Top 5 Industry Use Cases for Intelligent Process Automation in 2025

The pressure to do more with less has never been greater. Businesses are drowning in data, struggling with inefficiencies and racing to meet the demands of a 24/7 digital world. Traditional automation alone can’t keep up, it lacks the intelligence to process unstructured data, adapt to change and make informed decisions. However, with Intelligent Process Automation (IPA), businesses can overcome these challenges. Intelligent Process Automation (IPA) combines AI’s cognitive abilities with robotic process automation (RPA) to create smarter, self-learning workflows. It enables businesses to process workloads with minimal human intervention. Read our latest article to explore the top 5 use cases of Intelligent Process Automation in 2025.

1: Customer Service and Support Automation 

Customer support demand is rising across digital channels and modern consumers expect instant, 24/7 service. A Salesforce Survey shows that 80% of users now value the customer experience as highly as the product or service itself. Traditional call centres struggle with rising inquiry volumes, multi-channel communication (phone, email, chat, social media) and the cost of staffing around the clock. IPA can help meet these expectations efficiently. In 2025, 80% of companies will adopt AI chatbots for customer service, according to Gartner. 

Many businesses now deploy AI-powered virtual agents to handle a large portion of customer queries autonomously. For example, banks and telecom providers use conversational AI to guide customers through routine transactions (balance inquiries, plan changes) without human help. These AI agents can manage thousands of chats simultaneously, drastically reducing wait times and improving first-contact resolution. They provide instant answers around the clock, which boosts customer satisfaction and loyalty​

When an issue is too complex, the IPA system intelligently hands off the customer to a human rep along with context, ensuring a seamless experience. The impact is significant – companies report higher customer engagement and lower support costs.  This frees up human support teams to focus on high-value, complex customer issues while the “digital workers” handle the repetitive queries.

2: Sales and Marketing Automation 

Sales and marketing teams face data overload and time-consuming manual tasks. Without intelligent automation, businesses risk missing opportunities or targeting the wrong audiences. IPA is needed to handle the scale and speed required – it can sift through big data to find sales prospects or segment customers far faster than manual methods. Reports also suggest that companies using AI personalisation see 5–15% increases in revenue and improved customer retention​

Leading firms are deploying AI to take over many steps of the sales cycle. For instance, AI bots crawl the web or internal databases to identify potential leads that fit a target profile and then automatically send outreach emails or offers. Marketing departments use IPA to segment customers based on behaviour and launch targeted campaigns without manual spreadsheet work. An example is the use of AI agents to analyse campaign performance live – if certain ads are underperforming, the system reallocates the budget or suggests new content on the fly.

E-commerce companies also use IPA for dynamic pricing and recommendations (adjusting prices or promotions based on real-time demand and inventory). These applications allow the front-office teams to scale their efforts dramatically. Manual, “hands-on” marketing is being augmented by AI to handle routine follow-ups and free a salesperson to focus on closing deals​. The result is faster lead conversion, more personalised customer outreach and data-driven decision-making in sales.

3: Operations and Supply Chain Optimisation 

Global supply chains are under pressure from unpredictability (demand swings, geopolitical shifts, etc.) and the need for efficiency is imperative. Many companies have experienced stockouts or overstock due to poor demand visibility, as well as rising costs in transportation. Traditional supply chain management often involves siloed systems and manual data reconciliation. An IPA system can watch for supply disruptions or delivery issues in real-time and trigger contingency actions. By automating these processes, companies aim to avoid costly errors and respond faster to market changes.

For example, a global shipping firm can use an AI agent to monitor fleet data and suggest rerouting deliveries to avoid delays. Dun & Bradstreet uses AI agents to ensure accurate business data for 95% of Fortune 500 companies – enabling more informed credit and supply chain decisions. Across manufacturing and retail, IPA is also automating supply chain paperwork: bots handle order entries, invoicing, and customs documents by extracting data from forms and populating systems. 

4: HR and Employee Management Automation 

HR departments in large organisations deal with high volumes of repetitive, paperwork-heavy tasks that are prone to delays and errors. In 2025, many sectors face talent shortages, making efficient hiring more critical than ever. However, manual recruiting is slow: coordinating interviews, sifting thousands of resumes and ensuring a good candidate experience is challenging with limited HR staff. 

Likewise, onboarding and training employees across distributed teams require significant coordination. IPA is needed to relieve HR teams of administrative burdens so they can focus on strategic initiatives (like culture and talent development). To give an idea, the adoption of AI in HR has surged – 99% of talent acquisition teams now use AI/automation to streamline hiring (with 93% planning further tech investments in 2025). 

In recruiting, many companies use AI screening tools as the first line of resume review – for example, an AI system can scan resumes for keywords or experience and rank candidates, cutting down the pool to a manageable list for human recruiters. Some organisations deploy AI interview bots for initial candidate Q&A, saving recruiter time. These practices have led to significant improvements; a recent survey found that 98% of companies saw improved hiring efficiency via AI in tasks like scheduling and resume screening. 

During onboarding, IPA can automatically collect all necessary employee information, trigger IT to create user accounts and schedule orientation sessions. An intelligent onboarding bot might, for instance, send new hires personalised training materials and check in on their progress, ensuring no step is missed.

5: Finance and Accounting Automation 

Finance departments must ensure high accuracy and compliance but they traditionally rely on many manual processes such as entering invoice data, reconciling accounts, checking transactions for fraud, compiling reports, etc. Manual work in finance is not only slow but can lead to costly errors or missed deadlines. IPA can help achieve the speed and accuracy required. According to Roland Berger., adopting AI-driven finance solutions can make the finance function 15–20% more efficient overall. Companies have reported tangible improvements: automating pieces of accounts payable led to 33% faster invoice approvals, and automating aspects of the financial close process cut closing time by 25%. This is crucial as CFOs are pressured to “do more with less” and provide real-time financial insights. 

A common application is intelligent invoice processing – invoices emailed or scanned are automatically read by AI (using OCR and NLP to extract vendor, amount and dates) and then an RPA workflow enters that data into the accounting system and routes it for approval. This removes human data entry and errors. Many organisations have deployed such invoice bots to achieve near “touchless” accounts payable. In financial services, IPA is used for document-intensive workflows. For example, JPMorgan Chase implemented an AI-driven system (COIN) to analyse legal loan documents, saving 360,000 hours of work per year​ that lawyers and loan officers would have spent manually.

Accelerating IPA with the AI Supercloud

Across all these use cases, one thing remains clear, the need for powerful, scalable and secure infrastructure. The AI Supercloud provides enterprise-grade support for large-scale AI and automation deployments: 

• Scalability and Performance: IPA workloads can surge when handling large datasets or high transaction volumes, such as peak customer inquiries or quarter-end financial processing. Our AI Supercloud delivers cutting-edge GPU clusters for AI such as NVIDIA HGX H100, NVIDIA HGX H200 and the upcoming NVIDIA Blackwell GB200 NVL72/36 optimised with advanced networking solutions like NVLink and NVIDIA Quantum-2 InfiniBand, enabling AI models and bots to operate smoothly even under heavy loads. 

• AI Model Integration: Seamlessly integrating AI models into business workflows is essential for intelligent process automation. That’s why we provide fully managed Kubernetes and MLOps support, streamlining model training, deployment and optimisation. Whether developing a new fraud detection model or enhancing chatbot capabilities, our AI Supercloud empowers teams to build, train and deploy AI models within a scalable environment- accelerating innovation and time to market.

• Compliance & Security: Data sovereignty and security are imperative for enterprises handling sensitive HR or financial data. We’ve designed the AI Supercloud with AI-optimised, sustainable data centres that comply with strict regional regulations, including European data protection laws. Our secure environments protect your confidential information while providing the technological advantages of a sovereign cloud.

• Reliability & Customisation: IPA systems are mission-critical and downtime is not an option. We prioritise reliability with robust cloud architecture and enterprise-grade support. Our platform also offers customisable hardware and software configurations tailored to specific business needs. Whether you require additional GPU power for deep learning in image analysis or more CPU/memory for RPA orchestration, we ensure cost-efficiency and peak performance. With our flexible approach, you’re not locked into a one-size-fits-all solution—you get an AI infrastructure fine-tuned for your automation workloads.

Schedule a discovery call with our solutions engineer to assess your existing infrastructure, business objectives and unique requirements in detail.

FAQs

What is Intelligent Process Automation (IPA)?

IPA is the combination of AI and robotic process automation (RPA) to create intelligent, self-learning workflows. It enables businesses to automate complex processes, handle unstructured data, and make real-time decisions with minimal human intervention.

How does IPA improve customer service?

IPA powers AI chatbots and virtual agents that handle routine queries 24/7, reducing wait times and improving customer satisfaction. When issues require human assistance, IPA ensures seamless handovers with full context, leading to faster and more personalised support.

Can IPA help in sales and marketing?

Yes, IPA automates lead generation, customer segmentation, and personalised outreach. AI-driven marketing systems analyse customer behaviour, adjust campaigns in real time, and optimise engagement—helping businesses boost conversions and revenue.

How does IPA optimise supply chains?

IPA provides real-time monitoring of logistics, predicts disruptions, and automates document-heavy tasks like invoicing and customs clearance. This ensures efficient inventory management, cost reduction, and faster response to market changes.

How is IPA transforming HR operations?

HR teams use IPA for automated resume screening, interview scheduling, and employee onboarding. AI-driven tools reduce administrative workloads, speed up hiring processes, and enhance the employee experience with personalised training workflows.