Regardless of industry, many companies are concerned about maximizing return on investment (ROI). To achieve good ROI, organizations are looking into AI automation solutions, which can transform the way companies operate, streamline processes, and automate repetitive tasks.
As AI automation attracts good financial benefits, getting clarity on its ROI is required. According to a Deloitte study, many firms report a favorable ROI. Some of the key areas yielding returns include IT operations (69%), customer service (74%), and decision making (66%). It is important to note that not all firms experience a tangible ROI.
In this blog post, we will understand the role of AI automation in attracting good ROI. Next, we will cover ways to maximize ROI. Also, we will gain insights into the challenges of measuring ROI in AI and automation.
Understanding ROI in AI Automation – Key Metrics to Consider
Measuring ROI in AI and automation is crucial. Identifying key performance indicators will help you in this regard.
- Process efficiency: Here, you can track the time taken to execute a given task during pre and post AI implementation.
- Error reduction: Compared to automated ones, measure the error numbers associated with the manual process.
- Customer satisfaction: To gauge the impact of AI-powered solutions, monitor feedback and customer satisfaction surveys.
Tangible benefits
AI automation offers many quantifiable benefits that impact the bottom line. Let’s look at some examples.
- Improved efficiency and productivity: AI frees up employee time to prioritize other important tasks by automating repetitive tasks, leading to measurable gains.
- Cost savings: With AI automation, you can reduce labor costs connected with manual processes. Moreover, this leads to cost savings via improved quality control.
How to maximise ROI in AI and Automation?
The ways to maximize ROI in AI and Automation include the following:
1. Identify high-end use cases
First, determine where you would like to implement business process automation.
Then, start with assessing your current processes and workflows, determining tasks to be streamlined via AI automation technology. Next, look for functions that are time-consuming, repetitive, and error prone.
Let’s look at some of the use cases.
- Invoice processing: Streamline data extraction and data validation from an AI-powered accounts payable (AP) automation. Here, you can match invoices with receipts and purchase orders, offering productivity to your AP staff.
- Mailroom management: Manually managing digital mail can be a time-consuming process. Also, the monotonous mail-related tasks do not end as the mail is distributed. To help you out, use a digital mailroom that uses AI to automate the process.
2. Set clear automation goals
Here, you can set defined goals to achieve a high return on investment. While setting your goals, take past performances into account. Look for hidden costs connected with manual processing, like errors. To get an idea, survey the staff to know their challenges and the processes to improve.
3. Develop performance monitoring strategies
If you can’t monitor goals, you’re not on the right track.
Achieving ROI from AI automation needs consistent monitoring, iteration, and measurement. Here, KPIs can help you track the effectiveness of your AI initiatives, including cost savings, productivity gains, and customer satisfaction metrics.
Leveraging analytics and reporting tools are also important in monitoring performance in real time. Using these insights can update your automation workflows to drive quality outcomes. With a data-driven approach to optimization, you can maximize the ROI of your automation efforts.
4. Invest in infrastructure and data quality
The effectiveness of AI automation solutions heavily relies on the accessibility and quality of your data. By investing in the right infrastructure and data quality, your AI algorithms can have access to clean and relevant information, improving the reliability and accuracy of your automation initiatives.
Attaining quality infrastructure involves implementing data governance policies, consolidating data from disparate sources, and utilizing advanced analytical tools to drive actionable insights.
5. Choose the right business process automation partner
This is an important step in achieving a higher ROI in AI automation.
According to a survey, 78% of firms feel that software vendors make it tricky to access data. To combat this issue, we need to identify the remaining 22% of vendors who provide this data without any hassles.
Evaluating an AI automation partner’s data management strategy is a good practice. You can request example reports, demonstrations, and references.
In the US, there’s a data breach at $9.48 million. This shows that there is a need implement effective data security measures. This holds true for partnering with a vendor as well. Ensure that your needs are clear to your prospects and always review their portfolio for better clarity.
6. Build a good business case
To drive ROI, you must invest in AI automation tools. Prepare a solid business case that can help you outline the following
- Design a cost-benefit analysis over a specified timeframe.
- Forecast the ROI from the AI automation project.
- Estimate the time taken to recoup the initial investment.
- Learning ways automation will help employees focus on higher-value tasks.
- Apply the necessary security measures to avoid any errors.
With these pointers, a business case can ensure key involvement of stakeholders to achieve objectives and undertake critical activities to improve ROI.
Challenges in Measuring ROI in AI Automation
Although the above metrics offer valuable insights, learning the challenges associated with AI automation is important
1. Data availability
Comprehensive data collection is necessary to accurately measure ROI in AI automation. Companies may not have the necessary data infrastructure to scrutinize relevant inputs.
2. Intangible benefits
Some of the advantages of AI and automation like informed decision making and improved competitive advantage are tricky to quantify monetarily.
To overcome these hurdles, firms need to focus on both qualitative and quantitative metrics and develop good benchmarks for measuring progress.
Data-driven decision making is a key factor of successful AI and automation processes. By measuring performance, firms can unlock the full potential of AI-powered technologies.
iTCart, an AI automation company, will help your organization in driving ROI by leveraging its AI systems. Their services will help you stay competitive. From business process automation solutions to document management systems, the organization offers 360-degree AI-powered services that ensure the overall development of your business.
