Why Leaders Find Intangibles Key To Measuring AI Investment Value

The problem with ROI (return on investment) calculations is that they tend to ignore the factors driving longer term business success. 

This may be especially true for AI and Gen AI, as the upfront costs can be daunting, masking the potentially transformational value to the enterprise. Intangibles like improved decision-making, data quality and customer loyalty may drive the business case for AI. That is why organizations successfully introducing AI to their operations are careful to take a more holistic approach to measurement in order to optimize both impact and outcome. JL  

Alvin Lee reports in Twilio:

Is investment in AI paying off? Figuring out return on AI isn't straightforward because AI benefits may not have immediate financial gains. Setting up AI isn't cheap. Keeping it running isn’t cheap, either. In addition to infrastructure and technology costs, team members must be trained to use it. New talent may need to be hired. The metrics for a traditional ROI calculation are helpful, but ROI doesn’t work for validating investment in AI (because it doesnt include) intangibles important to long-term business success like: increases in customer engagement, improvements in operational efficiency, more accurate decision-making, loyalty, data quality and brand reputation. AI powered insights helps anticipate changing market conditions and better capitalization of opportunities.

Businesses and professionals around the globe are getting on the AI bandwagon, looking for ways to use this exciting technology to design products, supercharge customer service operations, and create innovative services.

But here's the (literally) million-dollar question: Is your investment in AI paying off?

Figuring out your return on investment (ROI) on AI isn't as straightforward as you'd think. So we’re here to walk you through how to think about this complicated question.

First, here’s a primer on AI to familiarize yourself with key terms if you’re new to it: Complete generative AI glossary for businesses.

 

Let's start with the basics. When investing time and human resources—and money—the decision always comes down to ROI. Is it worth it? In business, that’s a fair question to ask.

But with AI, the traditional rules of ROI don’t always apply.

The traditional approach to calculating ROI is straightforward. If you invest money in something, and it generates more money than it costs you, you have a positive ROI.

Compare your gains against your costs. That’s it. But with AI, it’s not that straightforward. Why? Because AI benefits don’t necessarily have immediate financial gains. First, you might see business benefits like:

• Increases in customer engagement
• Improvements in operational efficiency
• Breakthroughs in more data-driven and accurate decision-making

These things can be huge for the success of your business but might not correlate directly to a number at the bottom of your quarterly report.

Along with this, the returns on your AI investment may not show up immediately. But those incremental benefits will add up. In the long run, your business gets saturated with the effects.

Challenges in measuring ROI for AI investments

So here’s where we are: businesses can’t take the traditional approach to quantifying ROI with AI investments, primarily because determining your investment is fuzzy. Now, let’s look at some additional considerations: data quality, intangible benefits, and cost of implementation and maintenance.

Data quality

The effectiveness of your AI models depends almost entirely on the data you use to train those models. Poor data leads to inaccurate models, which then lead to inaccurate predictions and flawed business decisions. Bad data will also mean needing to make corrections and adjustments. So to ensure high-quality data, you’ll need to include data cleaning, validation, and ongoing maintenance in your process.

And that will cost you (which may complicate your ROI calculations).

Intangible benefits

Consider customer loyalty and brand reputation. How do you put a price tag on these? A loyal customer is more likely to recommend your business to others, and that's marketing you can't buy. How does this factor into your ROI? These intangibles might not have a direct monetary value but are all-important to your long-term business success.

Let’s imagine you have an AI-powered chatbot that provides exceptional customer service. The immediate benefit might be difficult to measure—especially in dollars—but the long-term impact on your business may be substantial. You’ll probably see reduced customer churn and higher lifetime value (repeat business) for each customer.

The benefits of AI might not show up in your immediate ROI calculations, but remember, it’s all about the long term.

Cost of implementation and maintenance

Setting up an AI solution isn't always cheap. Keeping it running isn’t necessarily cheap, either. Initially, you’ll likely have infrastructure and technology costs. But you’ll also need to train your team to use it effectively. You might even need to hire new talent.

Then, over time, you may need hardware upgrades or regular maintenance. Ensuring optimal performance from your AI tools won’t be free. Of course, this doesn’t mean that the most expensive tools are the best ones for your business. The key takeaways here are:

• Choose an AI tool for its business fit, not just because it’s the latest (and maybe greatest).
• Don’t underestimate your setup costs.
• Include ongoing costs, just like any other technology or software tool\

 

• Alternative ways to estimate and measure the success of AI

ROI calculations look at gains versus costs. The gain metrics for a traditional ROI calculation are helpful, but do these tell the whole story? No, not even close. So what else should we look at?

Customer satisfaction metrics

The net promoter score (NPS) is a pretty good indicator of customer loyalty. Customer loyalty, by extension, relates to long-term revenue. So when your NPS score is high, that means your customers are happy. And when your customers are happy, they’ll be your brand advocates—or even better, brand evangelists. They’ll recommend your brand to others. The NPS might not directly impact your bottom line today, but over the long haul, it’ll translate to revenue.

Operational efficiency

Automating tasks with AI saves your team time, and that’s a win for your ROI. But how much of a win? The time you save for your team can go toward more strategic tasks, such as tasks dedicated to revenue growth. On one end, you’ll have more efficient and productive operations. And on the other end, you’ll have better capitalization on opportunities. Again, this contributes to long-term ROI, but how this translates to hard numbers is hazy.

Adaptability

How do you determine the concrete financial gains of being agile? AI helps you adapt to rapidly changing market conditions. Even better, it can help you anticipate those changes. As AI tools analyze market trends and customer behavior, you can get an early warning before significant shifts occur. By being proactive with AI-powered insights, you can avoid pitfalls and seize opportunities.

 

AI will impact your ROI over the long term, even if you can’t calculate the short-term financial gains down to the dollar. And while the traditional approach to calculating ROI doesn’t quite work for validating your investment in AI, the gains will permeate your organization over the long term. You’ll see improvements in customer satisfaction and operational efficiency while your business decisions become increasingly grounded in hard data.