The integration and role of artificial intelligence into workforce engagement management solutions has become a key focus for many contact centres. Over the past decade, AI has been both a buzzword and a beacon of hope, promising efficiency gains and improved customer experiences. Yet, as our recent State of the Contact Centre research reveals, the journey with AI in WEM is not without its complexities. In this blog post, we’ll highlight the current role of AI in WEM and what your contact centre should be doing to stay ahead of the curve.

While contact centre managers are keenly aware of the potential benefits AI can bring, they also recognise its limitations. Our recent State of the Contact Centre research highlights that contact centre managers see plenty upside to AI, but also recognise limitations—including its ability to track and address mental health (29%), identify a need for training (27%), and predict customer actions and behaviours (27%). So, what are the benefits that AI can deliver to WEM specifically?

1. Efficiency: AI algorithms can analyse vast amounts of data quickly and accurately, enabling more efficient workforce scheduling, forecasting, and optimisation. This efficiency leads to cost savings and improved productivity.
2. Personalisation: AI-powered WEM solutions can tailor schedules, training, and feedback to individual employee preferences and strengths, leading to higher levels of engagement and satisfaction.
3. Predictive Analytics: By analysing historical data and real-time inputs, AI can predict future workforce needs, helping organisations proactively address issues such as understaffing or overstaffing.
4. Continuous Improvement: AI can identify patterns and trends in workforce behaviour and performance, enabling organisations to continuously refine their strategies for employee engagement, training, and retention.
5. Automation: AI can automate repetitive tasks such as scheduling, time tracking, and performance monitoring, freeing up managers to focus on more strategic aspects of workforce management.
6. Adaptability: AI algorithms can adapt to changing business conditions and employee preferences, ensuring that workforce management strategies remain effective over time.

Overall, AI can enhance the effectiveness and agility of Workforce Engagement Management solutions, leading to better employee experiences, higher productivity, and improved business outcomes. But what may surprise many is that these are not future, potential benefits offered by AI in WEM. In fact, the AI journey has likely already begun at many contact centres. Today’s leading WEM solutions are leveraging AI tools across various functions, from workforce management and quality management to interaction analytics and beyond. These tools, such as AI forecasting, intraday automation, and WEM bots, represent the groundwork for a more intelligent and efficient contact centre ecosystem.

The high-level benefits AI-driven workforce engagement management offers are plain to see. But how exactly are the best WEM solutions delivering these improvements? Let’s delve deeper into these transformative tools:

WFM:

• AI forecasting: Uses historical data, real-time info, and advanced algorithms to predict workforce needs accurately, optimising scheduling and staffing.
• Intraday Automation: Dynamically adjusts staffing levels and schedules in real-time based on changing demand patterns, enhancing operational efficiency.
• WEM Bots: AI-driven chatbots automate workforce engagement tasks like scheduling and time-off requests, improving accessibility and reducing admin overhead.

Quality Management & Analytics:

• Interaction Analytics: AI-powered speech and text analysis evaluates customer interactions for sentiment and trends, improving agent performance and satisfaction.
• Predictive Quality Scores: AI predicts the quality of customer interactions in real-time, prioritising coaching and training efforts.
• Predictive NPS: AI forecasts customer sentiment and likelihood to recommend, identifying potential promoters and detractors.
• Automated Quality: AI assesses customer interactions automatically, enhancing efficiency and consistency in quality management.
• Phrase Optimisation: AI identifies and optimises effective language used by agents, enhancing customer satisfaction.

Contact Summarisation:

• AI-powered algorithms analyse and condense customer interactions into concise summaries, extracting key insights efficiently.

In the pursuit of optimising customer experiences, contact centres must tread carefully, balancing self-service with the risks of customer churn due to poor experiences.

To truly harness the potential of AI in WEM, organisations must adopt a proactive approach to monitoring and refining AI systems. Whether it’s fine-tuning bot configurations or tracking NLU performance over time, the key lies in iterative refinement and adaptation. By learning from past mistakes and embracing proven use cases, contact centres can chart a course towards AI-driven excellence.

The future of AI in WEM hinges not only on technological advancements but also on ethical considerations and human-centric design. By augmenting agents’ capabilities rather than replacing them outright, AI can become a catalyst for positive change in the contact centre industry. As we navigate this evolving landscape, let us remain vigilant, mindful, and forward-thinking in our approach to AI.

To find out more about how Calabrio can help you on your WEM AI journey, book a custom demo today.