Intelligent Automation (IA): A Competitive and Strategic Advantage

A study by Slack and Qualtrics found that 65% of the most productive employees are intelligently automating their workflows and saving an average of 3.5 hours per week — and that’s just for individuals.

Automation eliminates the tedious aspects of everyday work, from automated systems that update sales pipeline data to auto-generated meeting summaries that managers can review on their own time. When businesses use automated processes across their operations, they can achieve greater efficiency with less effort.

Read on to learn about the technologies behind intelligent automation, how it supports businesses, and how to implement it yourself.

What is intelligent automation?

Intelligent automation combines technologies like artificial intelligence, robotic process automation, and natural language processing to automate routine tasks and help humans make decisions. It helps improve business processes to free up employee time, reduce human error, speed up work, and save money.

Unlike older forms of automation, which require human scripting for each process, intelligent automation enables systems to learn from past data, identify new areas for automation, and put them into practice with minimal human involvement.

For example, intelligent enterprise automation can power everything from 24/7 global customer support to fully automated manufacturing quality assurance.

How does intelligent automation work?

Intelligent automation combines software technologies to help teams achieve greater efficiency and productivity. Some of the most prominent technologies include:

Robotic process automation (RPA)

RPA is the foundation of traditional automation. It helps machines mimic human activity, which is great for scaling processes that function the same way every time. Think of an assembly line, where a conveyor belt moves identical parts to each machine to screw bolts into it before it moves on. A formula embedded in a spreadsheet is another example: You go through the steps of manipulating certain data once, then you devise a formula that applies the same steps to new data as instructed, saving time.

With proper calibration from the start, RPA never requires additional human effort. Think of forms that autofill on a website or tabs that sort invoices by paid status and value in a software program.

Artificial intelligence (AI)

Modern AI can learn from user and data interactions to discover patterns and solve new problems. For example, Slack AI tools can automatically create a transcription from a recorded meeting between two co-workers. Then, it can create a short, detailed summary of that transcription and a list of action items for each attendee to complete.

Voice recognition technology hears and identifies each person’s voice and separates their dialogue. Then large language models (LLMs) quickly create a comprehensible summary. Additional RPA can use that summary to create and assign tasks for each person.

Machine learning (ML)

ML uses statistical models and algorithms to manage tasks without receiving instructions from a person. It collects large quantities of data to train its algorithms, dictate output, and even analyze unstructured data like emails, company documents, or social media posts. It makes predictions based on patterns found in the data and its ability to infer meaning.

For example, a company may require facial recognition technology for authentication and sign-in for employees on their phones or laptops. This tech is powered by ML. It recognizes the contours and features of a unique individual’s face, not just a photo of a similar likeness. This saves time when logging in and helps companies increase security — because someone can’t log on if they’re not a recognized employee.

Natural language processing (NLP)

NLP helps computers understand human language, fed from any text source. It uses this understanding to process vast amounts of text data, analyze sources, and find trends.

For example, NLP powers large search engines. When you search for something online, the search engine doesn’t just show you results where your search phrase appears on every existing website. It ranks them based on what it believes your intent is with that keyword.

For example, someone searching “process documentation” may seek a definition, an example of it, a guide on how to do it properly, or a tool that handles it automatically. NLP considers a keyword, phrasing, and other context a user provides in their search query. Based on that and complex algorithms, a search engine will return results that it determines are most relevant.

NLP also powers common tools like predictive text, translation, voice-based smart assistants, and sentiment analysis.

How intelligent automation improves business efficiency

Intelligent automation can make a variety of business processes far more efficient. The more repetitive tasks you can offload to automation, the greater your potential returns on investment (ROI). Here are some of the ways it pays off:

• Increased productivity: The technology, systems, subscriptions, and skilled expertise required to set up an automation foundation may cost you up front. But they can quickly pay for themselves as you scale the tasks they handle and allow your team to focus on more complex tasks.
• Greater accuracy: Automated processes are quicker and more consistent, greatly decreasing the chance of human error. This can translate to less need for thorough quality assurance, fewer defects, and reduced recalls.
• Smoother customer experience: Intelligent automation allows for faster and more personalized 24/7 service experiences. And when a skilled human rep needs to take over, they’re given the customer history and case information they need to continue to provide a great experience without putting the customer on hold.
• More compliance: Many non-compliant behaviors come from human error or oversight. Someone may accidentally skip an important process step, forget to log a defect after a call or enter incorrect information when writing an incident report. Intelligent automation helps correct mistakes and avoid errors by handling things in the background and making it so steps can’t be skipped, leading to better compliance with regulations.

Real-world intelligent automation success stories

Here are a few examples of how companies in different industries are using intelligent automation to achieve success.

Creating personalized solutions for greater efficiency

Verizon scaled automation in its various departments using Slack’s no-code Workflow Builder tool. Employees were most familiar with their own problems, so rather than relying on IT, they used natural language prompts to build workflows. They were able to handle things like coordinating installation services, assigning field technicians, and providing more accurate appointment times to customers.

Streamlining internal workflows for smoother operations

Capital One built a Slack bot workforce to support its human office workers in the communications platforms that 50,000 of them used daily. This lets them automate processes like responding to FAQs and ensuring financial communications compliance.

Capturing deal insights to boost win rates

Salesforce enhanced its competitive intelligence operations by removing bottlenecks in its prospecting and collaboration process. Whenever an opportunity closed, a competitor survey was sent to the account executive in Slack. The completed survey form was then generated and sent to the company’s competitive intelligence leaders, allowing them to review more data faster and fix issues identified in their sales pitch.

Key features of intelligent automation tools

Intelligent automation has many benefits, from helping solve problems to increasing efficiency. When choosing automation software for your business, consider these key features:

• Low- or no-code workflow builder: Business needs can often change rapidly and your operations should be able to keep up. Consider a low- or no-code workflow automation tool, like Slack’s Workflow Builder, where users can use drag-and-drop interfaces or even natural language prompts to automate any new process your business might need.
• AI and integration: Look for an AI-powered tool that connects with the other tools you use daily. For example, Slack AI can integrate with thousands of third-party apps, giving your teams a way to both retrieve and generate data where they’re already spending their time.
• AI agents and bots: AI agents are essentially bots that your teams can interact with through natural language prompts. They can be specialized for different roles, like service, sales, and HR. A tool like Agentforce for example, lets users build AI agents to perform tasks, such as providing onboarding documentation, drafting a pitch deck, ordering a replacement work device, and more.

 

Implement intelligent automation in your organization

Considering what intelligent automation can do for businesses — from time and money savings to less stress while expanding operations — you may be excited to get started. But any major changes to your processes will require training and guidance to ensure a smooth transition.

A 4-step guide to implementation

Here are the basic considerations for implementing intelligent automation effectively across your organization:

1. Identify and document processes for automation: Leaders in each department should solicit feedback from their teams about the repetitive tasks that take up their time. Ensure these processes are documented clearly, and submit them as candidates for automation.
2. Provide training: For teams to fully adopt new tools like intelligent automation, they should understand their benefits and how to start using them. Make sure the tools you choose are user-friendly and offer training opportunities where possible to build trust and confidence.
3. Automate simple tasks first: You can begin with RPA for simple tasks that never need to change, like document scanning or invoice processing. Assess how they’re going before diving into deeper challenges, such as pulling together all data and resources for creating an SOW.
4. Track performance and collect feedback: Be sure to set key performance indicators (KPIs) to measure success and make adjustments. Learn from your team about what’s working and empower them to propose more automations or adjust existing ones.

Common challenges and how to overcome them

Employee hesitation

Employees can be resistant to change. They may feel their workflows are just fine or fear they won’t have enough to do and may risk job security after some tasks are automated. Communicate clearly to them how automation can support their work — not take it away. Change fear into excitement about what they’ll be able to accomplish that was previously unmanageable.

Cost and ROI

A high initial cost and poorly defined ROI can cause business leaders and decision-makers to decide against intelligent automation tools. Set achievable KPIs at the beginning of your automation journey and divide your ambitions into smaller sprints. Each automation should prove its worth in time and cost savings and empower you to automate even more tasks across your organization.

Lack of expertise

Some intelligent automation solutions can be highly technical to set up and maintain — even no-code solutions can take time to figure out initially — and you may not already have a dedicated IT expert on staff. Consider hiring at least one subject matter expert, take advantage of your vendor’s after-sales support, and use the knowledge you gain to train generalists at your organization that can support your team when questions arise.

Set your business up for intelligent automation

Intelligent automation is growing more common as tools become more widely available, cheaper, and easier to use. With more forms of AI entering the mainstream, business leaders will need to implement automation tools to remain competitive and free their workforce up for the higher complexity issues and service that customers have come to expect.

Learn more about easy-to-use, intelligent automation tools like Workflow Builder and Slack AI.