The majority of industry experts claim that AI in general is the biggest opportunity in CX since decades, and that’s probably true. But as with every opportunity, there are risks associated with it. Those risks aren't broadly discussed, hence I've summarized the main approaches to ensure AI solutions will deliver desired results when being deployed. The following approaches are based on several observations and although some may appear obvious, other risks require a thoughtful approch to be minimized and avoided. That said, what and why should organizations prioritize when planning to deploy AI?
The following 7 approaches around process and performance will help organizations deploy AI more effectively when implementing #AI solutions in #CX:
- AI is not a one size fits all strategy. Before implementing AI, organizations should have a solid customer-centric foundation, which involves understanding customer needs, expectations, and preferences. AI solutions should align with customer-centric goals and enhance the overall customer experience rather than replacing human interactions without proper consideration. Organizations should comprehensively understand their service journeys, pain points, and opportunities for enhancement. This proactive approach allows for the strategic utilization of AI to address bottlenecks and improve overall performance.
- Define whether your organization wants AI to handle customers autonomously or support humans in handling customers. There are several AI solutions available to help in support functions such as recruitment, training, quality management and agent assistance rather than front-facing automation to replace human interactions. However, both approaches are important for maintaining customer satisfaction, loyalty, cost control and building strong relationships while fostering a positive brand image.
- AI can be effective in streamlining processes and improving operational efficiency. However, organizations should have well-defined processes in place before integrating AI. Implementing AI without streamlined processes can lead to inefficiencies or automation of inefficient processes, which will not yield the desired results.
- AI implementations often require employee training and upskilling to work effectively with AI systems. Organizations need to prioritize training and readiness programs to ensure that employees understand how AI works, how to leverage its capabilities, and how to provide seamless customer experiences alongside AI systems. This includes the measurement of the effectiveness of the AI solution and the satisfaction from a customer perspective. That may involve different KPI approaches as well.
- Organizations should assess their existing technology infrastructure and systems to ensure smooth integration with AI solutions. Evaluating compatibility, scalability, and potential dependencies before implementing AI allows seamless integration and avoids disruptions in existing processes. If you are currently having a large number of various CRM systems, harmonization may take more efforts and costs to achieve the desired benefits.
- AI relies heavily on data to drive insights and decision-making. Organizations need to ensure that they have access to accurate, relevant, and high-quality data. Prioritizing data management and governance practices will help organizations leverage AI effectively and derive meaningful insights from their data. This will also help maintain AI a long term solution considering changes in business and processes.
- Management and ownership of the AI and technology solution, especially if your CX operations involve outsourcing to vendors. If your vendors own the major parts of the solution, you may be facing limited options to change your contract and/or strategy at a later point. The Ownership Strategy needs to allow for appropriate flexibility, which should be addressed in the supplier selection process ahead of the AI deployment itself.
The above steps allow organizations to set a strong foundation for success by aligning AI initiatives with their specific needs, ensure data readiness, provide adequate employee training, and maintain a customer-centric approach throughout the implementation process. A strong foundation increases the likelihood of achieving desired outcomes and delivering enhanced customer experiences with AI technologies, rather than purely reducing costs whilst scarifying customer experiences and consequently loyalty. AI requires long term management approaches to ensure it becomes, and continues to stay effective.
