ROI of AI

AI (Artificial Intelligence) holds great promise for the future of business. Still, these facts show that 75% of companies won’t see a return (Return on Investment) and ROI of AI even after a few years and are likely to set back their company culture even longer.

ROAI. 6 steps to a successful ROI of AI

We work with companies to ensure that the adoption, implementation, and measurement are successful, generate a return, and improve the workplace. Here’s what we do.

1. Establish target goals and talk about them with employees.

Begin by envisioning what success with AI looks like. Quantify the level of improvement within a specific timeframe. Let your employees know what you’re thinking and how it will improve the company and profitability. Here are examples.

  • Increase revenue by 25% in a year.
  • Generate 35% more qualified leads within 6 months.
  • Decrease operating costs by 60% in 2 years.
  • Process more claims to see 30% greater profits in 6 months.
  • Summarize clinical studies more accurately to achieve 20% better health outcomes within 1 year.
  • Analyze purchase behavior more efficiently to predict future behavior, resulting in a 30% increase in revenue per customer within 15 months.
  • Increase transaction speed for customers at the drive-thru by 40% within 6 months to generate a 20% increase in income.

2. Define key tasks

The tasks AI performs are how you hit your target and ROI of AI. Tell your employees about its impact on them. 72% of employees trust AI to bring value to their processes through greater productivity, improved decision-making, and better experiences. Here are some considerations.

  • Generate content, images, and videos.
  • Create an AI agent or sales agent to handle inquiries and answer questions and requests.
  • Automate business processes like resume screening, email writing, and consumer onboarding.
  • Automate accounting processes like data entry, invoicing, and payment.
  • Personalize customer service and improve experiences.
  • Generate code to help development teams.
  • Analyze large datasets to identify patterns and predict trends.
  • Categorize data, identify insights, and create action strategies.
  • Predict demand and optimize inventory levels.
  • Conduct financial analysis for risk assessment and fraud detection.

3. Assign an AI taskmaster

The human importance is crucial. While AI can perform these tasks, someone or a team has to be at the helm, managing progress and monitoring results. We can perform this work or train and coach someone on your team. Here’s what they do.

  • Evaluate AI tools for the task and select the most suitable ones. A variety is likely to be required.
  • Allow for mistakes or “hallucinations” that AI makes. Trust me, they will occur. However, it can likely be corrected with an improved prompt, a broader perspective, or targeted to a specific audience.
  • Make improvements, provide assessments, and even switch AI tools when necessary.
  • Establish a measurement plan with a timeframe.
  • Adhere to and uphold ethical standards.

4. Assemble AI toolbox

The selection of AI tools sets everything in motion. Of course, tools vary depending on the task. However, here are some things to know.

  • Content Generation: The LLM (Large Language Model) is the foundation. GPT-4o from OpenAI, Gemini models from Google, and Llama 3 from Meta are leading contenders. Moreover, most have additional capabilities for image, video, code generation, and many other features. Since LLM learns and improves over time, it is best to rely on one.
  • AI Agents: A type of AI system that understands and responds to customer inquiries without human intervention. They can aid a sales force, generate more leads, create presentations, or be a personal assistant. Claude and Copilot are popular considerations for AI agents.
  • AI Automation: Use artificial intelligence and machine learning to simplify business processes, improve decision-making, and reduce manual workloads. Moveworks, Power Automate, and UiPath are the most widely used AI automation tools.
  • AI Analysis Tools: These tools assist with data analysis and offer features such as data visualization, automated insight generation, and simplified data transformation, making them valuable for both novice and experienced data analysts. Tools in this area include Sana, Julius AI, and Microsoft Power BI.

5. Create a measurement plan with a timetable for ROI of AI

AI is measured against two types of metrics: usability and impact. First, it measures how AI performs its task, and second, it measures how it achieves business targets. Here are some examples.

Usability of AI

  • Completion Rate: The percentage of people who complete a desired action based on the total number who had the opportunity.
  • Success Rate: The percentage of success among several attempts to perform a procedure or task.
  • Task Time: The time it takes to complete a desired task.
  • Error Rate: The percentage of processing errors for a specific task or action.
  • Satisfaction Score: A metric from a satisfaction survey that measures how happy a customer is with a specific product.

Impact on Business

  • Conversion Rate: The percentage of users who completed a desired action.
  • Retention Rate: The percentage of customers who continue paying for a product over time.
  • Customer Lifetime Value (CLV): A prediction of the net profit attributed to the future relationship with a customer.
  • Churn Rate: (Lost Customers ÷ Total Customers at the Start of period) x 100.
  • Net Promoter Score (NPS): On a scale from 0 to 10, how likely are you to recommend this product/company to a friend or colleague? Net Promoter Score helps measure customer loyalty based on their responses.

6. Achieve your ROI of AI – ROAI

The ROI of AI (or ROAI) is calculated using the formula above over the established timeframe. Regularly examining your chosen usability and impact metrics can help you keep a close eye on your tasks’ progress and the tools’ performance. This can significantly impact achieving the desired results.

Based on available studies and our experience with ROI, a norm of at least 200% or $2 for every $1 invested is a realistic expectation for a company committed to a successful ROAI.

Does the Return on AI Investment (ROAI) make sense for your business? Interested? Get in touch with Rob at rob@barnraisersll.com.