The Overlooked Roadblock For AI: Manual Processes

For companies that still need to adopt AI-based automation for manual processes, the key to success rests in adopting a structured approach that defines business, technology, and people considerations.

Niranjan Vijayaragavan, Chief Product Officer, Nintex

September 16, 2024

4 Min Read
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Nikreates via Alamy Stock

While some tech leaders debate the risks and pitfalls of artificial intelligence, many others explore its opportunities and potential. For example, over half (64%) of business owners who use or plan to use AI expect it to increase productivity, according to a Forbes Advisor survey.  

However, what I find more fascinating is the speculation around real-world applications, especially within the verticals that are most ripe for digitization and automation. Believe it or not, even in the age of AI there are a surprising number of businesses that rely on manual tasks and processes. How can an AI model optimize construction designs that are drawn with pencil and paper? How can LLMs automate medical billing when 90% of healthcare providers still use manual processes for patient collections?  

While it’s clear these industries stand to benefit from generative AI, they must crawl before they run in the automation race. Otherwise, organizations can hurt their operational productivity if they don’t first have the necessary infrastructure.  

What Decision-Makers Need to Know  

Less than half of mid-market organizations successfully complete their automation pipelines,for a variety of reasons. Some manual processes may be intricate or involve human judgment that is challenging to replicate with automation; existing legacy systems may lack modern APIs or are difficult to interface with automation tools; and there may be a lack of ongoing maintenance and support to keep automation solutions operational and effective.  

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As a business begins to implement its automation pipeline, decision makers should consider this framework as a guiding principle: 

  • Identify where automation is most helpful 

  • Automate using low-code tools augmented by AI  

  • Scale adoption of automation through modern interfaces and powerful engagement techniques  

To help address some of the barriers, organizations should:  

Focus on human benefit: People are more open to embracing automation when they understand it is designed to improve their experience at work. Leaders should map creative ways their teams can use regained time rather than letting the default expectation be that people just “do more” of whatever else they were doing before.  

Focus on flexibility: Understand that automation is not a “set it and forget it” process. Regularly explore if there are ways to creatively adjust and tune your automation systems to be of maximum service to your business.  

Value Creation Through Automation

Automation is not a one-size-fits-all solution. One common assumption is that the goal of automation always is efficiency, but that’s not the case. The primary drivers behind automation include:  

  • Adding value to a product or service  

  • Making processes more predictable or accurate  

  • Improving the customer experience  

  • Enabling scale and growth for the business  

  • Fostering collaboration across organizations  

  • Making work less repetitive or frustrating  

Establishing the goal of automation is crucial to successfully implementing the technology. Once they establish a clear goal, companies should choose one specific process to automate end-to-end. This becomes a model that can be adapted for other instances. For example, a company could look to its HR department and automate its entire employee onboarding process to efficiently get new talent set up for success. From there, build on this success throughout the organization and install tailored solutions based on the needs of your teams.  

In many cases, low-code automation software may be the quickest way to automate certain tasks and should be considered a real solution before other more advanced tools. These tools offer a good first step for automating and injecting AI-driven enablers on top of this foundation.  

Apply an Automation Framework  

An automation framework is a set of guidelines, best practices, tools and reusable components that provide structure and consistency for automation within an organization. Most importantly, it establishes a systematic approach to designing, implementing and managing automated workflows.   

An automation framework helps organizations achieve consistency, efficiency and scalability in their automation efforts by providing a structured approach.  

Standardization: Standardizing processes across the company avoids potentially costly errors and improves overall accuracy.   

Scalability: A structured approach can help scale automation initiatives as the company grows, ensuring it can handle increasing volumes of work without increased costs.  

Cost Savings: Reduces operational costs by minimizing manual effort  

Compliance: Covers the adherence to regulatory requirements and internal policies through a consistent automation process.  

Devising a comprehensive and applicable framework can feel a bit daunting at first. But by laying the foundation for your automation work, it will save you headaches in the long run as teams begin to adopt increasingly new and innovative technology.   

Scale Automation Practices across Teams 

Too many companies get wrapped up in the headlines and promises of exciting technology like AI without considering the infrastructure needed for it. Already having automation in place will make the implementation process for emerging technologies easier and ensure that every team gets the tools that fit their needs.  

Above all else, making automation stick is most important. That's why it is critical to build a clear understanding of how to implement automation effectively, from a framework to the specific goals and to the barriers within your organization that may hamper its use.   

About the Author

Niranjan Vijayaragavan

Chief Product Officer, Nintex

Niranjan Vijayaragavan has spent more than two decades driving product strategy, vision and execution for organizations including Microsoft, Boston Consulting Group (BCG), Expedia and Avalara. With extensive SaaS product development expertise Niranjan has successfully led and grown global teams. He has a master’s degree in engineering from the University of Maryland and an MBA from Haas Business School. 

 

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