Artificial Intelligence

How to Measure the ROI for Artificial Intelligence

A recent MIT study found that among the 90% of companies that have made at least some investment in AI, fewer than 2 out of 5 report obtaining any business gains from AI in the past three years.

Further, 70% of companies report minimal or no impact from AI so far.

Troublesome, given the hefty financial investment companies are making and the expected payoff, Kara Longo Korte, director of product management at TetraVX, shares how companies can demonstrate the ROI of their AI investments.

Artificial intelligence (AI) offers significant opportunities for digital transformation, but business leaders are struggling to prove it’s a worthwhile investment. A recent MIT study found that fewer than two out of five companies cite business gains from their AI investments in the past three years, and 70% of companies report minimal or no impact at all.

These numbers are troubling, given that companies are making substantial financial investments in AI and expect similarly large payoffs. The good news? The implementation of AI solutions actually can deliver a healthy ROI – but the key is identifying the right metrics to measure it.

Learn More: How Has AI And IoT Changed Human Work Experiences In Day To Day Life

Qualitative metrics can prove AI’s value to your organization

Not all ROI can be reduced to numbers, some ROI lies hidden in qualitative metrics. In the case of AI, qualitative data measures the human experience related to new technology investments. You can prove the ROI of AI by focusing on two specific qualitative metrics: employee and customer satisfaction.

Employee satisfaction

To fully assess the value of ROI through the lens of satisfied users, it’s important to have a sense of “before” and “after” metrics. You might focus on the degree to which ease-of-use has been enhanced or the extent processes have been accelerated.

For example, when coupled with analytics, AI programming helps enhance collaboration and communications in a variety of ways. Voice assistants, for example, could have future capabilities to help schedule meetings, translate calls, and send text messages. This could allow more time for high-value work and improve employee satisfaction — and outcome ripe for capture in a before/after qualitative metric.

Customer satisfaction

Regardless of whether or not the new technology or platform is strictly customer-facing, positive changes to processes will trickle down to the customer experience. Most organizations already have some way of measuring customer satisfaction, whether it’s through surveys, a Net Promoter Score (NPS), etc. You should examine these metrics before and after the implementation of an AI solution to gauge success and uncover the need for any necessary adjustments.

Without an analysis of customer satisfaction as a whole, it can be difficult to fully evaluate AI’s value to customers. For example, in the contact center, AI introduces the “chatbot” into the customer service process. These “virtual assistants” —- software programs designed to act like humans —- automatically engage in conversations with customers while also managing their transactions. This improves the organization’s ability to provide a more personalized experience using customer data and significantly reduces time to resolution.

Learn More: Why the U.S. Needs a Department of AI

What if You Sill Struggle with Showcasing the ROI of AI? ROI you Hoped For?

If you’re still struggling to demonstrate the ROI of AI technology, speak with users to identify the challenges they face with the new system. The conversation should clearly define why the solution hasn’t proven successful. Next, consult your vendor or IT consultant. In some situations, low user adoption or dissatisfaction is the result of inadequate training or poor configuration, both of which are easily solved.

Lay a Foundation for the ROI of Future Investments

Technology investment conversations should always start with a focus on end-users and identify which users will use the platform and how they will benefit. By focusing on end-users, you can temper unreasonable expectations for the technology prior to implementation. In many cases, the nuances of AI technology mean that improvements to the employee and customer experience aren’t immediately visible, but emerge over time.

You should also perform due diligence before choosing AI or any other technology, both internally and with potential vendors. Ideally, your technology partner will help define the success of the AI solution and provide support in areas that impact the technology’s success.

Finally, before you launch an AI initiative, you need to choose the right problem for the technology to solve. Without a clearly defined problem, it will be impossible to determine the success or demonstrate ROI.

At this point, most of us recognize that AI has the potential to provide significant value for organizations across industries. When given a clear problem to solve, AI solutions can accelerate processes, streamline workflows, and produce happier customers and employees. By laying a solid foundation for AI investments and identifying the right metrics, you can demonstrate the ROI of the technology now and set the stage for additional AI investments down the road.

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