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Explore how AI automations and AI agents work and how implementing them in your business gives you a competitive edge.
In today's data-driven world, businesses are constantly seeking ways to streamline processes, boost productivity, and gain a competitive edge.
This is where AI automation comes in — creating a new level of intelligent workflows that transform how your business operates.
In this article:
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Automation’s significance in today's fast-paced world lies in its ability to transform complex challenges into manageable solutions — improving business processes by delegating repetitive tasks to machines.
Automation tools streamline processes by linking data across various tools, and once established, they need minimal ongoing manual intervention.
Before we discuss exactly how automation helps with business efficiency, let’s define a few different types of automation.
Traditional automation is designed to execute repetitive tasks based on explicit, predefined rules determined by humans and does not learn or evolve.
AI automation uses artificial intelligence capabilities like machine learning and natural language processing (NLP) to enable machines to learn from data and experiences, recognize patterns, and make human-like decisions.
AI automation tools do adapt and evolve over time.
Similar to AI automation, AI agents are designed to make human-like decisions. However, unlike AI automation tools, AI agents take autonomous actions (i.e., without needing any human input).
The key differentiator of traditional automation, AI automation, and AI agents lies in their independence and cognitive capabilities.
| Type of Automation | How It Works | Level of Human Involvement | Tasks |
|---|---|---|---|
| Traditional Automation | Predetermined rules | High — need explicit instructions | Menial, repetitive tasks |
| AI Automation | Learns from data to make human-like decisions |
Medium — moderate amount of setup | Data analysis & decision making |
| AI Agents | Make decisions autonomously | Low — need only an end goal | Complex problem-solving & interactions |
By embracing automation — specifically AI automation and AI agents — you can streamline your operations, improve decision-making, and unlock the full potential of your workforce.
Automation boosts:
Ultimately, automation tools improve efficiency and accuracy, significantly reducing operational costs — while freeing up capacity for higher innovation, enabling greater opportunity for growth.
Businesses across various industries leverage automation in many ways, including:
| Task or Industry | How Automation Is Utilized |
|---|---|
| Document Handling | Extracting & processing data |
| Project Management | Planning projects & allocating resources |
| IT | Deploying & maintaining systems |
| Hiring & Onboarding | Streamlining recruitment, tracking, & onboarding processes |
| Customer Support | Offering 24/7, personalized assistance & resolving queries swiftly |
| Marketing | Synthesizing data across channels to optimize digital campaigns & tailoring campaigns to individual preferences to increase engagement & conversion rates |
| Supply Chain Management | Optimizing inventory & delivery, anticipating needs, & refining logistics |
| Manufacturing | Automating quality control processes, predicting equipment failure, & optimizing production lines |
| Retail | Personalizing customer recommendations, automating inventory management, & optimizing pricing strategies |
| Finance | Processing loans, detecting fraudulent transactions, & personalizing recommendations |
| Healthcare | Analyzing medical images for early disease detection, automating administrative tasks, & personalizing patient care plans |
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To understand how automation functions, it's essential to know six key concepts.
| Concept | Description |
|---|---|
| Workflow | A sequence of steps to complete a task |
| Triggers | Events that initiate the workflow |
| Inputs | The data required for the automation to work |
| Logic | The rules that determine what happens within a workflow |
| Action | The steps taken by the automation |
| Output | The ultimate result of an automation |
An automation is essentially a workflow (i.e., a sequence of steps to complete a task) that will happen automatically once triggered.
Triggers are events that initiate the workflow. They can be a wide variety of events, such as:
Once you start leveraging tools within automation, you’ll notice that different tools offer various — and sometimes distinct — triggers for initiating workflows.
Inputs are the data required for the automation to work. Inputs can be text, images, sensor data, or many other types of relevant information.
For example, inputs of an email trigger may be the email body, subject line, sender's email, sent date, tags added, etc.
While inputs typically come from the initial trigger, additional inputs can be incorporated as the automation progresses through various actions.
This dynamic nature of inputs allows for flexibility and adaptability within the automated workflow, enabling systems to respond to changing conditions or requirements as they execute tasks.
In regards to automation, logic encompasses the rules that determine what happens within a workflow (e.g., processing inputs and determining the appropriate action).
Logic can be broken down into:
Logic is created by establishing "if/then" statements to enhance the intelligence and adaptability of automation processes — enabling them to handle complex tasks precisely and reliably.
"If/Then" Statements
“If/then” statements specify that if a certain condition (i.e., the "if" part) is met, then a particular action or set of actions should be executed (i.e., the "then" part).
For example, if a customer places an order exceeding a certain, amount, then offer them a discount.
“If/then” statements may involve filters or constraints.
Filters sort, categorize, or exclude data based on specific criteria to determine which subset meets certain conditions and should or should not be processed further.
For example, if an email is determined to be spam (based on a filter of content or sender information) then it does not get sent to the user’s inbox.
Constraints set limitations or boundaries on which actions can occur — ensuring that actions taken align with predefined rules and objectives.
For example, if a marketing campaign hits a certain dollar amount (i.e., the constraint) then no more money will be spent on that campaign.
Actions are the steps taken by the automation once the trigger has been activated.
A wide variety of actions are possible, with some being specific to the tool you’re using. Examples of some possible actions include sending an email or updating a record.
An output is the ultimate result of an automation (e.g., a generated report, completed task, or the decision that’s made).
Outputs are generally created at the end of the automation... although not always.
For example, in iterative or continuous automation processes, outputs may be generated at various stages throughout the workflow rather than solely at the end.
An Example of The 6 Key Concepts In Action
Let's consider the real-life example of Alex, a businessman who owns a medium-sized e-commerce store specializing in outdoor gear.
Alex wants to improve customer engagement and sales through personalized marketing but struggles to manage this manually due to the growing customer base and the vast amount of data involved.
This is where AI automation comes into play, leveraging the six key concepts outlined above.
Workflows
Alex sets up an automated marketing workflow using a comprehensive marketing automation platform that integrates AI capabilities and offers a wide range of features, including customer relationship management (CRM), email marketing, social media marketing, and analytics.
The automation tool Alex chooses needs to be integrated with his e-commerce platform to allow for the seamless flow of data between his e-commerce site and the marketing automation tool. Depending on Alex’s e-commerce platform, he may choose a tool like HubSpot or Salesforce Marketing Cloud.
Triggers
The trigger for Alex’s workflow is a customer's interaction with his website, such as:
Inputs
Inputs for the workflow include:
Logic
The AI-powered marketing automation tool uses logic to segment customers based on their behavior, predict customer preferences, and suggest products they are likely to buy.
For example, if a customer frequently views camping equipment but has yet to make a purchase, the logic dictates that this customer should receive targeted emails about camping products.
Actions
Based on the logic, the action taken might be sending a personalized email with a special offer on camping equipment to the customer.
This email could include product recommendations tailored to the customer's interests — leveraging AI's ability to analyze past interactions and predict preferences.
Output
The output of this automation could be an increase in customer engagement (evidenced by higher email open rates) or more website visits — and, ultimately, increased sales of targeted products like camping gear.
The Result
In this scenario, AI automation allows Alex to create a dynamic, personalized marketing strategy that adapts to each customer's behavior and preferences — not only enhancing the customer experience by making marketing communications more relevant and timely but also driving sales by promoting products that customers are genuinely interested in.
AI automation, in this case, transforms a complex, data-intensive task into a streamlined, efficient process — enabling Alex to focus on other strategic areas of the business.
APIs & API wrappers are the tools used to accomplish automation.
Application programming interfaces (APIs) play a crucial role in AI automation by acting as the connective tissue between different software — and AI automation tools are essentially API wrappers... Don't worry, we'll explain.
Application programming interfaces (APIs) are tools that allow programs and software (e.g., customer databases, CRM platforms, and social media analytics tools) to communicate and share information.
APIs facilitate the real-time exchange of data between different software within an automation workflow.
Put simply, APIs:
For example, an automation workflow that monitors inventory levels (i.e., inputs) in real-time can use an API to trigger a procurement process, or series of steps to acquire goods (i.e., action), when stock falls below a certain threshold — ensuring seamless and timely replenishment.
While automation tools can streamline and enhance the integration process, they are not a mandatory requirement for implementing APIs.
You have multiple options for using APIs, including:
| Build & Implement Your Own APIs (Without Using an Automation Tool) |
Implementing your own APIs without automation tools involves understanding the API documentation, making API requests, handling responses, and integrating the API functionalities into the business processes or applications. It’s a complicated process that may be daunting for those with little experience. |
| Leverage Pre-Built APIs (With or Without Using an Automation Tool) |
A more efficient and cost-effective solution compared to building your own APIs from scratch is leveraging pre-built AI APIs to integrate intelligent functionalities into your existing applications and workflows. |
| Use Automation Tools to Integrate APIs | Automation tools provide a user-friendly interface to the API (aka an “API wrapper”) so that you can easily connect different software programs together to automate processes and utilize AI functionalities in your workflows. |
The term "API wrapper" refers to software that provides a more user-friendly way to work with an API by removing the complexity of directly interacting with the API.
You can think of an API wrapper as a translator that enables you to use APIs without getting lost in the technical details or as a middleman that takes care of the complex interactions needed to use APIs.
Almost every automation tool on the market is essentially just a wrapper for APIs.
The beauty of using automation tools is that you don't need to be a coding expert to make them work.
A few added benefits of API wrappers include:
By eliminating the complexity of directly interacting with APIs, API wrappers make AI technologies more accessible to a broader range of users — offering a simplified way for businesses to leverage AI automation in their operations.
We are at an early stage in AI agent development, but progress has been rapid — and they are set to revolutionize how we work.
The primary distinction between AI agents and non-agent automation tools lies in agents’ capacity to learn, adapt, and autonomously make intricate decisions — setting them apart from non-agent automation tools, which, though reliable for routine tasks, necessitate explicit instructions for each scenario.
By surpassing the capabilities of non-agent AI automation tools, agents offer a more dynamic and optimized workflow approach. You only need to specify the desired outcome, and the agent will execute the tasks on your behalf.
Because they provide sophisticated solutions in dynamic and complex scenarios, AI agents prove particularly valuable in environments where:
Supply Chain Management Example
In supply chain management, a non-agent automation tool typically functions based on predefined rules and workflows (e.g., reordering stock when inventory levels reach a set threshold) but lacks the ability to comprehend or adjust to complex, unforeseen changes in demand patterns or supply chain disruptions.
AI agents, on the other hand, can:
The types of automation tools available range from user-friendly low-code/no-code platforms (meaning that they require zero, or very little, traditional coding knowledge) to more sophisticated systems that offer extensive customization for experienced developers.
For automation beginners, it’s important to choose ones that:
It’s also beneficial to know that anything you’re doing within these automation tools can easily be pulled out and implemented in your own product or process as well — meaning you’re not permanently locked into specific AI tools.
With automation tools becoming increasingly important in the modern workplace, there are a plethora of automation tools available for you to use… and this list will only continue to grow.
While certainly not the only options out there, two prominent automation tools are Zapier and Make.
Both offer AI-powered features as well as integrate with a wide range of software and apps — with Make offering 1,200 integrations and Zapier offering 6,000+ as of March 2024.
And while they both perform the same basic function, there are key differences between the two.
| Tool | Zapier | Make |
| Ideal Users | Beginners/non-coders | Those with some programming knowledge |
| Key Differentiators | Easier; Large user community | More customization; Advanced features |
| Unique Benefits | User-friendly for simple automation needs | Historical data; Robust error handling; Custom integrations |
| Pricing (as of Apr 2024) | Limited free plan; Pricing based on tasks performed | Limited free plan; Pricing based on features |
The best choice for you mainly depends on your specific automation needs and their complexity. You may want to choose…
TIPS
Need help setting up automations with Zapier? Use the Automation Consultant by Zapier GPT, which will help you discover opportunities for streamlining your workflows across various apps — and guide you through setup.
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At Futurepedia, we believe that automation is not merely a trend but a transformative shift… and quite likely the next wave of AI.
That’s why we created two directories to help you find the right tools for you:
| AI Workflow Automation Tools | Explore 80+ AI automation tools |
| AI Agent-Based Tools | Discover 25+ AI agents |
Also, feel free to check out these other resources:
| AI Glossary | Learn 50+ Key Terms to Master AI Jargon |
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