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
"Personify" existing systems by providing chat-like natural language understanding interfaces.
System of Record Integration
IA aggregates disparate user interfaces and quickly changes systems to increase agility.
Data Analytics and Dashboarding
Intelligent automation collects and structures data into real-time dashboards and automates processes based on data-driven decisions.
Provide intelligent employee self-service interfaces allowing your employees to focus on more important work.
360-Degree View of the Customer
AI-led chat interfaces provide personalized support and services based on customer profiles and needs.
IA simplifies CRM updates and data quality to eliminate CRM app training and provide accurate sales and promotional planning.
Other available resources
Apps Are Not the Path to Digital Transformation
LCAPs promise to simplify and speed up development to create more apps faster but more apps cause more problems. Read how creating more apps may make your digital journey more difficult.
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 Business Outcome Orchestration
Krista Intelligent Automation orchestrates your people, internal apps, and AI to automate and optimize complete business outcomes.