7 Intelligent Automation Examples Leveraging AI for Business Success

One powerful example of intelligent automation that uses AI is customer service chatbots. These AI-powered chatbots can greet, help, and solve inquiries automatically, instantaneously addressing questions and support requests at an incredible scale and speed.

Picture your customer contacting you at the stroke of midnight and still receiving immediate assistance—that’s the magic of AI. Businesses save on operational costs and human agents can be freed up to handle more complex tasks.

By adopting this intelligent automation that uses AI, companies can improve the customer experience and run their organizations more efficiently. So come along as we explore real world examples and the big difference they make.

What is Intelligent Automation?

Intelligent Automation is the dynamic combination of technologies, such as AI and machine learning, that aim to improve business processes and streamline decision-making. AI-powered automation, especially generative AI-equipped Intelligent Automation, allows businesses to solve complex tasks beyond just automating basic processes to those that require human-like reasoning.

This approach lends itself to greater process volume, creating a scalable solution for organizations of all sizes.

AI's Role in Intelligent Automation

AI is revolutionizing Intelligent Automation, powering systems to learn and improve over time. Take the mortgage industry, for instance, where less than 1 in 5 customers use their main bank when they get a mortgage.

Intelligent Automation allows banks to deliver the customer experience today’s consumers expect by simplifying application processes and accelerating and reducing the margin for error.

Intelligent Automation vs. Traditional Automation

Intelligent Automation is a step beyond robotic process automation (RPA) and standard automation, incorporating the power of various advanced technologies. To improve efficiency, it blends Robotic Process Automation (RPA) and Intelligent Document Processing (IDP).

This means it can create intelligent interactions end-to-end and across the enterprise – from smarter HR to streamlined customer service. It fosters a more collaborative culture that better connects teams to broader business objectives.

Key Components of Intelligent Automation

Intelligent automation is built on a foundation of RPA, IDP and process mining applications. These three aspects encourage hyperproductivity and the democratization of tools along team lines.

Intelligent automation makes the use of AI safe, introducing governance and guardrails to keep AI responsible. Through unifying enterprise applications and refreshing information across databases, it automates manual workflows such as claims processing, dramatically improving precision and speed.

Benefits of Intelligent Automation

Intelligent automation uses AI technologies to simplify business processes, offering critical benefits like invoice processing efficiencies.

Increased Efficiency and Productivity

By using intelligent automation to free up time spent on repetitive, manual tasks, teams can spend their time on more strategic initiatives.

In the banking industry, AI is able to process 99% of loans in under a day. As a result, service delivery becomes incredibly fast.

This level of efficiency enables your team to do more with less. You can have super high productivity without having to hire more people.

Reduced Operational Costs

That’s because operational costs are inextricably tied to staffing. Intelligent automation reduces the burden of hiring additional support agents, because intelligent automation can respond to customers on its own.

This saves money on payroll costs which improves efficiency companywide. For example, automating routine tasks in HR, such as onboarding and paperwork, minimizes the time and costs associated with new hires.

Improved Accuracy and Compliance

By removing the possibility of human error, automation helps your organization remain compliant even in some of the most highly regulated industries.

By removing inefficient manual data entry processes and automating analysis and reporting, organizations can reliably stay ahead of compliance requirements and stay competitive.

Enhanced Customer Experience

AI-driven systems are able to process and respond to customer inquiries quicker, leading to an increase in overall customer satisfaction.

Take last-mile delivery—here, intelligent automation can analyze constantly changing, real-time data to determine the most efficient delivery routes, providing faster service at a lower emissions cost.

Better Decision-Making

AI delivers targeted recommendations on go-to-market strategy and enables organizations to optimize their sales motion, accelerating new sales.

Not only does it process data trends faster than any individual employee, but its predictive analytics gets them the context they need to act before their competition does.

How AI Powers Intelligent Automation

Intelligent automation, powered by artificial intelligence (AI), is improving both the public and private sector efficiency through intelligent automation examples. This technology takes the grunt work out of the equation, allowing organizations to focus on value tasks and making a greater impact.

Natural Language Processing (NLP)

With the help of natural language processing, or NLP, technology is allowing machines to understand and respond to human language. In healthcare, for instance, AI has the ability to constantly curate patient data and effectively sort through it all for more precise diagnosis and treatment.

This intelligence cuts down on the time-consuming administrative task of looking up patients’ care history, freeing medical staff to spend more time attending to patients. By creating rich communication experiences, organizations can engage individuals in a way that feels decidedly human, even within intelligent automated workflows.

Computer Vision

Computer vision makes it possible for machines to understand and make decisions based on visual data. AI relies on technologies like optical character recognition (OCR) to read and capture text, automatically extracting data from documents, images, and PDFs.

This powerful feature can eliminate hours of tedious and error-prone data entry, improving both accuracy and efficiency. This is a godsend to industries including finance and logistics. AI improves last-mile delivery routes through real-time traffic, weather, and other data.

This process saves money in fuel emissions and fuel costs.

Machine Learning (ML)

The machine learning algorithms sifting through terabytes of data are providing insights that inform business decisions and strategies. AI can better enable businesses to increase sales through recommending sales strategies and optimizing sales processes already in place.

Consolidating data from multiple sources makes it easy to track and manage contacts. That drastically simplifies how organizations can get their hands on vital information.

Robotic Process Automation (RPA) Integration

As you’ll see, RPA paired with AI and other advanced cognitive technology forms a powerful, new tool for intelligent automation. Such integration enables the automation of monotonous low-level tasks requiring no human oversight, running around the clock on all forms of data.

In turn, organizations are better positioned to address employee experience and customer-centricity, two key priorities of their stakeholders.

Examples of Intelligent Automation That Uses AI

Examples like these show how intelligent automation, powered by AI, is dramatically changing the way organizations do business. It improves productivity, mitigates mistakes, and frees up staff to work on more high-value initiatives.

Here’s a look at some real world examples.

1. Automate Data Extraction Processes

AI tools are adept at scanning multiple documents, utilizing intelligent automation technology to quickly abstract relevant data that meets a variety of criteria. For example, banks and other lenders can use intelligent automation solutions to extract key information from loan applications, speeding up application reviews by days or even weeks.

2. Streamline Data Entry and Updates

Now picture eliminating thousands of hours of tedious, repetitive manual data entry. AI helps fill in the blanks, updating and correcting databases with current information, saving the industry from data breach liabilities.

This also liberates employees from these monotonous duties.

3. Enhance Customer Service Interactions

Chatbots providing customer support, for instance, are a great use case. In fact, they answer customer inquiries 24/7, giving instant answers to fundamental questions.

When things are complicated, they pass them up to human agents, which increases customer satisfaction.

4. Improve Customer Onboarding Experience

AI systems can customize onboarding experiences, walking new customers through setups based on individual needs, showcasing intelligent automation examples. This relatively simple act creates an immediate transition during which strong relationships can be forged, right from the jump.

5. Optimize Recruitment Processes

Predictive AI, an intelligent automation tool, can sift through resumes, pinpointing highly qualified candidates in a fraction of the time compared to traditional methods. This automation solution saves HR teams hundreds of hours while enhancing candidate quality.

6. Automate Employee Onboarding

Current employees enjoy automated onboarding systems that deliver training materials and paperwork. This helps them hit the ground running.

7. Simplify Payroll Processing

AI automation can help determine the correct salary and deductions, reducing mistakes and ensuring timely payments.

8. Implement Price Optimization Strategies

AI rapidly analyzes consumer behavior and market trends, demonstrating intelligent automation examples by allowing companies to change prices in real-time for optimal profit.

9. Refine Lead Nurturing Techniques

AI tools, as part of intelligent automation solutions, can track and analyze lead interactions, optimizing workflow to convert leads into customers effectively.

10. Accelerate Order-to-Cash Cycle

AI automation streamlines the order taking process, enhancing workflow efficiency and improving cash flow through intelligent automation solutions.

Intelligent Automation Across Industries

Intelligent automation, particularly through generative AI automation tools, is transforming every industry by cutting costs and enhancing business process management. This dramatic shift is perhaps most easily illustrated across both public and private sectors, showcasing intelligent automation examples in action.

Healthcare Appointment Management

For example, in healthcare, AI-powered systems make it easier for patients to book appointments. These same systems lower no-show rates by sending automated appointment reminders, via text, email, or phone—the patient’s choice.

One hospital system in New York used an AI-powered scheduling assistant that improved appointment retention by 25%. As a result, more patients can receive care when they need it. Healthcare providers can make better use of their resources as well.

Financial Services KYC Compliance

In the financial services sector, Know Your Customer (KYC) compliance has always been important. AI-driven tools can automate the complex verification process, quickly scanning mountains of documents and flagging discrepancies in just seconds.

One bank in California has reduced the time needed to perform KYC checks by 40%. This enhancement allows them to onboard customers faster and more securely.

Insurance Underwriting Automation

Insurance companies use AI to enhance and automate underwriting. Automated systems can make determinations of risk factors in a matter of seconds by scanning large data sets.

One major insurance company used AI to speed their underwriting process from days to hours. This automation allowed them to process clients faster without sacrificing accuracy as a focus.

Retail Inventory Optimization

Retailers are leveraging AI to ensure they have the right product, in the right place. Smart automated systems forecast stock requirements based on data trends and customer purchasing patterns.

This approach helps avoid costly overstock and stockouts. One large retail customer experienced a 30% decrease in surplus inventory from using a system like this, improving overall profitability.

Manufacturing Predictive Maintenance

In the manufacturing space, AI is proving indispensable for predictive maintenance. It sifts through equipment data to predict when a failure might occur.

One Texas battery factory adopted AI-powered sensors and achieved a 20% reduction in downtime. This led to millions in gains from improved production efficiency.

Implementing Intelligent Automation Successfully

A proven, structured approach helps you implement intelligent automation solutions successfully. This creates an environment where each milestone serves the purpose of smooth integration and enhances business process management efficiency.

Identify Automation Opportunities

To start, identify the processes that are most suited for automation. Identify the repetitive tasks that suck up countless hours of valuable time like data entry or report generation.

Automating customer inquiries through AI chatbots frees up your team’s most valuable asset—time. This enables them to apply their expertise to more complicated problems, increasing productivity overall.

Choose the Right AI Technologies

Second, determine which AI technologies to implement. Look for intelligent automation tools that incorporate machine learning and other predictive analysis capabilities.

AI-based analytics, for example, can help you forecast customer churn. This enables you to personalize your services to increase citizen satisfaction.

Integrate with Existing Systems

Fitting your AI systems into your current structure and architecture is key. Make sure whatever automation software you choose can integrate or connect with your current programs, including other software like CRMs, to keep everything running seamlessly.

An effective, intelligent system reduces confusion and distraction while improving safety and user convenience.

Ensure Data Quality and Governance

Data integrity is key to automation success. Implement strong data governance policies to ensure data accuracy and reliability.

Consistent audits and validation checks ensure your AI systems are functioning with the most up-to-date information. This accuracy is crucial to developing smart solutions and informing good investment decisions.

Monitor and Optimize Performance

Finally, remember to evaluate your automation systems after they go live. Incorporate a close-eye practice with metrics and user feedback to find the gaps.

Continuous optimization ensures that your automation remains effective and relevant in a changing business landscape.

Challenges and Risks of Intelligent Automation

While there are many benefits to pursuing intelligent automation solutions, it’s important to understand the challenges and risks involved with its adoption. Tackling these issues facilitates easier and safer adoption of advanced business process automation technology.

Data Security and Privacy Concerns

At the same time, as automation grows, the volume of sensitive data it processes is increasing. Businesses need to take data security seriously to protect themselves from raw data hacks.

For example, companies that use AI-based chatbots for customer service should have strong encryption protocols in place to secure sensitive data. The costs of not properly securing data is in the billions of dollars along with harm to reputation.

Ethical Considerations and Bias

Automation systems, frequently powered by AI, can unintentionally replicate biases found in the datasets they learn from. This new form of discrimination, for example from hiring algorithms that prefer some demographics over others, can result in discriminatory employment practices.

The only way to ensure fairness is to continually monitor and adjust these systems to promote equitable outcomes across all user interactions.

Integration Complexity

That said, integrating intelligent automation into legacy systems built on complicated rules is a daunting task. Firms will likely encounter problems with the compatibility of cutting-edge AI technologies and legacy systems.

A manufacturing plant introducing robotics must ensure that these machines communicate effectively with current production lines, which often involves significant investment and time.

Need for Skilled Workforce

The transition to smart automation requires a workforce that is proficient in operating and maintaining these increasingly sophisticated technologies. To address this, companies need to develop training programs which teach employees the skills needed to work alongside intelligent automation.

For instance, an organization implementing AI tools needs to offer training to ensure employees can learn how to harness these new innovations wisely.

Measuring ROI of Intelligent Automation

Measuring the return on investment (ROI) of intelligent automation is crucial for understanding its impact and value. By focusing on the right metrics and intelligent automation technologies, you can effectively assess how automation tools are positively influencing your organization.

Define Key Performance Indicators (KPIs)

First, determine which key performance indicators (KPIs) best align with your objectives. These could be objective metrics such as error rates, processing time, customer response times, etc.

For example, if you automate a customer service chatbot, measure the time taken to resolve queries before and after using the bot versus human agents. That apples to apples comparison is what allows you to really detect the progress.

Track Cost Savings and Revenue Growth

Then, determine your cost savings and revenue increase. As intelligent automation eliminates manual effort and drives down error-related costs, ROI reflects those benefits on the financial benefit side.

For example, let’s say you have a manufacturing firm automating its inventory management. All sorts of various benefits — it can save their operation thousands per month in labor costs, improve order accuracy, leading to increased sales.

By aggregating and quantifying these savings you can create a compelling story to justify further investment in automation.

Assess Customer Satisfaction

Customer satisfaction should be one of the most important metrics you track. Gather feedback using customer satisfaction surveys or net promoter scores to see how your automation is benefitting customer experiences.

When your clients indicate faster resolution of service requests due to automated systems, that adds up to more positive ROI. Satisfied customers come back, helping to ensure revenue for the future.

Monitor Process Efficiency

Lastly, keep an eye on process efficiency. Consider the time freed up by automation and what that means in terms of increased productivity.

For instance, if a business automates its invoicing process, the impact could be measured in time saved that staff no longer spend on invoicing paperwork. This transition frees employees to focus on more value-added, strategic work.

Future Trends in Intelligent Automation

The evolution of intelligent automation technologies is rapidly changing, fueled by technological advances and the adoption of AI automation. These intelligent automation trends are collectively redefining how companies drive their business, improving operational efficiency and workforce productivity.

Hyperautomation

Hyperautomation is the next step beyond traditional automation, where various tools and technologies are connected together. To achieve this, it applies AI to automate complex, end-to-end processes that involve human-like decision-making.

For instance, organizations have started taking advantage of artificial intelligence capabilities to comb through volumes of customer data and anticipate customer buying patterns to automate and enhance sales processes. This automated approach not only shaves time off labor but reduces errors, giving teams back the strategic work.

AI-Driven Process Mining

AI-enabled process mining applications can automatically map and visualize end-to-end workflows, surfacing areas of friction and bottlenecks as they occur. For example, a logistics company could leverage process mining to follow executives’ delivery routes.

This allows them to identify bottlenecks and determine the most efficient routes to provide quicker service. This understanding enables enterprises to operate more efficiently and improve the customer experience.

Low-Code/No-Code IA Platforms

By breaking down automation barriers, low-code and no-code platforms democratize automation, allowing users who lack extensive technical knowledge to create applications. This opens the door for even the smallest of businesses to easily automate tasks without making large investments in IT resources.

Consider a retail environment where an employee can use a no-code platform to facilitate real-time inventory tracking, keeping shelves stocked without the headache.

Intelligent Document Processing (IDP) Advancements

Intelligent Document Processing uses intelligent automation to process documents. For example, a large healthcare provider might use IDP to digitize patient records, eliminating the risk of manual entry mistakes and speeding up access to critical information.

This development increases stakeholder compliance and provides a better service during delivery.

Conclusion

For governments, intelligent automation—work made easier, faster, better by the addition of AI intelligence—is a game changer. It reduces costs, accelerates execution, and increases efficiency. From healthcare to finance, protecting our data while making it interoperable increases transparency and efficiency in our major sectors. Our communities and businesses can only thrive when they fully embrace this powerful new tech. Featured real-world examples help you understand how companies are automating their operations and increasing customer satisfaction every day.

We know that getting started with intelligent automation can seem like a large, overwhelming leap, but it can be achieved in small incremental steps. Monitor issues, follow trends and be able to adjust quickly to new developments. You can gauge success easily using a few simple metrics that illustrate ROI. Don’t miss out—take the leap and find out how intelligent automation can revolutionize your work. Register now and see for yourself what a difference it can make!

Frequently Asked Questions

What is intelligent automation?

Intelligent automation—RPA integrated with AI—fills that gap, maximizing operational efficiency through intelligent automation technology. It automates underlying repetitive tasks and leverages AI algorithms to inform automated decision-making and the ability to learn.

What are the benefits of intelligent automation?

The benefits of intelligent automation are clear—improved efficiency, fewer mistakes, lower costs, and better customer experiences, allowing employees to focus on higher value tasks.

How does AI power intelligent automation?

AI takes intelligent automation to a new level by enabling systems to learn from data, recognize complex patterns, and make decisions with minimal human intervention. This winning combination fuels the development of intelligent automation solutions that continually learn and improve, enhancing business process management over time.

Can you provide an example of intelligent automation using AI?

One major example of intelligent automation is the use of chatbots for customer service. These intelligent bots can respond to questions, incorporate findings, and refine their responses, resulting in quicker service and more satisfied customers.

What industries benefit from intelligent automation?

Finance, healthcare, manufacturing, and retail are just some of the industries where intelligent automation examples show AI as a huge asset, employing intelligent process automation to increase efficiency, accuracy, and deliver improved services.

What challenges come with implementing intelligent automation?

Other hurdles are no less daunting — integrating with current systems, managing change, and adapting the workforce to intelligent automation technologies. It’s critically important for companies to think through these to provide the safest and most effective transition.

How can ROI be measured for intelligent automation?

The ROI can be calculated by looking at the savings from costs, gains in productivity, and overall increase in customer satisfaction. Monitoring these metrics makes a case for future investments in intelligent automation.