5 Strategies For Getting a Strong ROI with Agentic AI

Investing in agentic AI—or any form of AI—is not a guarantee of success. To the contrary, just 25% of AI initiatives have delivered expected return on investment (ROI) over the past three years, according to IBM industry research. That said, AI is the future. Businesses that don’t invest in AI simply will not be able to stay competitive over the long term. Thus, the question is not whether AI is worth the investment, but rather how to get maximum ROI from every AI investment. 

Unlike previous forms of AI like analytical AI and generative AI, agentic AI is a powerful, encompassing form of AI that can think, learn, and act on its own. The encompassing capabilities offered with agentic AI are precisely why agentic AI has the potential to deliver enormous ROI for businesses—but only if the business is strategic and disciplined. 

Let’s explore five essential strategies for businesses to get a strong ROI with agentic AI:

Identify end-user pain points

Agentic AI is versatile and endlessly customizable. While businesses can integrate agentic AI into any number of workflows and business processes, it doesn’t mean the business should. And the reason is simple: End users won’t use it and may even become so skeptical of it that it gains a poor reputation. Instead, the business should focus on identifying end-user pain points that agentic AI can help solve. 

Read more: 5 Reasons Organizations Are Replacing GenAI With Agentic AI

The process of identifying pain points starts with employees themselves. Businesses need to be prepared to get in the trenches and directly shadow and interview employees to understand the challenges they face. Whether that’s inadequate human personnel to get work done, or human teams prone to making the same types of errors repeatedly, the key is to document what the issues are, then figure out how agentic AI could be configured and optimized to alleviate pain points. When end users can see that agentic AI is implemented with them in mind, they’re much more likely to adopt and buy into the technology.

Constrain scope initially

When end users learn about agentic AI’s integration into their workflows and processes, they understandably get excited. In fact, the better a business is about aligning the technology to the end users’ pain points, the more likely the project is to experience scope creep. As a bigger pool of end users sees more ways to integrate agentic AI into more workflows and processes, the scope of AI implementation can quickly balloon.

As much as businesses may want to ride this momentum, it’s important to constrain the scope initially. Businesses should start with focused pilots that prove out ROI for a single, discrete, measurable element. No matter how well-planned, the pilot will necessarily evolve. Moreover, the business needs time to test functionality, validate alignment with strategic business goals, and build robust governance around agentic AI to ensure it does not become more of a risk than an asset. 

Invest in training AI agents

The hallmark characteristic of agentic AI is that it can learn and think on its own. But that doesn’t mean agentic AI can go from 0 to 100 instantly. Agentic AI relies on AI support agents to serve as the conduit through which this technology provides assistance and insights to human users. Significantly, these AI agents need to be trained (by human teams) in how to do their job effectively. That means human teams need to point AI agents to information about what success should look like, plus where to find the data to enable this learning. AI agents learn how to think and act autonomously through what’s known as reinforcement learning, where they are rewarded for appropriate actions and penalized for ineffective actions.

Read more: 4 Changes Organizations Must Make To Enable Agentic AI

Thus, to get a strong ROI with agentic AI agents, extensive training is essential. Businesses need to be able to define clear objectives and success criteria for AI agents, including what their target response time and accuracy rate should be. Businesses also need to invest in curating high-quality data sets and information to point the AI agents to. Again, it’s up to human teams to set up frameworks and guardrails for these iterative learning processes. These resources are not available out of the box; each business needs to custom-design its own AI learning processes.

Generate customer insights with AI

Agentic AI’s value proposition is its ability to streamline and automate a range of processes and workflows. These improvements reduce friction, ease frustration, and free up employees to focus on higher-value tasks. In the process, agentic AI indirectly contributes to the bottom line. But agentic AI also can directly contribute to the bottom line, by generating customer insights that directly grow sales.

Older forms of AI have been able to assist human teams with automating analysis of customer data streams, but agentic AI takes these capabilities to the next level. Because agentic AI can think and act on its own, agentic AI can autonomously and continuously analyze customer data with minimal human supervision. That enables agentic AI to identify patterns and trends in data—from risks of churn, to changing customer behaviors and sentiment. When agentic AI is generating data-based recommendations for pivots and other changes that grow and sustain revenue pipelines, businesses are proving out the ROI of agentic AI.

Use AI to accelerate coding

To remain competitive, businesses need to continuously expand their business ecosystems—adding apps, automations, interconnectivity, and even integrating agentic AI support agents. Traditionally, coding and development work has been among the most expensive, time-consuming investments that a business needs to make, particularly when a business commits to securing top talent (either in-house or through a contracted partner).

But custom development also is necessary. That’s why businesses should be taking advantage of agentic AI to assist human teams with coding. AI code assistants can write the first draft of code for a project, troubleshoot errors and inefficiencies with existing code, and prioritize among coding issues that a business needs to address. These cost-intensive, laborious tasks can be done far quicker and to a higher standard of quality than human teams can do, ensuring a strong ROI.

Final thoughts 

Agentic AI is like having a large team of highly skilled employees who never want to clock out, who want to absorb and learn as much as possible, and who are 100% committed every day to getting better at what they do. To ensure businesses can get a strong ROI with agentic AI, it is crucial for businesses to identify end-user pain points, guard against scope creep, develop high-quality training for AI support agents, generate customer insights with help from AI, and use AI to help with coding and development projects. 

If you are ready to extract maximum value from your business’s agentic AI investments, we encourage you to reach out to the agentic AI experts at Fullcast. We can help you set in motion the activities and investments that will keep agentic AI firing on all cyclinders, and ultimately guarantee the strongest possible ROI from agentic AI over both the short and long term.