Generative AI (GenAI) is leading a widescale evolution of business processes across industries. The rapid development of use cases for the technology makes it critical that organizations invest now or risk falling behind. A recent report showed that 82% of organizations plan to introduce AI agents across their business in the next three years. It’s easy to see why. AI agents, particularly GenAI, have enormous potential to accelerate digital transformation journeys—from improving operational efficiencies to helping multi-channel contact center agents deliver experiences that delight and surprise customers.
Executive Vice President and Global Head of Business Process Services at Hexaware.
The race to an AI-driven future
As technology develops, organizations are under increasing pressure to demonstrate to customers and investors that they are at the forefront of innovation. They are looking to embrace GenAI to create new value by augmenting traditional business processes with new efficiencies and to drive better customer experiences. However, there is a risk of investing in technology for its own sake if they don’t embark on their adoption strategies with a clear goal in sight. This is especially true when it comes to GenAI. Two years after the emergence of ChatGPT, we’ve seen countless use cases being explored and developed. The time for experimentation is over.
In 2025, organizations need to focus on proven, value-driven applications of GenAI aligned with clear business objectives. Without this more purposeful approach, they will only scratch the surface of the benefits the technology can unlock. With the clock ticking, organizations must quickly determine which use cases to focus on and how to integrate them into their operations to create value. Here are three of the most impactful GenAI use cases that are already proven to elevate business processes to a whole new level:
1. Enhanced central business functions
GenAI should not be about reinventing the wheel. As a first step, organizations should focus on improving central business functions they already perform well. Initial use cases should be aligned to streamlining key processes such as document handling and supply chain management. These use cases will be more effective with focused AI models trained on targeted data sets that provide the rich context needed to automate specific functions with precision.
As a result, organizations will increasingly embrace Small Language Models (SLMs) in 2025. These approaches are more cost-effective, easier to customize, and have fewer parameters than Large Language Models (LLMs), making them better suited to targeted business functions. In fact, 56% of organizations plan to use SLMs within the next three years, demonstrating the central role they will play in future GenAI strategies. As they continue to curate SLMs for new use cases, organizations will be able to power further AI solutions to streamline additional business functions.
2. Improved CX and quality of life
Customer experience (CX) is another function organizations can take one step further with GenAI. Most significantly, GenAI assistants can make life easier for service agents and help them deliver better outcomes for the business, especially those in CX roles. For example, contact center teams may have to search multiple systems for the information they need to handle customer complaints or reschedule an appointment during a support call. This process takes time, keeping the customer waiting longer and degrading their experience — especially if they are forced to recount previous conversations with other team members.
With a GenAI assistant, time-consuming tasks associated with document processing and information gathering can be automated. This helps agents deliver experiences far beyond what callers expect, allowing organizations to surprise and delight their customers. It also enables service agents to focus on higher-value tasks such as building relationships with customers, giving them greater job satisfaction, and alleviating burnout. As these capabilities mature, leveraging a blend of humans and GenAI agents will revolutionize customer experience through predictive analysis and process automation, helping organizations to remain agile and carve out a more decisive competitive advantage.
3. Advanced communication skills
Finally, GenAI has real potential to reduce language barriers and empower service agents to support customers from any location. A recent report found that AI can deliver a 90% reduction in document translation time, resulting in efficiency savings of up to 2.79 million euros. GenAI can use a similar capability to detect language and automate responses to frequent customer queries via webchat, email, social media, and even phone. In many cases, this removes the need for customers to speak with service agents. That not only improves customer satisfaction by accelerating resolution time but extends the organization’s reach by moving beyond traditional communications channels.
Human agents can also leverage AI-powered voice assistants to translate conversations during live service interactions so that they can speak with customers without being fluent in their language. This means that in 2025, human empathy and experience in dealing with complex customer challenges are the skills that will matter most for service agents, not the number of languages they speak. As their use cases for GenAI mature in this area, organizations will propel customer experience to the next level by streamlining workflows and reducing case resolution times dramatically.
Generating value with AI
GenAI has huge potential to transform business processes, but organizations urgently need to move beyond the experimentation phase to tap into this opportunity. As tangible use cases continue to emerge, organizations must have clear, customer-focused objectives and a well-defined roadmap to ensure they integrate these technologies in a way that drives value. With this more considered approach, they will be much better poised to reap the rewards of GenAI and deliver market-leading innovation.
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