Across industries and verticals, enterprise automation has been delivering immense business value for a while now. However, by implementing enterprise automation, many organizations worry that they may have already reached their value threshold. That’s why many business leaders are now looking at expanding their use of automation technology as a business strategy.
They realize that the real challenge lies in automating complex business processes. This is driving the shift from enterprise automation to intelligent automation. Powered by AI, intelligent automation (IA) can self-organize data, draw “intelligent” inferences, and drive informed decisions. McKinsey reports that on its own, Generative AI has the potential to reduce manual workload by 60-70%.
How AI Is Driving Intelligent Automation (IA)
Defined as the “next wave in automation,” IA is the integration of AI and approaches like robotic process automation (RPA) and business process management (BPM). At the very core, AI is the “decision engine” of IA and serves to deploy machine learning algorithms to analyze structured and unstructured data.
In essence, IA can simplify business processes, which enables users to think about business outcomes or goals instead of focusing on the processes themselves. They can seamlessly go about:
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Seeking assistance for innovative tasks
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Improving the accuracy of their operations
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Enhancing the security of the operational framework
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Identifying opportunities to improve day-to-day workflows
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Eliminating the loopholes that otherwise pave the way for errors
With the combination of AI, RPA, BPM, and even computer vision, IA can streamline business processes and improve interactions between applications.
Automating Complex Processes Using IA
We talked about how IA simplifies workflows and streamlines complex processes. But how does this exactly pan out? Here are some examples that shed light on IA in action:
Financial Reporting
IA tools can automate the collection, processing, and analysis of financial data. Further, they can generate real-time financial reports by consolidating data from various sources.
Invoice Processing
IA technology can optimize complex invoice processing by validating invoice-related information in different formats and sources. It can also automate tasks like approving invoices, comparing invoices with purchase orders, and processing timely payments.
Workforce Hiring and Training
With intelligent automation, hiring companies can streamline complex HR processes like:
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Candidate screening
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Employee onboarding and exits
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Employee training
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Payroll processing
Supply Chains
For manufacturing and supply chain companies, IA tools can automate order processing and inventory management. Additionally, they can streamline supply chains by monitoring inventory levels and tracking real-time shipments.
Benefits and Challenges of IA
Indeed, the automation of complex processes accrues several business benefits in the name of:
Higher Productivity
According to a Deloitte report, organizations using intelligent automation are realizing a broad set of benefits. One of the major benefits is improved productivity. The report found that 63% of organizations are discovering new use cases for automation using process intelligence.
Besides automating processes and applications, IA tools can automate business decision-making processes and help in making accurate data-driven predictions. This automatically leads to higher business productivity.
Lower Costs
The same Deloitte report found that by automating business processes across their entire value chain, organizations are reducing their operational costs. Consider this; AI-powered chatbots or virtual bots can cut down operational costs by 30%. According to Salesforce, IA can also reduce business process costs by 25-40% on average.
Effectively, IA can save both time and money by automating end-to-end processes and minimizing human interactions.
Improved Accuracy
According to IBM, IA can “improve accuracy through consistent processes and approaches.” To emphasize this claim, it’s worth considering that intelligent automation can leverage AI to drive accurate decision-making in enterprises.
With a consistent approach to automating manual or repetitive tasks, IA tools can drive automation with more accuracy (and fewer errors) than humans. An example of this would be IA-powered bots automating the generation of error-free production reports in a manufacturing facility.
Enhanced Customer Experience (CX)
AI-powered chatbots can resolve customer complaints across channels and take over 30-50% of the workload handled by customer service agents. Also, with AI-enabled automation tools (especially those equipped with generative AI capabilities), organizations can quickly understand their varied customer base and market needs and offer the right products or services. As such, with the growing focus on omnichannel CX, IA can help companies integrate multiple customer touchpoints and channels.
Despite all these benefits, it’s not easy for organizations to automate complex processes. Some of the common IA-related challenges include technical skill shortage, ambiguity about internal processes, and lack of standardization. For a successful implementation, organizations need to clearly define the objectives of automation along with a detailed action plan.
Additionally, enterprise users and employees need adequate training on the use of the new technologies. They must also be aware of the importance of data security and privacy.
Making the Leap to Intelligent Automation with Recode
At Recode Solutions, our AI-led automation services enable our customers to identify opportunities for automation, build innovative solutions, scale their operations, and evolve the workflows. From cognitive automation to collaborative automation, our solution delivery ensures that businesses leverage the latest technologies to create and sustain their operational models.
Want to upgrade to the next level of automation using the capabilities of generative AI and intelligent automation? Contact us today!
