Intelligent Automation for Manufacturing

Intelligent Automation for Manufacturing


Manufacturers evolve automation use cases 

In the past few decades, robotics and automation have become increasingly sophisticated, leading to manufacturers’ more significant degree of automation. Several types of automation use sophisticated technologies such as robotics, sensors, and artificial intelligence to carry out tasks that would otherwise require human labor. Robotics increases worker safety and productivity and lowers costs but doesn’t manage constraints and dynamic market changes for business processes and decisions. 

AI-led tools "Focus more on context and adapting to people and less on task and process flows...[and] AI-led process improvement will take a people-first approach. Context will drive required actions within a single UI experience centered around the customer or employee journey.” - Forrester

Twelve Criteria Help Choose Among DPA, Embedded Process Support, RPA, And AI-Led Platforms, Forrester, October 2021

Intelligent automation removes process bottlenecks 

There is a growing trend toward using intelligent automation in manufacturing business processes as they learn from the factory floor. Intelligent automation (IA) combines artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and process automation to optimize business operations. Just like robotics have augmented physical labor, manufacturers use IA to automate business processes with software instead of relying on humans to memorize tasks and steps to complete an outcome. Intelligent automation systems work faster and more accurately than humans, meaning tasks can be completed in a shorter timeframe and at lower total costs. 


AI optimizes internal processes 

Manufacturing companies have long automated supply chains to provide the fastest throughput possible. However, these organizations have similar opportunities to automate complete processes across internal functions. Today, manufacturers realize AI enhances internal processes by using software to automate previously time-consuming tasks. Manufacturers automate complete business processes to maintain margin and maximize resource utilization by using AI-led intelligent automation.  

Intelligent Automation Use Cases

Manufacturers can apply automation to several business functions to increase outcomes. Some examples include:

Natural Language Understanding

Natural Language Understanding

"Personify" existing systems by providing chat-like natural language understanding interfaces.

Record Integration

System of Record Integration

IA aggregates disparate user interfaces and quickly changes systems to increase agility.

Data Analytics

Data Analytics and Dashboarding

Intelligent automation collects and structures data into real-time dashboards and automates processes based on data-driven decisions.


Human Resources

Provide intelligent employee self-service interfaces allowing your employees to focus on more important work.

Customer view

360-Degree View of the Customer

AI-led chat interfaces provide personalized support and services based on customer profiles and needs.

Salesforce Automation

Salesforce Automation

IA simplifies CRM updates and data quality to eliminate CRM app training and provide accurate sales and promotional planning.

Other available resources


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The Future of Intelligent Automation - Krista Software

The Future of Intelligent Automation

Digital transformation is building or optimizing business models using modern digital technologies. Today, the speed at which your company transforms depends on your ability to change your systems and change your people.

Krista Outcome Orchestration

Krista Business Outcome Orchestration

Krista Intelligent Automation orchestrates your people, internal apps, and AI to automate and optimize complete business outcomes.

Contact us to learn how AI-led intelligent automation can increase your productivity.

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