Harnessing the Power of Generative AI: Unlocking Value in Customer Service and Enterprise Workflows
By Claudio Rodrigues, Chief Product Officer at Omilia
Generative AI (GenAI) has rapidly moved from being a futuristic concept to a core component of business strategies across industries. As companies increasingly embrace AI technologies to stay competitive, the true differentiator lies in how they leverage these models. The power of GenAI isn’t just in its ability to process information, but in how effectively it integrates with proprietary business data to deliver meaningful value, particularly in areas like customer service and enterprise workflows.
While nearly 94% of organizations are exploring or expanding their use of GenAI, according to recent IDC data, simply adopting AI solutions isn’t enough. What separates leaders from followers is their ability to harness the full potential of proprietary data—data unique to their organization that reflects its specialized knowledge, processes, and customer interactions. In today’s AI-driven world, the edge doesn’t come from using off-the-shelf models based on publicly available data, but from training these models on internal, business-specific datasets. This allows companies to deliver more personalized, efficient, and impactful results.
Take the example of a customer service center. An AI-powered chatbot is useful, but when integrated with historical customer data, it becomes a powerful tool for anticipating customer needs and offering personalized solutions, leading to better outcomes for both the business and the customer. In this sense, organizations that strategically leverage their own data alongside AI technologies will be able to create lasting competitive advantages, setting them apart from others using generic solutions.
Ensuring Data Readiness and Security
However, unlocking the true power of GenAI requires more than just integration; it demands that businesses ensure data readiness. The best AI models in the world will falter if they’re fed poor-quality data. In fact, only 24% of businesses currently feel they are fully prepared in terms of data organization and readiness. Outdated or unstructured data can lead to flawed AI outputs, hindering decision-making and customer satisfaction. To avoid this, organizations must take stock of their data—cleaning, structuring, and categorizing it properly so that AI models can process and generate reliable insights.
Security is equally crucial. As companies deploy AI solutions, they face new challenges around data security and privacy risks, such as IP leakage and AI hallucinations—situations where AI generates false or misleading information. To prevent these outcomes, businesses must implement robust data governance frameworks. Establishing guardrails around AI models, monitoring outputs, and ensuring only the most relevant and secure data is used are key steps in mitigating these risks. Secure data flow gives businesses greater confidence in the accuracy and relevance of their AI models, helping maintain both customer trust and internal security.
Driving ROI in Customer Service and Enterprise Workflows
Once the data is secure and ready, the potential for Generative AI to deliver real return on investment (ROI) becomes clear. In customer service, AI has been a game changer. GenAI is transforming self-service solutions for customers. AI-powered chatbots and virtual assistants allow customers to resolve issues on their own, whether it’s resetting passwords, troubleshooting product problems, or checking account balances. These solutions enable businesses to scale their customer support efforts while maintaining high levels of customer satisfaction, without the need for additional human agents. In doing so, companies can lower operational costs while providing round-the-clock support.
By implementing GenAI-powered agent assist tools, businesses can better support and empower their agents. AI automatically generates post-call summaries, provides real-time suggestions for resolving issues, and even predicts what a customer might need next based on past interactions. These tools also help reduce agent training time by providing instant access to knowledge, ensure higher compliance with company policies and processes, and boost agent confidence during live interactions. Together, these improvements not only reduce the time it takes to resolve customer inquiries but also enhance the customer experience, leading to higher satisfaction rates and, ultimately, increased loyalty.
Internally, GenAI’s impact on enterprise workflows is equally profound. For instance, AI-powered employee self-service tools are now streamlining HR and IT processes, allowing employees to find answers to routine questions, troubleshoot IT issues, or navigate onboarding without relying on dedicated HR or IT personnel. This not only improves productivity but also allows internal teams to focus on more complex tasks that drive the business forward.
Preparing for AI at Scale: Bridging the Data Gap
As businesses scale their AI efforts, they must also bridge the data gap—ensuring that the data feeding AI models is fresh, categorized, and accurate. This is where many companies fall short. Without proper data governance, even the most advanced AI systems will deliver suboptimal results, ultimately limiting the ROI they can generate. Regular data audits, investment in data quality management tools, and the establishment of clear data governance policies are critical steps to ensure that GenAI delivers its full potential.
Furthermore, choosing the right AI partner is key to long-term success. Not all AI models are suitable for every use case, and selecting a partner with a deep understanding of the industry can make the difference between a successful implementation and wasted resources. For customer service, this means identifying AI solutions that can pull together multiple data sources - voice, chat, social media- into one platform, providing a holistic view of the customer and enhancing service personalization.
Unlocking Long-Term Value with GenAI
The future of AI is here, but realizing its full potential requires more than just deploying the latest technology. Success with Generative AI is rooted in data readiness, security, and targeted use cases that drive meaningful ROI. Businesses that take a strategic, thoughtful approach—one that integrates proprietary data, ensures security, and scales AI across critical workflows—will unlock new levels of efficiency, personalization, and customer satisfaction.
As AI continues to evolve, those who invest today in the right strategies and partnerships will be well-positioned to lead their industries tomorrow.