10 reasons why every business needs to know AI ROI


“If you can’t measure it, you can’t manage it.” – Peter Drucker.


Over 50 years ago, one of this century’s most noteworthy management consultants and business visionaries made this statement about innovation and marketing. If Peter were with us today, would he make this statement about AI? And AI ROI? Consider these statistics.

Peter’s wisdom has never been more relevant considering AI’s adoption rate. Moreover, for companies implementing AI programs, knowing AI ROI provides a way to measure and manage it and a scalable path to success. Here are ten reasons why.

1. Cost

AI is not free. First, it will require an investment—possibly a significant one. Businesses investing in AI programs can expect to pay between $6,000 and $300,000.

2. AI Functionality

The software system alone is estimated to range from $900 for third-party solutions to $200,000 for custom solutions. Moreover, there is a cost to maintain and monitor it. AI functionality measurements like F1 score, ROC curve, and AUC should be checked to ensure your AI is doing what it should. Otherwise, how do you know?

3. Time to Implement

Building an AI solution takes time, anywhere from 3 months to a year or more, usually in the phases of discovery, planning, and building.

4. Customer Experience

There will be differences in the customer experience. AI ROI should consider metrics like completion rate, task time, error rate, and NPS (Net Promoters Score) to see if these differences create better or worse user experiences.

5. AI ROI Range of Results to Date

Microsoft, IBM, and Deloitte have conducted studies to show the ROI of AI. And they range from companies seeing an $8.00 return for every $1.00 invested to companies that are losing money. Moreover, as you might expect, big tech companies see significant results while many others are getting burned.

6. Test and Learn Opportunities

PwC says, “AI is still at a very early stage of development.” That’s why businesses should adopt a “test and learn” approach. Results to date show focusing on repetitive tasks that employee tracking Software don’t like and therefore might make mistakes may benefit from greater efficiency and may achieve the most success. That’s why they may be an excellent way to integrate AI into a company less threateningly.

7. AI ROI Goals

To achieve success, you have to define it. This is true in life, business, and AI implementation. Establishing goals for success demonstrates vision, commitment, and accountability. Firstly, goals show what you aim to do. Should circumstances change, they can be revised. Secondly, they also may cause a business to focus on a more thought-out program that is more likely to succeed. Here are AI ROI case studies that have been conducted to date to help with planning.

8. Scalability

Scalability is the ability of a system or process to handle an increasing amount of work or growth. It requires a robust foundation of processes that can adapt and evolve with the growing demands of the business. That’s why proof positive in the present will be so valuable for scalability in the future.

9. Funding

Considering the investment required, funding is always going to be an issue. However, the team that can show the ability to generate a return is much more likely to get the financing they are seeking.

10. Human Touch

Artificial intelligence technology allows computers and machines to simulate human intelligence and problem-solving capabilities. To many, this is seen as a threat. However, these capabilities can only be controlled for the greater good of a business, with the human touch of the people in charge guiding the outcome. Moreover, results will always be more significant with a human touch at the controls.

Do these reasons help convince you of the need for AI ROI with your business?

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