Intelligent Automation Use Cases

In case all the artificial intelligence buzzwords have left your head spinning, here's another one to consider: intelligent automation (IA).?

In recent years, the hype surrounding artificial intelligence technology has reached a near-fever pitch. The business world, always on the lookout for the “next big thing” to enhance efficiency and sustain success, has seen a notable increase in discussions about the potential impact of artificial intelligence (AI), with various promises and expectations.

Meanwhile, there’s increasing attention on new tools and techniques falling under the umbrella of “intelligent automation”.?

While one is an integral part of the other, you’ll see that intelligent automation is the future of doing business and AI is the means to help you get there.

In this blog, we’ll take a closer look at the topics of intelligent automation and Artificial intelligence and uncover the business value and benefits that come with integrating intelligent automation into an enterprise’s operations.

Moreover, we’ll delve into specific applications of intelligent automation, focusing on three fundamental use cases: real-time recommendations, immediate alerting systems, and anomaly detection.

What is Intelligent Automation

Untangling the jargon that often swirls around these topics can pose its own set of challenges. Intelligent automation (IA) is not just another term for artificial intelligence (AI), although the two concepts do overlap.?

But before that, let’s start with the concept of automation. At its core, automation involves the use of technology to standardise repetitive tasks, streamlining operations.?

However, intelligent automation (IA) elevates this concept by integrating artificial intelligence technologies, which add cognitive and decision-making capabilities. This combination results in advanced solutions that do more than mimic actions. They can adapt, learn, and make informed decisions, amplifying the benefits of automation.?

In a sense, intelligent automation can be described as the operationalisation of artificial intelligence (AI) within different workflows, which not only brings standardisation but also integrates the transformative potential of AI within the operational fabric of an organisation.?

While there is still immense value in traditional automation, there is a high sense of anticipation surrounding the spectrum of possibilities that artificial intelligence brings to the table.?

Benefits of Intelligent Automation

By applying artificial intelligence to standard automation, businesses can streamline all kinds of tasks, hence stand to see plenty of benefits with one of the most strategically significant being an augmented customer experience.?

The impact of intelligent automation on customer experience is transformative and multi-faceted.?

Beyond improving internal operations, intelligent automation has tangible benefits for customers. The efficiency gained from streamlined workflows and faster processing times, thanks to artificial intelligence, allows businesses to provide more responsive services.?

This integration brings a practical shift in how businesses interact with their customers. The ability to personalise engagements represents a significant departure from traditional one-size-fits-all approaches. Artificial intelligence enables businesses to analyse customer data, preferences, and behaviours, allowing for tailored services and recommendations. These businesses can anticipate customer needs but also set a new standard for customer-centricity, fostering a deeper connection between both sides.?

Another impacted facet of customer services is query resolution.?

In a scenario where a customer encounters an issue tracking a recent purchase's delivery on an e-commerce platform, the integration of AI-powered chatbots proves highly beneficial. Upon engaging the chatbot, it swiftly comprehends the query using natural language processing, providing real-time updates on the delivery status by accessing relevant order information. The AI chatbot efficiently handles routine queries, ensuring swift and accurate assistance, while also seamlessly escalating to human representatives when more complex problem-solving is required.?

Operating 24/7, the chatbot offers continuous support, addressing the limitation of business hours. This integration not only expedites query resolution but also showcases the efficiency of artificial intelligence, contributing to improved customer satisfaction and loyalty through immediate and accurate assistance.

Whether it's quickly resolving queries, offering personalised services, or suggesting relevant product options, the integration of artificial intelligence with automation significantly contributes to an elevated customer experience.

Intelligent Automation Use Cases

Many companies are tapping into intelligent automation’s potential. And like regular automation, IA can be used in just about any industry.

In this section, we’ll delve into specific applications and use cases that highlight the practical benefits of intelligent automation starting with recommendation engines.?

Real-Time Recommendations

Have you ever wondered how Spotify swiftly adjusts its playlist suggestions to match your evolving music preferences? Or, when you scroll through your social media feed on Instagram, do you notice how the explore page tailors its content to your recent engagements? Companies like Spotify and Instagram use real-time recommendation systems, ensuring that content suggestions adapt to your interactions and preferences in the moment.

Consider Spotify as a case in point. You're much likely to choose Spotify as your go-to music streaming platform, when you feel the service is tailored to your liking. Spotify does such a wonderful job at understanding your music preferences, delivering personalised playlists and song recommendations that you develop a deep sense of loyalty to that brand, directly influencing the platform's bottom line through increased user retention and sustained subscription revenue.

The effectiveness of recommendation systems lies in their ability to leverage data intelligently. Through strategic analysis of customer preferences, historical data, and other relevant information, these systems create win-win situations. The customer receives tailored suggestions that align with their needs and preferences, leading to increased satisfaction. At the same time, sellers benefit from higher chances of successful conversion.?

A use case that perfectly illustrates this situation is a recommendation system designed to incorporate item profitability. Rather than basing recommendations solely on a customer's browsing history and past purchases, companies can implement strategies to control how profit-based recommendations deviate from traditional suggestions. This allows businesses to strike a balance that aligns with customer trust while maximising profitability.

Imagine you're a customer exploring an online fashion retailer, like "Zara," globally recognized for its trendy and curated clothing collections. As you navigate through the platform, the recommendation system goes beyond merely suggesting items based on style. In this scenario, let's focus on your interest in purchasing a winter coat.

For you, the customer, the recommendation system looks into your browsing history, past purchases, and style preferences to present a selection of winter coats perfectly aligned with your taste. This not only streamlines your decision-making but also enhances your overall shopping experience.

On the business side, for Zara, the integration of item profitability into the recommendation system is essential. By strategically analysing the profitability of individual winter coat options, the system ensures that the suggested items not only resonate with your preferences but also contribute to the retailer's financial objectives. For instance, the system may prioritise recommending coats with a higher margin or those that have proven to be popular among customers.

This integration of item profitability ensures a win-win situation. You, as the customer, receive tailored suggestions, while Zara maximises the likelihood of a successful sale and optimises profitability by promoting specific winter coats. The recommendation system, in this example, transforms the shopping journey into a mutually beneficial experience, combining customer satisfaction and business success.

Another facet of retail operations that stands to benefit significantly from effective data management is inventory control. By strategically utilising customer-related data, Zara can strike a balance between offering a diverse range of winter coats to customers and avoiding overstocking less profitable options.

Immediate Alerting Systems

Alerting systems, when integrated into intelligent automation frameworks, enhance the overall efficiency and effectiveness of automated processes.

By providing early detection and instant notifications, alerting systems become the trigger for automated processes to kick into action.

This early warning mechanism ensures that potential issues are promptly brought to the attention of the intelligent automation system. This urgency is especially critical in scenarios like fraud detection, manufacturing processes, and other industries where timely action can significantly mitigate risks.?

Intelligent automation, fueled by advanced algorithms and machine learning models, goes beyond the traditional rule-based approaches. When paired with alerting systems, it can dynamically respond to notifications by making informed decisions. For example, in fraud detection, an alerting system may flag a suspicious transaction, prompting the intelligent automation to autonomously initiate further investigation or preventive measures.

Let’s take the example of fraud Detection.?

In a time where businesses face a constant risk of financial fraud and cyber threats are evolving rapidly, manual detection methods are no longer relevant.?

Intelligent automation has the power to stop fraud before it even starts. How? By providing a systematic way of detecting suspect transactions and automating rule-based checks.?

Automated alerting systems are designed to trigger alerts in response to suspicious activities, providing not only real-time monitoring but also significantly reducing the time it takes to detect and respond to potential threats.?

Let’s get technical. Essentially, these alerting systems operate through the use of advanced algorithms and machine learning models to analyse large datasets. These systems have the ability to identify unusual patterns, detect anomalies and trigger alerts for additional investigation. The algorithms are continuously learning from new data to improve the overall accuracy of the models. This proactive approach reduces the likelihood of false positives and ensures that potential threats are detected effectively.?

Another interesting application of intelligent automation in manufacturing is mobile service alerting for maintenance.?

In manufacturing, situations like urgent maintenance requests, unexpected breakdowns or quality issues are common on a shop floor. Fast response becomes critical as equipment malfunctions or quality problems can bring operations to a standstill. Traditionally, when a machine breaks down, a maintenance engineer must be alerted either through a blinking red light on the machine or manually by a machine operator using a landline phone located somewhere on the shop floor.

In more smart and more digitised manufacturing, IoT technologies can detect the breakdown and indicate it on a computer screen. Control room staff then have to manually locate someone available to address the technical issue. However, this process is slow and demands valuable human resources.?

With mobile alerting, maintenance teams gain true mobility, transforming the response process into a more real-time experience. Machines and other manufacturing systems can directly and automatically send urgent maintenance or service requests, streamlining service dispatching processes.?

On the mobile application, technicians have a job queue and can take ownership of tickets, incident alerts, and service requests.

In real-time, operators can track who has responded and assumed responsibility for specific maintenance tasks. There is no need for additional communication to locate available team members or confirm job ownership. Subsequent shifts can easily review the status of tasks and identify completed jobs.

The mobile app enables swift job assignment, real-time tracking, fostering efficient collaboration among engineers. This not only accelerates incident resolution but also enhances operational transparency and accountability.?

For such smart factories, the result is a clear and substantial return on investment, marked by improved responsiveness, reduced downtime, and optimised resource utilisation.

Anomaly detection

Anomaly detection involves detecting unusual patterns or behaviours. Its applications span various domains, comprising? fraud detection, manufacturing, and smart buildings.

Smart Buildings: Monitoring and responding to unexpected changes in energy consumption.

Anomaly identification is an important component of intelligent infrastructure, enabling monitoring and response to unforeseen shifts in energy consumption.

The system discerns irregularities in energy use, simplifying the spotting of potential hitches or inefficiencies. Prompt responses to these irregularities empower smart infrastructure systems to fine-tune energy usage swiftly, promptly dealing with issues to ensure smooth operational functions.

Predictive Maintenance: Detecting anomalies in production processes to ensure product quality.

Anomaly detection, particularly in the context of predictive maintenance, is highlighted as a cost-efficient strategy. By foreseeing discrepancies in production processes, manufacturers can prevent defects and reduce waste.?

Rapid and accurate anomaly detection in the production line enables immediate corrective actions, preventing potential defects and maintaining desired quality benchmarks.?

Picture a scenario where a production system, equipped with anomaly detection capabilities, continuously monitors diverse production parameters like dimensions, material properties, or process speeds. If there is a noticeable shift from the expected values, the anomaly detection system triggers an alert. This alert acts as an early warning, prodding the production team to investigate and rectify the anomaly promptly.

The proactive aspect of anomaly detection not only prevents defects but also contributes in optimising the overall efficiency of the production process. By addressing anomalies in real-time, manufacturers adhere to rigorous quality standards, reduce waste, and guarantee that each product aligns with the prescribed production norms.?

This strategy not only enriches product quality but also streamlines the production sequence for heightened efficiency.

Maximise your intelligent automation with Digazu

The true power of Intelligent Automation lies in the quality and timeliness of processed data. Digazu ensures a continuous flow of relevant data, unlocking the full potential of automation investments, driving unparalleled efficiency and accuracy in operations.??

Digazu, a real-time, low-code streaming platform, simplifies the flow of real-time data for businesses. This empowers intelligent automation across various applications, including recommendations, alerting, anomaly detection, and more.

Digazu ensures seamless integration across various data sources, consolidating diverse datasets for efficient alerting and anomaly detection. With a low-code configuration approach, users can effortlessly create data pipelines either visually or through SQL in a matter of minutes, facilitating the enrichment of data streams. The platform further excels in real-time, high-volume execution, allowing users to execute and monitor data pipelines on any scale of data.?

This capability ensures the timely and efficient processing of data, enabling users to derive actionable insights in real-time.?

Transform your real-time data sourcing and processing with Digazu, and maximise the returns on your Intelligent Automation endeavours.