How to Use AI for Operational Excellence
Organizations are under immense pressure to do more with less – streamline operations, reduce costs, all whilst improving both the outcomes of the business and their employees.
For IT and end-user computing (EUC) professionals, this challenge is especially prevalent. Systems are becoming increasingly complex, the digital employee experience is now directly tied to customer satisfaction, and the role of technology teams extends much further than solely keeping the lights on.
This is where AI for operational excellence comes into play. Artificial intelligence is empowering organizations to operate smarter, not harder. But operational excellence goes beyond efficiency – it's about consistently delivering high performance, aligning IT efforts with business goals, and driving continuous improvement across workflows, systems, and the employee experience.
What is operational excellence?
Before diving into the use cases that drive operational excellence, it's important to understand what operational excellence means.
Operational excellence is about running a business in a way that consistently delivers outstanding results. It means fine-tuning processes, cutting out waste, and relentlessly seeking opportunities for improvement. While efficiency is part of the picture, operational excellence extends further, it’s about building a culture where every team member focuses on creating value for customers, staying adaptable to change, and continuously improving day after day.
When applied to IT operations, AI for operational excellence involves applying intelligent systems, analytics, and predictive insights to improve workflows and support the needs of both IT teams and the employees they serve.
Key Areas Where AI Drives Operational Excellence in DEX
AI is already transforming how organizations operate. By leveraging AI in day-to-day operations, organizations can optimize processes, manage software and assets more intelligently, and significantly enhance support experiences.
Below are some of the top use cases where AI is actively driving efficiency and helping businesses achieve true operational excellence.
AI for Process Optimization
IT process optimization is one of the most powerful use cases of AI in operations. Traditionally, IT operations have been reactive – responding to tickets, troubleshooting issues manually and constantly facing the burden of repetitive tasks. With AI, this is no longer the case as organizations can shift to a proactive model – significantly reducing manual workloads and response times.
Examples of AI Process Optimization in Action:
- AI-powered device insights – AI can automatically surface patterns behind system or application crashes, unusual CPU or memory usage, and even collaboration tool issues such as poor call quality.
- AI powered remediations – Beyond detection, AI can automatically act on issues – resolving bottlenecks, restarting services, or applying fixes before employees even experience disruption.
By leveraging AI for process optimization, IT teams to quickly pinpoint root causes without hours of manual analysis and apply targeted remediations –allowing IT to focus on higher-value initiatives that directly support business growth.
Software Management
IT asset management has always been a balancing act. Too many licenses mean wasted spend, too few means productivity bottlenecks. How do IT teams ensure employees have the tools they need to succeed while managing the unnecessary costs?
AI makes software license management smarter. Through advanced analytics, AI can track software usage patterns across environments, identifying underutilized or redundant applications to reallocate or terminate unused licenses.
Key Benefits:
- Cost-optimization – eliminate wasted spend through identifying unused licenses that can be reclaimed or reallocated
- Smart inventory management – anticipate future software needs to prevent overstocking or shortages to keep resources aligned with real-world demand
- Enhanced decision-making – with accurate insights, IT leaders can make informed choices about renewals, upgrades, and vendor negotiations
By using AI for software license optimization, organizations not only cut unnecessary costs but also improve the digital employee experience. By eliminating redundant applications, organizations minimize context switching – a proven productivity killer, with 45% of employees saying it directly reduces their output.
Enhancing Support Experiences with AI
Another critical area where AI drives operational excellence is IT and customer support. Support functions are often overwhelmed by high volumes of repetitive issues, leading to delays and frustrations for both employees and customers.
AI is changing this dynamic by enabling faster and more personalized support experiences. Instead of long wait times or generic responses, employees and customers can now receive faster, context aware support.
Use Cases:
- Virtual agents – AI-powered chatbots and virtual assistants can resolve common issues instantly such as password resets or connectivity problems to reduce ticket volume and significantly improve response times.
- AI Employee Sentiment Analysis – AI can analyze conversations to detect user frustration, escalate urgent cases, and suggest tailored responses, improving both resolution quality and user satisfaction.
- Support improvement – By analyzing ticket trends, AI uncovers recurring problems, training gaps, or process inefficiencies. With these insights, IT teams can address the underlying root causes in support processes, rather than just the immediate issues.
Importantly, improving DEX through AI-powered support also positively impacts the customer experience (CX) as a result. Customer Service Advisors in industries like insurance, for example, may face delays resolving queries or processing requests if their systems aren’t performing which leads to frustration for both employees and customers.
However, organizations can flip this dynamic by giving employees seamless technology that enables them to serve customers faster, more efficiently, and with greater confidence.
Getting it Right with a Clear AI Implementation Strategy
AI will only deliver results if organizations adopt it with a clear strategy. Without proper planning, even the most advanced tools can fail to deliver ROI.
Steps to Success:
1) Assess current operations
Begin with a clear understanding of where your IT and business processes stand today. Identify bottlenecks, repetitive tasks, and areas with high error rates. These insights help pinpoint the priority areas where AI can make the biggest difference.
2) Identify high-impact AI use cases
Not every process needs AI. Focus on the use cases that directly solve the pain points identified in step one – whether it’s reducing downtime, cutting license costs, or improving support.
Prioritizing initiatives with clear ROI and broad business relevance makes it easier to secure early buy-in across the organization.
3) Choose the right tools and partners in the business
AI success depends on choosing the right technology and building the right partnerships. Evaluate vendors carefully to ensure their solutions align with your strategic goals. At the same time, partner with stakeholders across the business, not just IT. This includes – executive leadership, data teams and end users – to ensure AI initiatives address real pain points and deliver measurable value.
4) Continuously evaluate and scale
Avoid trying to transform everything at once. Begin with pilot projects in high-impact areas and measure their effectiveness. Start small and test use cases, based on this the effectiveness can be measured and scaled based on the proven value. Once there is proven value for the initial projects, scale gradually to expand AI adoption across more workflows and teams with confidence.
5) Demonstrate value
Early wins are powerful. Make sure to showcase quick successes to build momentum and secure ongoing support from leadership and employees. Transparent communication around impact, creates trust and strengthens the case for future AI investment.
Without a clear roadmap, even the most advanced AI tools risk falling short of expectations. With the right strategy, however, AI becomes far more than a technology investment – it becomes a long-term driver of operational excellence.
The Future of AI for Excellence
The next wave of AI will push operational excellence even further. Emerging technologies like agentic AI are already reshaping the workplace by enabling systems to not just respond but act proactively on behalf of employees and their IT teams.
Operational excellence with AI isn’t just a vision, it’s already happening. See how AI-Powered DEX with Nexthink empowers IT and employees to work smarter, faster, and more effectively.
Ultimately, the future of AI in the workplace isn’t about replacing people. It’s about amplifying human capability to accelerate decisions, enhance measurement capabilities, and create a higher-performing workplace.