improved forecasting accuracy and higher customer satisfaction levels — often reveal the most useful insights for finance executives.

Level 3: Capability expansion metrics
In other words, what can your business accomplish now that it couldn’t before? What projects have been completed that wouldn’t have been before? And how has your competitive position been strengthened?

Demonstrate the Value of AI

Gartner identifies the following metrics that can best demonstrate the ROI on AI to your board members, investors and stakeholders:

1. Sales conversion rate
Sentiment-analyzing AI tools can analyze customer communications to help businesses adapt their sales messages in real time, creating emotional resonance with customers and prospects. Track the adoption rate of AI-driven recommendations during the sales process.

2. Average labor cost per worker
AI often allows lower-skilled employees to perform the work of more experienced employees, which can lower payroll costs. Select a standardized function like customer service where performance can be quantified and test whether employees using AI deliver equal or superior results as those not using the technology.

3. Time to value
In other words, how quickly does your company realize returns from new business initiatives? Use AI to analyze sales and marketing data from the past year and identify common obstacles that slow down the sales process, lowering revenue.

Concluding Thoughts

While corporations are investing heavily in AI, there’s still some question as to what kind of ROI on AI they’re receiving in return. Studies reveal that a small minority of CFOs and CEOs are realizing higher revenue and lower costs by implementing AI technology. Now is the time to establish baseline metrics to help you calculate the return on your AI investments — before you have dived too deeply into the AI waters.

Arthur F. Rothberg, Managing Director, CFO Edge, LLC