What is AI Business Process Automation?

AI-powered business processes improve cost efficiency and ROI. Tasks which previously required human input are managed independently through business automation, mitigating human error and often working at greater pace. Artificial intelligence is the difference-maker here – where traditional automation may have fallen down at decision-points, the greater decision-making capabilities of machine learning keep workflows moving and maintain process uptime.  

This improves ROI on multiple fronts: you maximize platform outputs, minimize human input, improve overall productivity, and you may even identify opportunities to reduce technology costs.   

Robotic process automation accelerates the completion of complex tasks while minimizing errors; providing a ‘dual threat’ of speed and accuracy improvement. While humans can build advanced data analysis skillsets and even work on predictive analytics, the truth is that we are prone to procedural errors. Especially where vast volumes of data are in play. Artificial intelligence, on the other hand, does not lapse in concentration or apply logic inconsistently. Moreover, the AI layer enables your technology to develop its understanding and build greater operational efficiency over time.  

Your team will be able to maintain both speed and accuracy up to a point. The true challenge lies in scaling – as your business grows, it becomes more difficult for humans to support both speed and accuracy. Get the balance wrong, and customer satisfaction could suffer.  

Intelligent process automation enables you to scale without introducing the risk of human error, and often without recruiting additional capacity which comes with salary costs. Companies can rely on AI systems with natural language processing to handle tasks of increasing scale without additional difficulty. For example: data processing, insight generation and personalized marketing can all be built into an RPA solution which will handle 10,000 contacts as easily as it manages 1,000.  

Offer better customer experiences by maximizing AI capabilities in your Content Supply Chain. Integration is the key ingredient. AI can conduct large-scale data analysis to identify new segmentation opportunities for your campaigns. Or, it can cater to individual customers based on real-time actions – provided that insights are flowing effectively through your business.  

Consider your data sources: your website, social media channels, sales activity, telemarketing, events and more. How does data from each of those channels reach your Marketing Automation Platform or CRM where it can assessed and handled by AI? 

Get it right, and machine learning can amp up your personalization efforts without significant human input. 

Scaling a business puts pressure on existing employees as the requirement for personalized content and campaign velocity grows. And while the results are clear, digital transformation itself can cause friction as long-term team members adapt to new ways of working. But, better employee experiences are possible as a result of business process automation!  

Show your employees how AI-powered business processes will remove mundane, repeat and routine tasks from their workload to break down the AI fear factor. You can realign workloads toward role-appropriate and skillset-maximizing tasks which will improve career prospects. They may have more space for creative tasks, or more capacity for revenue-driving sales activities that support their own remuneration.  

With the right training and support, AI business process automation can support a happier and more engaged team.   

AI implementation usually requires access to vast amounts of data to train its algorithms and perform tasks. In many use cases this data will be personal or of a sensitive nature. For organizations in regulated industries, this may introduce significant privacy and security risks including data breaches, unauthorized access or misuse of information. Compliance with regulations whether nationwide, such as GDPR in the UK, or more locally like CCPA in California, can pose another complication. Fortunately, there are answers to these challenges.  

Strong data encryptions and secure access controls can still safeguard sensitive information. You may choose to regularly audit your AI systems for compliance with privacy laws and ethical standards. Or, you can adopt privacy-preserving AI techniques such as federated learning or differential privacy to limit exposure to personal data. Ultimately, you will need to educate employees on secure data usage to uphold your best practices and safeguard your business.  

Implementing AI in business processes can require upfront investment in technology, infrastructure and expertise. Many software platforms are subject to license fees, and you may need to consider your wider infrastructure including computing power and server capacity to see the best results.  

Your best ally here is to demonstrate the return on investment (ROI) you will achieve through the implementation. Secure senior buy-in and you will be better supported to achieve AI success.  

Moreover, some of the costs can be mitigated. Working with a proven partner may reduce your reliance on in-house skillsets to accelerate your implementation without building in long-term dependencies. AI vendors or consultants will upskill your existing team members as part of a rollout, giving you better return on existing salary commitments.  

Finally, you can start small. Implement AI in specific, high-impact areas such as those mentioned above to demonstrate ROI before scaling.  

We mentioned the AI ‘fear factor’ above –it’s an important cultural factor to be aware of. Robotic process automation, especially where it touches AI, often requires companies to rethink workflows, roles and responsibilities. This can create some resistance from employees who may struggle to adapt or even fear job loss through automation. Successful adoption depends on fostering a culture of acceptance and providing sufficient training to upskill employees, even if it is time-intensive or adds costs.  

First, maintain transparency by clearly communicating the purpose, benefits and objectives of AI to employees. Emphasize collaboration rather than replacement. 

Design comprehensive training programs to equip employees with the skills needed to work using AI tools – or retain an AI partner to help you.  

You may even use recognized change management frameworks, such as Kotter’s 8-step process, to guide the organization through the digital transformation effectively while securing universal buy-in.  

AI technology adds major value to intelligent process automations in your data infrastructure. AI will process vast amounts of information much faster than manual input to rapidly automate manual tasks such as data entry, data analysis and insight generation. Natural language processing from AI software is an important tool as it increases your capacity to handle unstructured data from sources including scanned documents and emails which rigid RPA may fail to complete.  

The outcomes are manifold. You benefit from time savings and cost reduction on data tasks, better accuracy to minimize errors, and real-time access to clean and organized data for better forecasting. Remember, data without insights is just numbers. Leverage AI to equip your team with actionable insights, and empower them to make an impact.  

AI business process automation enhances customer service by automating routine interactions such as answering FAQs, routing tickets and processing simple requests. Chatbots and virtual assistants use natural language processing to provide instant and accurate responses, while automations and onward integrations streamline ticket management escalations to human agents.  

With such tools, you can offer faster response times and 24/7 support availability. This gives improved customer satisfaction due to quicker issue resolution, and may include personalization through AI analysis of the customer’s individual history. Concurrently, you are improving customer experiences and reducing support team workload to benefit overall satisfaction.  

Intelligent process automation drives operational efficiency throughout your supply chain and logistics. You can automate inventory management as stock moves in and out, track shipments and forecast demand. Machine learning models analyze historical data and market trends as a predictive analytics exercise, while your integrations and automations ensure smooth workflow coordination between suppliers, warehouses and distributors.  

Your key outcomes include reduced operational costs, better delivery accuracy and enhanced demand planning – all supported by greater supply chain visibility and adaptability to disruptions.   

AI process automation streamlines sales and marketing by automating lead generation, email campaigns and customer segmentation. AI tools built into your BPA analyze customer data to predict behaviors, identify high value prospects and carve out new segments; all feeding insights that drive personalization through your Marketing Automation Platform. 

This results in increased revenue from more targeted and timely marketing efforts. You see greater efficiency in your sales pipeline management, and better customer engagement with personalized and data driven interactions. Plus, consistent tracking and reporting of marketing performance metrics is part of the automated process.  

Be led by data, not by intuition. What are the pain points facing your business? Where are the greatest inefficiencies? Map these challenges against your objectives, and choose high-impact projects with few barriers to success.  

Don’t “boil the ocean”. Start small and select the most appropriate processes for AI automation – prioritize those that will show the best return with minimal friction. 

Data quality ensures accurate AI outcomes. Protect your integrations, reduce data siloes and ensure insights flow freely to maximize AI success.  

Automated processes require long term monitoring and optimization to secure their success rate. Keep a close eye on performance and identify new opportunities for integration and growth.