Generative AI (GenAI) is leading a large-scale evolution of business processes across industries. The rapid development of technology use cases makes it critical that organizations invest now or risk being left behind. A recent report showed that 82% of organizations plan to introduce AI agents into their businesses in the next three years. It’s easy to see why. AI agents, particularly GenAI, have enormous potential to accelerate digital transformation processes, from improving operational efficiency to helping omnichannel contact center agents deliver experiences that delight and surprise customers.
Executive Vice President and Global Head of Business Process Services at Hexaware.
The race towards 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 seek to adopt GenAI to create new value by augmenting traditional business processes with new efficiencies and drive better customer experiences. However, there is a risk in investing in technology for its own sake if you do not embark on your 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 have seen countless use cases explored and developed. The time for experimentation is over.
In 2025, organizations should focus on proven, value-based GenAI applications, aligned with clear business objectives. Without this more determined approach, they will only scratch the surface of the benefits that technology can generate. With time running out, organizations must quickly determine which use cases to focus on and how to integrate them into their operations to create value. Below are three of the most impactful GenAI use cases that have already proven to elevate business processes to a whole new level:
1. Improved core business functions
GenAI shouldn’t be about reinventing the wheel. As a first step, organizations should focus on improving the core business functions they already perform well. Initial use cases should be aligned to optimize key processes such as document management and supply chain management. These use cases will be most effective with focused AI models trained on specific data sets that provide the rich context needed to accurately automate specific functions.
As a result, organizations will increasingly adopt small language models (SLM) in 2025. These approaches are more cost-effective, easier to customize, and have fewer parameters than large language models (LLM), making them more suitable for specific business functions. In fact, 56% of organizations plan to use SLM in the next three years, demonstrating the central role they will play in future GenAI strategies. As they continue to select SLM for new use cases, organizations will be able to drive more AI solutions to optimize additional business functions.
2. Improved CX and quality of life
Customer experience (CX) is another function that organizations can take a step further with GenAI. Most importantly, GenAI assistants can make life easier for service agents and help them deliver better results for the business, especially those in CX roles. For example, contact center teams may need 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, makes the customer wait longer, and degrades 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 allows service agents to focus on higher-value tasks, such as building customer relationships, providing greater job satisfaction, and alleviating burnout. As these capabilities mature, leveraging a combination of humans and GenAI agents will revolutionize the customer experience through predictive analytics and process automation, helping organizations remain agile and gain 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, translating into efficiency savings of up to €2.79 million. GenAI can use a similar capability to detect language and automate responses to common customer queries via web chat, email, social media, and even the phone. In many cases, this eliminates the need for customers to speak with service agents. This not only improves customer satisfaction by speeding up resolution time, but also expands the organization’s reach by going beyond traditional communication channels.
Human agents can also leverage AI-powered voice assistants to translate conversations during live service interactions, so they can speak to customers without mastering their language. This means that by 2025, human empathy and experience handling complex customer challenges will be the skills that matter most for service agents, not the number of languages they speak. As their GenAI use cases mature in this area, organizations will drive customer experience to the next level by streamlining workflows and dramatically reducing case resolution times.
Generating value with AI
GenAI has enormous potential to transform business processes, but organizations urgently need to move beyond the experimentation phase to take advantage of this opportunity. As tangible use cases continue to emerge, organizations must have clear customer-centric goals and a well-defined roadmap to ensure they integrate these technologies in a way that creates value. With this more considered approach, they will be much better prepared to reap the benefits of GenAI and deliver market-leading innovation.
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