Are you wondering what the ROI Of AI Initiatives is in the community banking world? Artificial intelligence has quickly become a tech solution that businesses of all sizes across sectors are either implementing or looking to do so soon. While AI is helping companies transform operations and streamline internal processes, consistently measuring the return on investment of AI initiatives is key to ensuring continued investments result in favorable business outcomes.
Below, 19 Forbes Business Council members share ways businesses can measure the ROI of AI initiatives. Read on to learn specific metrics they recommend businesses closely track.
1. Understand The Impact On End Users And Staff
In healthcare, measuring soft ROI Of AI Initiatives is key to understanding whether AI reduces friction and clinician burnout. Seconds matter and are integral in creating more meaningful patient interactions and workforce satisfaction. Business leaders across all industries should measure how quickly end users access the information they need to excel, which in our case, drives better care experiences and quality. – Greg Samios, Wolters Kluwer Health
2. Divide Tasks Into Specific Steps
Breaking down tasks into smaller, precise steps can help us better understand the time, effort and energy required to execute them. With AI, even small error rates can compound significantly. For example, if an AI performs five sequential tasks at 90% accuracy, the overall success rate drops to 59% (0.9⁵). Thus, to maximize ROI, we should focus on step-level accuracy or implement human oversight. – Shivangi Khurania, Udeso
3. Track The AI Adoption Curve
Track the ROI Of AI Initiatives and your company’s adoption curve by monitoring how quickly your team embraces the technology and how it shifts workflow efficiency. Measure time saved, error reduction and decision speed on projects. Instead of focusing solely on output, track how AI accelerates processes. The true ROI lies not just in numbers but also in how AI transforms your team’s capacity to do their jobs. – Sam Nelson, Downstreet Digital
4. Prioritize High-Impact Use Cases
To measure the ROI of AI initiatives, businesses should focus on high-impact use cases that drive automation, efficiency, productivity and revenue growth, while also addressing data silos and enhancing data management. It’s crucial to identify areas where AI can have the most impact and to track metrics like cost savings, operational improvements and productivity. This ensures long-term value and success. – Sheila Rohra, Hitachi Vantara
5. Measure Margins Before And After Making Changes
I’d recommend measuring your margins before and after AI implementation. Margins reflect your team’s efficiency and output within a certain amount of time, which ultimately reflects the ROI Of AI on the platform you’re testing. – Emily Reynolds Bergh, R Public Relations Firm
6. Analyze Efficiency
When we implemented AI for a client, costs dropped 30%, but the real impact was efficiency. Workflows ran faster, and their team focused more on high-value tasks. Sales conversions increased, and customer satisfaction improved with quicker responses. AI isn’t just about saving money — it’s about building a smarter, more agile business. True ROI comes from tracking both financial and strategic gains. – Naresh Prajapati, Azilen Technologies
7. Examine Gains Versus Costs
Measuring the ROI of any technological investment is rather straight forward when you look at the gains vs. costs. Oftentimes, we see that organizations fail to properly capture the hidden costs of AI initiatives. Increased costs associated with cyber security, data governance, data storage and employee upskilling are usually missed when calculating the true ROI of AI initiatives. – Cory McNeley, UHY Consulting
8. Measure Process Improvements
One effective way to measure AI ROI is by tracking process improvements. Key metrics include cost savings, time reductions, error rate decreases and revenue per transaction. Additionally, monitoring customer satisfaction and system utilization helps gauge AI’s overall impact on business efficiency and growth. – Henri Al Helaly, EXILLIUM
9. Monitor Customer Engagement
There’s no point in using AI just for the sake of it, as it should solve actual issues customers have. To ensure good ROI, make sure the AI feature is something clients will actually benefit from. Once it’s implemented, track engagement with the new AI functionality. If customers avoid it, it’s likely not adding any real value. – Rytis Lauris, Omnisend
10. Measure Resolution Time For Frequent Problems
Measure the resolution time for common problems. When we implemented AI at LambdaTest, we truly measured how machine learning went from troubleshooting common testing failure issues from an average of hours to minutes. ROI should be measured by comparing normal processes to the AI uptime at a multiplied frequency of constant. – Maneesh Sharma, LambdaTest
11. Gauge Cost Savings And Revenue Growth
Businesses can measure the ROI Of AI Initiatives by tracking cost savings and revenue growth. Key metrics include automation efficiency (time and cost savings), customer engagement (conversion rates and churn) and operational improvements (error reduction and uptime). – Eran Mizrahi, Source86
12. Track Time Saved
Track time saved, not just dollars earned. One clear way to measure AI ROI is by calculating hours reclaimed across tasks like content creation, customer service, research and operations. Link that time to output, such as more leads, faster delivery and a better customer experience. AI should make your team faster, sharper and more focused on high-value work. If it’s not freeing people up to grow the business, it’s not worth it. – Michelle Gines, Purpose Publishing
13. Measure Decision Velocity
AI investments must be measured beyond cost savings and actually ensure they drive a competitive advantage. One key metric is decision velocity. Faster, data-driven choices create outsized returns. Track revenue impact, efficiency gains, error reduction and adaptability to market shifts. AI’s true ROI isn’t just in numbers; it’s in how decisively and intelligently a business moves. – Reid Rasner, Omnivest Financial
14. Track The Gap between Hypothesis And Results
Keep it as simple as a fourth-grade science fair. Instead of vague “innovation” metrics, measure AI ROI by tracking the gap between hypothesis and results. Before implementation, document your expected outcomes with concrete numbers (e.g., cost reduction, time savings, etc.). Then compare results against predictions. Force accountability so you don’t move goalposts after AI deployment. – Shayne Fitz-Coy, Sabot Family Companies
15. Bring In Specialists
AI is one of the toughest areas to track when it comes to investment today. If I were investing, I’d bring in a team of specialists to analyze project performance, gather user feedback and monitor product growth closely. The biggest challenges in this space are the complexity of the technology, the high level of customization and the general reliability. – Dmitrii Khasanov, Arrow Stars
16. Identify New Capabilities
All businesses exist to grow revenues and increase profitability, so these must be the KPIs for AI as well. However, I would argue that the real ROI for AI can be measured by answering what business capability — which was not possible before — was made possible by AI and had the maximum positive impact on KPIs like revenue growth, profitability or customer experience. – Krishnan Ramanujam, Tata Consultancy Services
17. Focus On Tangible Outcomes
Measuring the ROI of AI initiatives doesn’t have to be complicated. It’s about keeping things simple and straightforward by focusing on tangible outcomes like cost savings, revenue growth or productivity improvements. For example, if AI reduces customer service response times, track the resulting labor cost savings and improved customer satisfaction to clearly see the impact. – Muhammed Uzum, Grape Law Firm PLLC
18. Monitor The Impact On Employees
Track employee capacity and revenue per employee. If AI is working, your team should do more with less, leading to faster execution, higher output and stronger margins. It’s not just about cost savings; it’s about multiplying impact without multiplying headcount. – Hope Horner, Lemonlight
19. Ask How It’s Moving The Business Forward
To measure AI ROI, we need to start by asking how it is moving the business forward. I look at metrics that tie directly with faster sales cycles, better lead quality or time saved on manual tasks. It’s not just about the tech but about real impact. Track what matters to your goals, and let that tell the story. – Sonali Nair, Segment Agency
If you’re making decisions around AI and tech in your community bank reach out to us and let’s have a conversation about what’s working for others.
By Cory McNeley, Managing Director, UHY
Originally published by Forbes