How To Get ROI From AI/ML Projects

When it comes to AI adoption, one of the most important questions for business leaders is, “If we invest in artificial intelligence, what will be our ROI?”

Broadly speaking, there are two major perspectives to consider when thinking about return on investment from AI projects: short-term ROI and long-term ROI.

Many people providing AI services tell their clients that ROI is highly complex and difficult to get. This may be the case when solving some problems, especially if they haven’t been solved before, but in many cases the ROI is quite straightforward.

“Complexity is the enemy of execution.” – Tony Robbins

There are many companies stuck in “AI pilot purgatory” unable to get past POCs and prototypes. We all want ROI, but we often overcomplicate things, especially when it comes to AI. This perception of complexity becomes the bottleneck for companies, holding them back from breaking through to the next level. That’s why it’s crucial for business leaders to have a solid understand of how AI works to allow them to make better decisions (check out my blog post titled, “AI Fundamentals For Business Leaders” for more information).

To maximize your chances of short-term ROI, choose a problem you are already solving.

One of the biggest mistakes companies make when adopting AI is choosing a complex problem to solve. This is tempting, especially when hearing all the hype about the ‘magical’ capabilities of AI, but it is a common pitfall.

Instead, choose a problem you are already solving. This allows you to start with a performance benchmark to aim for. You know precisely what the problem is, you know how well you are solving it right now, and you can compare the AI solution vs the current solution.

Prove AI’s value and capabilities for your organization this way before expanding to more complex use cases. This will allow you to understand what success means in an AI project, what are the challenges, and what true ROI looks like.

Once you get ROI at this initial scale, you can expand the same use case to get more value out of it. Alternatively, you can choose other use cases where you leverage your experience and results from the first use case. There are always transferable lessons and best practices that allow you to keep transforming your organization with AI.

Check out my blog post titled, “Getting Started With Enterprise AI” where we touch on this topic, along with other key things to consider before starting an AI/ML project.

When assessing long-term ROI, ask yourself the following questions:

“Where is our sector going and who will ultimately win when it comes to AI disruption?”

“How will AI capabilities enable the ultimate market winners in our industry?”

“What are AI thought leaders in our sector seeing and predicting 3, 5, 10 years from now?”

“What are the current AI trends in our industry, what do they have in common, and where are they headed?”

“What data will be valuable in the long-term, and how can we collect/clean it over time?”

“When looking at the future AI-transformed version of our company, what processes are streamlined and automated?”

“What business functions will no longer require manual human labor in the future?”

“What aspects of our products/solutions would make it such that customers would not want to buy from anyone else? (price, features, value, user experience, etc.) What data would enable this?”

“What would be our ultimate competitive advantage if we leveraged AI and data?”

These are some of the questions asked by companies leveraging AI successfully. They always connect short-term ROI to long-term ROI. This allows them to win now and dominate in the future.

Artificial intelligence is permeating every industry, and this effect will only increase over time. Business leaders must strive for short-term ROI, but they cannot afford to ignore the long-term value of AI for their company. Every industry will be infused with AI technology and capabilities, and we have to anticipate these changes to prevent disruption.

This is a high-level framework to help you think about ROI for your company. Whether you are getting started with AI adoption, or you are expanding your current use case(s), keep both short-term and long-term ROI in mind.

For specific examples of ROI from AI projects, check out our latest client case study.

If you need help to accelerate your company’s machine learning efforts, or if you need help getting started with enterprise AI adoption, send me a LinkedIn message or email me at info@carloslaraai.com and I will be happy to help you.

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Client case studies and testimonials: https://gradientgroup.ai/enterprise-case-studies/

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