Many companies today are still burdened by manual, inefficient processes that hold back productivity and innovation. AI-driven automation presents a tremendous opportunity to digitally transform these processes to unlock new levels of speed, quality, and customer value.

In this practical guide, we’ll explore strategies and real-world examples to inspire your automation journey. With the right approach, AI can inject automation throughout your organization to reduce costs, accelerate operations, and delight customers.

Step 1: Identify High-Value Automation Opportunities

The first step is methodically evaluating processes across every business function to pinpoint areas ripe for automation. Cross-functional input is key, as perspectives from IT, operations, customer service, finance, HR, and other groups reveal different needs.

Common automation opportunities include:

• Repetitive data entry/updates across systems
• Employee onboarding and offboarding
• Invoice processing and approvals
• Customer support interactions
• Marketing campaign setup and reporting
• Sales lead qualification
• Financial reconciliations
• IT ticket handling and triage

Step 2: Automate Where it Matters Most

With many potential automation ideas uncovered, prioritize opportunities that will have the greatest business impact. Factors like process importance, time spent, and cost savings help determine where automation will be most valuable.

For example, a retailer automated refund processing, which provided fast ROI by eliminating 50,000+ hours per year agents spent on this common task. Quick wins build automation momentum.

Step 3: Design End-to-End Automated Workflows

With targets chosen, design the envisioned end-state workflow powered by AI automation. This includes defining trigger events, data inputs, process steps, system interactions, error handling, and outputs.

Thoroughly mapping out these workflows on paper first, before any coding begins, is an important best practice. This upfront visualization clarifies how the automated processes should operate optimally.

Step 4: Build and Deploy AI Automation Capabilities

Next, it’s time to make the AI automation magic happen through development work. Robotic process automation (RPA) tools from leaders like UiPath and Automation Anywhere enable building software robots rapidly by demonstrating workflow steps.

Machine learning models can also be incorporated to handle unstructured data like categorizing support tickets or scanning documents. Leverage cloud services like AWS, Google Cloud, and Azure to scale automation footprint quickly.

Step 5: Monitor and Refine AI Automation Over Time

Like any technology project, expect an iterative process of continuous improvement once initial automation capabilities are live. Rigorously monitor performance indicators like cycle times, output quality, and system usage to identify enhancement opportunities.

Refine both the automated workflows and ML models based on real-world feedback to drive step-level efficiency gains over time. Expand scope by rolling out automation to additional process variants and geographies.

Real-World AI Automation Examples

Now let’s look at some inspiring examples of AI automation in action across various industries:

• Financial services: JPMorgan automated over 360,000 hours of manual work in its consumer lending division using RPA and machine learning. Bots handle loan adjustments, interest recalculations, fee assessments, and more.
• Retail: The floor care company Dyson built an RPA platform that automates order processing, supply chain operations, HR tasks, and other workflows. Process times have sped up by 2-3X with improved accuracy.
• Healthcare: Automation Anywhere’s bots at Blue Shield of California execute time-sensitive claims processing steps, reducing manual work by 73% while boosting staff satisfaction.
• Technology: Cisco’s “AUO” automation platform conducts employee onboarding including system access provisioning and equipment delivery. Onboarding completion time decreased from days to just hours.

The time for AI-driven automation is now. Follow the practical steps in this guide to scope, prioritize, design, and deploy automation in your organization. Partnering with experienced automation consultancies can accelerate this transformation journey. Contact DBGM to discuss launching your automation initiative today.