Chapter 02
Technology that transforms the back office
The swan’s glide is only possible with strong, synchronized movement beneath the surface. Likewise, modern back-office operations require synchronized technologies that provide speed, accuracy and resilience.
Manual workflows, legacy systems, and siloed tools limit productivity and create inconsistencies that directly impact the customer experience. Technology offers a way forward, providing the insights you need to make faster, better decisions.
The most successful back-office transformations focus on technologies that solve specific operational pain points while ensuring seamless integration with front-office systems. The goal is not to add more tools, but to implement the right ones in the right places.
64% of customers will spend more if a business resolves their issues where they already are.3
Back-office AI
Generative AI has surged in popularity over the last few years, but it represents only one aspect of the broader AI field. Leveraging the full range of AI technologies can reshape business operations. Let’s look at five key areas where AI can drive transformation in the back office.4
Artificial Intelligence (AI)
AI builds on automation by adding the ability to learn from patterns, process unstructured data and make informed predictions.
Example: AI optimizes inventory and supply chain management by predicting demand and automating warehouse tasks.
Machine Learning (ML)
ML algorithms analyze patterns in data and make smart predictions.
Example: ML models detect and flag potentially fraudulent expenses by learning from historical transaction data.
Neural networks
Inspired by the human brain, neural networks recognize patterns in diverse data types.
Example: Neural networks speed up invoice management by accurately classifying and tagging documents based on content.
Deep learning
Deep learning uses complex, layered neural networks for self-learning and adaptation as data evolves.
Example: Deep learning uncovers workforce trends, supporting better talent acquisition, retention and evaluations.
Generative AI (GenAI)
A subset of deep learning, GenAI creates new data and insights from existing information.
Example: GenAI generates financial reports with smart insights and simulates advanced business scenarios using historical records.
Value of AI in banking, according to banking executives5
Chatbots and virtual assistants
Personalized marketing and product recommendations
Improving back-office productivity
Robotic process automation (RPA)
RPA has been around for at least 15 years, with applications in contact centers increasing over the last five or six years. It uses software “bots” to handle repetitive, rules-based tasks quickly and without errors. These bots can run continuously, process large volumes of work and ensure consistency across operations. Benefits include reduced cost; increased speed, accuracy, and consistency; and improved quality and scalability of production.
Common uses for RPA in the back office include:
- Data entry and updating records
- Generating invoices and processing payments
- Preparing onboarding documentation in HR
- Updating inventory and creating purchase orders
Data analytics
Data analytics turns operational data into actionable insights. In the back office, it can pinpoint inefficiencies and uncover trends that inform decision-making. For example, analytics can help managers identify recurring errors in order processing, measure compliance with service-level agreements and highlight performance variations between teams. This level of visibility allows leaders to address problems before they escalate and prioritize improvements that deliver measurable gains.
Workforce management (WFM)
Although WFM tools are widely used in contact centers, they remain underutilized in back-office operations. These platforms help forecast workloads, schedule resources and track productivity in real time. By applying WFM principles to functions such as claims processing or order fulfillment, organizations can optimize staffing levels and balance workloads across teams.
Integration as a competitive advantage
Connecting data and workflows across departments eliminates duplication, reduces manual transfers and ensures all teams are working from the same source of truth. For example, linking a CRM system with an order management platform gives sales teams instant visibility into stock levels and delivery timelines. Similarly, integrating HR and payroll eliminates errors that can occur when information is re-entered manually.
Laying the groundwork for implementation
Before investing in new technology, organizations should take time to understand their current workflows and identify where the most significant gains can be made. This requires mapping existing processes and standardizing steps where possible. Leadership should also be aligned on clear objectives. Training is equally important. Employees must understand both how to use the tools and why the change is being made.
3 Zendesk, “CX trends 2025,” zendesk.com.
4 Deloitte, “Uncovering hidden value through back-office AI,” deloitte.com.
5 OpenText, “State of AI digital banking report,” opentext.com.
Ebook
Back-office advantage: Driving customer success through operational excellence
