Redefine your Business Strategies with AI Workflow Automation

What is AI Workflow Automation?

By leveraging Artificial Intelligence, workflows are optimized to minimize task inefficiencies and errors. An AI workflow will effectively streamline the tasks by properly lining them up and only using limited resources.

Implementing an AI workflow allows businesses to negate limitations and improve the efficiency of these processes by freeing employees’ valuable time. This also allows them to focus on tasks that need their input. This finally increases productivity and efficiency of the overall performance. 

AI workflow automation is the process that uses AI to optimize all business processes. The most common repetitive and redundant tasks like data entry, data processing, and analysis are automated using workflow AI where computers and software take over such mundane tasks. The AI workflow solution also makes it possible for users to integrate external applications and tools.

An Overview of AI Workflow Automation

The automation strategy of the workflow is designed in such a way that it integrates different algorithms and machine learning into regular manual workflows. AI, with its learning abilities, can mimic any cognitive actions performed by humans, adapt to them, and eventually perform better. Hence, the workflows of the processes are working with intelligent automation and cognitive abilities. 

In comparison to this, the traditional automation system can easily perform predefined processes. This is where AI-based automation marks its difference. In an AI automation workflow, the software or the system has the potential to think, learn, and make necessary decisions autonomously for the process to move forward, done under the supervision of a human.

Traditional vs. AI Workflow Automation – Which one should you go for? 

Many technologies have influenced how workflows were automated a decade ago and today. With the advent of AI solutions, current workflow automation techniques transcend past capabilities and free human labor from unnecessary intervention, saving time and resources. Right now, from automated workflow generation to workflow management, business teams can instantly identify areas of improvement or detect any patterns of discrepancies. 

Let us look at a function-by-function comparison of traditional and AI-based workflow automation.

The Collaboration of BPM and AI Workflow Automation

Conventional BPM methods along with AI workflow automation make the best tool set for improving your business processes. BPM decides on the end-to-end process framework whereas, AI’s purpose is to automate certain tasks in those processes. 

This integration improves the tasks by enhancing the process flow and also improving its design, performance, and monitoring capacities. Additionally, these are accompanied by intelligent decision-making and workflow optimization.

Key Components of AI Workflows

Understanding what makes up an AI workflow is crucial for a successful implementation of one. The three important components of AI workflows are data input, processing algorithms, and output generation. When all these key elements are rightly orchestrated into the system, the business processes can be carried out efficiently. 

1. Data Input

Data input is the backbone of AI workflow automation. This component acts as the driving force for the automation. The quality of this force will determine the effect that it creates on the process. To understand this better, let us consider a situation where you have to work with two sets of data. 

One set of data is well-sorted and structured where the data is tabled which is relevant, accurate, and easy to deal with. The second set is an unorganized one with errors and irrelevant data. If you are asked which is easy to deal with, even without a second thought it can be said that the first set of data would offer a smooth ride. 

This is how automation works on processes. It transforms processes that deal with accurate and relevant data from multiple sources. Having an organized set of data helps the process finish smoothly. The AI workflow management system automates all repetitive manual tasks, making the time required for the process minimal and cost-effective. 

Data orchestration is an important factor that takes care of the procedures in the data warehouse. The data orchestration plays a key role in aligning every aspect of a workflow and ensuring harmony among different aspects. This involves workflow orchestration as well as dataflow automation. 

Why do data input and orchestration become crucial? It is crucial as the quality and accuracy of it determine the way a process finishes. The AI workflow automation results completely depend on the data. Incorrect data will lead to wrong decisions affecting the overall output of the process. Therefore, data input becomes an important aspect of AI workflow automation.

2. Processing Algorithms

Every process requires an element that becomes the core of decision-making. The decision maker navigates every stage in operations, processing data, and making decisions wherever required. The processing algorithms dictate how a process works and finishes. These algorithms can be rule-based where pre-defined rules are used to store, sort, and route processes accordingly. 

Eventually, using machine learning techniques these algorithms can be transformed to a more advanced version that can adapt and improve. Robotic process automation (RPA) tools are yet another solution that can accelerate the efficiency of the process. RPA can automate repetitive tasks with ease. Once the rules are set in the rules engine, the algorithms are set such that it does not require any manual assistance. Hence complex tasks like decision-making regarding processes are removed and it also saves time.

3. Output Generation

As the third important component, output generation is the final stage where the process is run automated using AI models and algorithms. This finally generates the contents like images, text, sounds, and other forms of data.

The output generation provides you with a lot of advantages like supporting workflows, minimizing the time required for processing, and boosting efficiency by eliminating manual work. Some of the essential outputs generated are automated reports and analytics, and recommendations regarding automated actions that enable the streamlining of tasks and enhance the overall proficiency of workflow performance.

Core Technologies in AI Workflow Automation 

The core technologies of AI workflow automation enable organizations to practice intelligent process management. These core technologies include machine learning, Natural Language Processing (NLP), and Robotic Process Automation (RPA). Let us take a close look at these solutions. 

Machine Learning

Machine learning has been significantly transforming data processing and management. Businesses that workflow automation, leverage machine learning algorithms to process huge amounts of data, identify patterns, work on changing conditions, etc. This AI-powered tool aids teams in making data-driven decisions, garnered from the system-processed data. Machine learning transformation workflow automation by making it optimized and streamlined. It elevates multiple tasks such as task management, resource delegation, and error detection. 

Optical Character Recognition (OCR)

OCR is one of the most popular ML-based technologies impacting businesses for over a decade. Evolving since then, OCR continues to influence businesses in extracting texts using advanced solutions like AI, automating document management with zero human intervention. With a simple scan that only takes a few seconds, texts are extracted from documents directly into the system and can be mapped accordingly. This one-time setup enables teams to autofill automated forms. 

Natural Language Processing (NLP)

NLP facilitates effective and seamless system-system and system-human communication. It is the system-based language that enables machines to understand, interpret, process, and generate human language. This solution drives collaboration and enables faster data processing. NLP is a core solution that takes care of tasks such as sentiment analysis of written text and analysis of chatbot interactions. 

Robotic Process Automation (RPA)

Robotic Process Automation is all about automating rule-based and repetitive tasks. Moreover, this automation capability can be extended to complex processes when integrated with AI, creating an intelligent solution for automation. Organizations integrate machine learning, Natural Language Processing, and RPA, and a wide spectrum of tasks can be automated, considerably reducing human intervention and increasing overall efficiency. The automation solution, powered by AI capabilities, offers a robust, adaptable, and efficient workflow automation solution. while the AI business plan generator aids in optimizing business strategies.

Trends to Look Out for in AI Workflow Automation in 2025

The Powerful Combination of AI and RPA

RPA and AI form the strongest solution that takes the business by storm. All types of tasks ranging from cognitive to repetitive to administrative tasks are automated and streamlined to bring out maximum efficiency of the business teams. 

Increased Transparency 

Decision-making with these technologies is much simpler and straightforward. Data and insights garnered from the process analytics, allow decision-makers to make data-driven decisions. Actions taken can be completely backed up by transparent AI algorithms, offering more clarity.

Advanced Conversational AI

With the recent advancements in the NLP, more advanced conversational AI and virtual assistants are expected to be adopted by businesses across industries. This is no longer just about automating workflows, it is now a strategic technique to acquire accurate process management. 

Cybersecurity Boost

The integration of AI and machine learning enables a stringent regulation of cybersecurity. Tasks such as threat detection and incident management are automated end-to-end, providing a centralized approach. The integration of intelligent cybersecurity with DevOps creates a more agile and secure AI-driven workflow automation. 

Why is AI Workflow Automation Important?

Ultimately, every business aims to achieve growth achieving productivity, profit, and sustainability. Therefore, automating processes becomes a necessary solution. Automation optimizes the tasks in a workflow that makes processes more profitable and successful. Even the slightest upgradation of tasks can bring exponential beneficial changes to the business. Let us look at some of the benefits garnered from AI workflow automation.

Integrating AI into Process Workflows

AI brings several capabilities to business processes. Although the idea of integrating AI into your daily workflows may seem challenging, the following discussion points ought to facilitate a positive transition to AI.

Chatbots

This AI powered tool can be used out of the box and assume manual duties for employees across business lines. Several companies integrate chatbots into their daily operations. Chatbots are extremely useful tools that can answer questions and deliver solutions quickly and accurately.

Intelligent data extraction

Chatbots can be used for performing several advanced functions by leveraging AI techniques like Machine learning and NLP. AI can process mass data from a wide range of structured and unstructured sources in different formats and languages. Intelligent, AI-enabled business processes improve service to customers, suppliers,partners, and employees, by moving away from rigidly defined workflows to highly intelligent, autonomous systems. Intelligent bots are often used to pull data from sources, such as, handwritten text, images, and PDF files. The extracted data is contextualized by AI to reduce the noise in the source material and also improve data accuracy.

Adaptive process automation (APA)

Adaptive process automation can automate digital processes by leveraging AI techniques like ML and digital process automation. APA bots are programmed with self-remediating and autonomous decision making capabilities that allow them to optimize processes. These systems are also capable of reasoning and retaining information, which allows them to gain deeper insights into data. NLP and ML techniques can also be used to improve interaction with humans. APA systems are capable of highly advanced functions that make them accountable and auditable. 

Benefits of Workflow Automation with AI

Improved Efficiency and Productivity

Automating is the best solution when it comes to improving the efficiency and productivity of your business. Automating processes is much easier and resource-efficient than manually trying to reduce limitations. For example, suppose a business is automating its customer service workflow using an AI workflow builder. In that case, it will be able to respond and address queries much faster and get high levels of customer satisfaction.

Better Data Analysis

Traditionally, businesses were driven by experience and knowledge about the processes. However, today they are driven by data. This leads to a piling up of data to deal with. Dealing with data is a tedious task and that is why automation is important. AI automation workflow tools have the potential to deal with heavy data and analyze it better and faster than humans. Moreover, these tools can also give feedback for better outcomes next time.

Cost Savings

AI workflow automation platforms cost comparatively less than the team manually managing all the tasks. The left-out cost can be invested in a more valuable process like hiring new employees. Additionally, an AI workflow will minimize the errors, saving more budget.

Faster Time-to-market

Faster time-to-market can bring more revenue to your business. It also gives a strong market share and escalates your business agility. Being more agile means your business will be able to adapt to changes quickly. This is best suited for businesses that handle a large amount of manual work and can witness visible changes in the output.

Reduces Human Error

Human errors are inevitable in a manual setup. Manually performing business processes can be monotonous and it can get the best out of the workforce. It is a fact that automation is more reliable than humans. No wastage of budget or resources occurs making the process affordable and an errorless process can be obtained.

It Scales Teams of all Sizes

AI workflow automation is the best solution for businesses with numerous complex processes and large workforce. It can be an effective tool for managing the business and administrative processes together.

Cross-functional Coordination 

Collaboration is a significant factor that is nurtured with AI workflow automation. This is crucial when multiple departments work on complex tasks and have to collaborate for a smooth flow of data and resources. It eliminates process silos and aligns the teams with the set overall goals and objectives. This facilitates accurate decision-making and a faster resolution of conflicts. 

Customization and Flexibility

AI workflow automation is powered by intelligent solutions that make it more adaptable to changing business needs and requirements. These AI workflows are highly customizable, curating them according to the needs of every team and allowing them to make the right decisions. 

Comprehensive Automation

AI-based workflow automation is far beyond simple automation of routine tasks. It is a comprehensive approach that handles every task, from data entry to decision-making to strategizing. Business teams not only remove drawbacks but improve the overall efficiency and productivity of the team. 

Unified Data Flow

AI-based automation software stands as a centralized platform where data is processed, stored, and managed for the entire organization. Data can be unified and seamlessly accessed to integrate with any workflow.

Enhanced Strategic IT Planning

Decision-making is significantly improved with AI tools that facilitate strategic IT planning. IT initiatives can now be well-aligned with the overall goals of the business, where decisions are completely made based on the analytics generated by the tool that studies processes as well as customer behavior. 

Better IT Governance 

Compliance is now made easy to achieve with simplified yet efficient AI workflow automation platforms. Based on the conditions that are set or preset, the system continually looks for any non-compliance with internal policies and legal regulations. This way, all the processes continue to run compliant and secure.

Resource Allocation

There is better resource allocation and significantly reduces any wastage. Decision-makers can make better judgments on the requirement of resources and monitor requirement changes in real-time. This allows the teams to forecast needs and dynamically adapt to change. 

Technology Innovation

Businesses can freely innovate and invest in higher-end projects and initiatives with the technical expertise of AI workflows and manage them effectively. Businesses can focus on scaling instead of being tied with routine works like incident or inventory management. 

Citizen Development Oversight

A business’s top management can have clear insights into the development arena where even citizen developers can be encouraged to innovate using no-code platforms. Governance rules can be set according to which development can be widened in scope. 

Steps in Implementing AI Workflow Automation

1. Assess your Current Workflows

Research and analysis of the existing setup is the first step that a business must take to implement AI in workflow automation. With such an analysis, you will be able to identify the areas of improvement. The current processes have to be scanned in depth to understand where they have to be enhanced and to determine the processes or tasks within a process that has to be automated.

2. Map out the Process

Once you identify the processes that have to be automated, you will be able to identify the workflows that have to be automated. In this stage, you will have to check the tasks’ efficiency by measuring the results obtained with the expected results.

3. Choose the Right AI Automation Tool

When all the workflows are identified, your next step is to determine the right tool for your workflow automation. Choosing the right tool is highly important for acquiring the right results. It should also be noted that it also helps you meet your organizational goals. Additionally, the tool must have the features that you desire and require. Extra features may lead to extra payment. Cflow is an ideal AI workflow automation tool that businesses can invest in completely.

4. Automate the Process

This is the stage where the inefficient processes are automated. All the complex processes that fail to give the right outcome will be transformed into efficient ones. Here, the automation steps taken will be completely based on the analysis done while mapping. Therefore, only a defined number of employees and resources will be required.

5. Test and Refine

Once the rule-based automation algorithms have been set into the workflow, it is now time to test run the AI workflow and generate results. These have to be tested for different error cases to ensure that it does not take an unexpected turn.

6. Monitor and Optimize

Once the test run has been done, the necessary changes have to be made to the processes. It is also ideal to collect process feedback to negate any possible drawbacks. Once the implementation is completely done, the automated processes have to be monitored continuously to detect any flaws. To monitor them, certain key performance indicators (KPIs) can be used. Some of these parameters can be as follows- 

• Customer satisfaction
• Cost savings
• Time savings
• Process efficiency

Use Cases of AI Workflow Automation

We have seen sales and marketing use cases of AI workflow automation in detail. There are other use cases where AI workflow automation can make a difference. The insurance industry for example, uses AI to reduce friction and costs in the insurance claims processing. 

1. Insurance Industry

AI workflow automation can be used to automate the claims processing by creating a claims submission interface for uploading customer-filled PDF claim forms. This interface automatically verifies claim data and configures data within a fraction of the time taken to carry out the task manually. The staff at Insurance companies can now focus on important tasks, instead of on rote tasks like sorting through claims documentation. 

2. Legal Industry

Legal research is a data- and labor-intensive task that lawyers have to carry out on a regular basis. Automating legal research using AI accelerates research and improves the accuracy and relevance of the research. Moreover, the privacy of legal data is maintained by AI workflows. 

3. Healthcare Industry

AI-based workflow automation has emerged as a transformative force in the healthcare industry. From streamlining administrative processes to enhancing diagnostic capabilities to automating appointment scheduling – AI workflows take care of everything. The administrative burden on healthcare staff is greatly reduced and quality of healthcare is improved by automation 

4. Finance Industry

Handling vast amounts of financial documents and data manually can be problematic for finance professionals. AI algorithms are capable of analyzing transaction patterns and identifying anomalies in real-time, thereby, providing a proactive approach to data security.

5. Manufacturing Industry

Manufacturing is all about efficiency and accurate processing that will help in the delivery of the right outcomes. AI-powered automated workflows revolutionize how manufacturing processes are carried out, starting from conception, production, waste reduction, etc. AI systems are built to control and monitor manufacturing machinery and alter it based on the change in requirements. This will eliminate any downtime as well as improve machines’ lifespan. A centralized inventory management system enables the company to manage and sort requirements on time. 

6. Retail Industry

The success of retail businesses lies in service and customer satisfaction. This is achieved with a seamless process flow. Intelligent inventory management ensures that every purchase process is standardized and streamlined with real-time data and statistics. These also have features that enable retail teams to render personalized services and run automated marketing campaigns. Additionally, it takes care of the supply chain, ensuring smooth forecasting and supply. 

7. Banking Industry

To improve operational efficiency and customer service, AI-run workflows have taken the banking sector by storm. Automated workflows that are structured on AI solutions, help banks and financial institutions detect potential threats and fraud. This significantly reduces risks with transaction monitoring in real-time. Documents are verified and approved in an instant with automatic routing. This way customers are onboarded faster, compliance is achieved seamlessly, and service offered is top-notch. 

8. Oil and Gas Industry

The oil and gas industry has some complex core processes that need to be optimized to deliver profitable outcomes. These processes are carried out using critical equipment that requires consistent maintenance to prevent any form of work downtime or accident. This can only be achieved with the real-time monitoring of these core processes. AI workflow systems improve this scope by offering real-time monitoring and analytics. Additionally, routine works like data entry and approvals can be automated end-to-end. Compliance can be achieved with automated verification, documentation, and reporting. 

9. Sales and Marketing

In sales, starting with lead generation, qualification, and to the final onboarding, AI workflow automation can save the sales and marketing teams in any business. AI-assisted tools can instantly identify leads and qualify them for faster customer onboarding. Marketing automation allows the teams to target the right audience based on the behavior and demographics generated by leveraging AI-based analytics tools. Additionally, personalized and customized campaigns can be formulated using AI tools for better reach and leads.

Tasks-wise Automation with AI

Here are different types of tasks no matter the industry that users work in, that can be transformed using AI workflow automation for enhanced performance. 

• Filling out forms and emails transformed as service requests.
• Distribution of workload based on criteria like load, time, resources required, etc. 
• Creation and sending of invites for calendar events
• Email notifications and alerts are sent in case of any status change in a process
• Assignment and routing of tasks to the right team member
• Setting alerts in case of approaching or overdue deadline
• Generation of contracts and delivery of signatures
• Review and approval notification when required
• Data synchronization from an email or form
• Automatic generation reports and dashboards using workflow data

Types of AI Workflow Automation

1. Predictive Analytics Automation

If you are looking forward to improving and boosting profitability, improving operations, predicting sales forecasts, and also widening your customer base, predictive analytics automation would be the best choice of workflow automation method. 

Predictive Analytics Today (PAT) research reveals that 52% of businesses use predictive analytics automation for the above-mentioned achievements. Predictive analytics works by combining artificial intelligence (AI) as well as machine learning (ML).

2. Cognitive Automation

With the combination of artificial intelligence and process automation, cognitive automation helps businesses to boost desired outcomes. The method of cognitive automation involves different approaches like capturing data, automated decision-making, etc. Unlike so many other AI solutions, cognitive automation tools have the potential to imitate the way humans think.

3. Rules-based Automation

A rules-based automation model works on rules set by humans. These rules are used to store, sort, and manipulate data. This way, it can mimic human intelligence. All sorts of repetitive tasks can be automated using rules-based automation offering new levels of efficiency in labor.

Steps in Choosing the Right AI Workflow Tool

1. Determine your needs with AI workflow
2. Check all the essential features and their compatibility with your business
3. Look for integrating properties with external applications
4. Check if the platform has easy navigation
5. Check if it fits your budget

Challenges with AI Workflow Automation

Isolately investing in solutions like RPA, AI, etc, still fails to offer complete end-to-end process automation. Due to this, the efficiency pathway is left halfway. Therefore, there is a necessity to have a broader spectrum of tools all in one place instead of disconnected ones. Having to deal with multiple tools is difficult. Some of the challenges include – 

• Implementation Costs – AI workflow automation requests quite a heavy investment. This arises from factors such as trainer personnel, the setup infrastructure, software, and training requirements. 
• Exception Management – Although AI runs on pre-defined conditions and rules, it can lead to exceptional cases, which require trained personnel to handle the situation, without letting it affect the existing functions. 
• Need for Skilled Labor – The previous point brings us to the need for trained labor who knows how to work with upgraded technologies and deliver the maximum output. 
• Security and Privacy Concerns – Handling sensitive information better is critical when it comes to functioning with advanced technology. Some data must not be shared with AI-based tools. Special security measures and steps have to be taken before any data is processed using an AI automation solution. 
• Ethical Issues and Bias – AI can learn and adapt to the requirements of the users. This can offer space for bias, affecting multiple decisions taken for hiring, workflow management, and customer service. Hence, regulating the functions and what you are asking the AI tool to perform is crucial. 

On the whole, all these challenges lead to cost-inefficiency that completely overshadows the purpose of implementing automation in the first place. Hence, to overcome these challenges, it is necessary to find the right tool. 

Best Practices for AI Workflow Automation

Implementing AI workflow automation solutions to the existing system of processes can interfere with the current synergy of functionality. However, this is one of the most essential solutions required for companies to sustain themselves in the ever-changing space of business. Here are some best practices to achieve  this seamlessly – 

• Understand the current state and efficiency of the workflows. This will give an unfiltered understanding of its performance.
• Always integrate reliable data with the workflow database. This will ensure a smooth and seamless process flow, integrated with efficient data processing. 
• Choose the right automation tool for AI-powering the workflows. Multiple factors have to be considered that will help orchestrate processes efficiently and quickly. 
• Think beyond the workflow setup, and widen the scope of automation to other sections of business too. 
• Keep your partners, customers, and contractors informed and in the loop with the advancements made in the system. 
• Go step-by-step to avoid changing the whole system in one go. Change has to be implemented partially for the team to adapt. 
• Always think about security and compliance. Ensure that every task and initiative is secure and compliant. 
• Invest in training and change management for an effective utility of the new solutions. 

Cflow’s Powerful AI Workflow Automation

As we have seen the benefits that AI workflow automation tools offer, it is essential to choose the right tool. Cflow offers a perfect customizable suite for beginning your automation journey. The platform is no-code workflow automation software, where processes can be automated with simple steps. 

• Cflow offers flowchart-based workflows where the users can just drag and drop icons to assemble the stage. 
• Cflow offers pre-designed and customizable templates for any business processes the users want. 
• Cflow’s rules engine is where the users can embed the rules that help the processes navigate by making certain decisions.
• Cflow allows easy assigning and routing of tasks to multiple users. Customized reminder notifications can be sent to users.
• Cflow enables integration with several other SMB applications like Slack and Quickbooks.
• Cflow provides its users with customized graphical reports and analytics that help in assessing the processes’ performance.

Top 5 AI-Based Workflow Automation Tools

1. Cflow

An AI-powered workflow automation that addresses the requirements of businesses across industries. You can automate workflows 10 times faster without having to write even a single line of code. The insane levels of customer support provided guide users through all stages of setting up automated workflows and using these workflows to streamline their processes. You can create custom workflows with the visual drag-and-drop forms designer.

Cflow is the best kept secret on efficient workflow automation tools, specializing in planning and navigating digital transformation for small, medium, and enterprise-level businesses. 

2. Bardeen.ai

This is a generative AI tool that can be used to automate various tasks performed by business apps like Google sheets, Notion, Hubspot, and other integrations. Bardeen uses modern AI technology like large language models (LLMs) and generative AI for making workflows more efficient. This tool uses a smart automation generator that can be used for workflow automation as per business requirements. 

3. GPT 4

This is an AI language model developed by OpenAI that can generate human-like text. GPT-4 is effective in generating product descriptions, chatbot responses, or even writing blogs that support product development tasks. Its ability to generate high quality content within minimal human intervention makes ChatGPT the ideal tool for automating various tasks and maximizing productivity. ChatGPT was built on top of GPT-3, and has set the record for the fastest growing user base in history. 

4. UiPath

This is a robotic process automation (RPA) platform that allows businesses to automate repetitive tasks like data entry, file transfers, and report generation. UiPath incorporates AI technology for discovering automation opportunities in task mining and process mining, as well as in computer vision, document understanding, and communications mining. The Business Automation Platform from UiPath intends to support generative AI experiences that are stable, manageable, and resilient, scaling up to enterprise level. 

5. IFTTT

Stands for “If this, then that”. This is a popular AI tool that uses generative AI to automate tasks based on triggers and events. This tool is useful in tasks like  saving email attachments to cloud storage, sending notifications, and updating social media profiles. IFTTT is also available in a paid plan for implementing AI-generated social media posts, blogs, and summaries as automated workflows.

Conclusion

Soon the world of business is going to be where every organization, regardless of the industry, is efficient by leveraging AI solutions. Currently, efficiency is redefined in terms of the degree to which you implement these new technologies. 

AI workflow automation is one such transformative solution that will elevate your business to greater heights. If you are looking forward to getting hold of the best solution from the market, Cflow is the best decision you can make. 

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FAQs

1. What type of tasks can be automated using AI workflows?

Any business process that involves rote tasks requiring low intelligence inputs are right for automation. Finance, healthcare, legal, and insurance industries employ several tasks of this nature that are apt for automation. 

2. How to choose the right type of AI automation?

The decision on the AI workflow to be implemented must be taken based on the business requirements and process goals. 

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