Is your contact center ready for artificial intelligence (AI)? With AI having so much potential when it comes to transformation, there is a lot to consider as the stakes are high. AI is not a point solution, so implementing it into your contact center is more about the overall puzzle than the individual pieces.

As the first in a two-part series, we are exploring the key questions contact center leaders should address when planning to implement AI in contact centers. AI is in a constant state of evolution and can address many of the challenges that contact centers face, like agent onboarding and training.

Question 1: What is the status of your transformation plans?

The starting point for any long-term AI deployment plan is to have a detailed understanding of where your contact center is in your transformation journey. Then, you can evaluate where AI fits in with your contact center strategy. As a transformation tool, adopting AI solutions and blending it with human agents can provide opportunities to reduce costs, improve efficiency, enhance the agent experience, or provide a better customer experience.

As you’re considering your transformation plans, it’s also important to pinpoint any technology barriers to adopting AI in your contact center. Is your current contact center prepared for AI, and how prepared is it? Do you require an AI solution for your on-premise or cloud contact center? Are there limitations in your technology that will create silos and complexity?

Question 2: Who is driving your AI journey?

AI deployments will happen across the organization, not just in the contact center. Your AI roadmap will need to align with the rest of the organization, especially as you shift your focus from customer service to the agent and customer experience. This is when AI orchestration capabilities become more critical.

With AI, contact center leaders will have to make technology decisions alongside the rest of the organization. Since AI touches all aspects of the business, contact center leaders need to ensure that their plans are on course with other AI deployment plans the business may have. Decisions may need to be made jointly with executive leaders who will have their own agenda and expectations for AI.

Question 3: Why are you adopting AI?

Whether contact center leaders are the sole driver or one of many for their AI journey, there must be consistency in the rationale. There are many valid reasons for adopting AI in and outside the contact center. According to Forbes, 56% of businesses are deploying AI for customer service, which is inline with the contact center’s focus. However, another 51% are using AI for cybersecurity and fraud management. Others are using AI for customer relationship management (46%), digital personal assistants (47%), inventory management (40%), and content production (35%).

A leading driver for AI in contact centers is automation, making this a good starting point. However, since it can take many forms, you need to be specific about what is being automated.

For an initial AI deployment, aside from needing to be clearly defined, the rationale should be simple. To minimize risk, initial deployments should address basic routine tasks that an AI application can handle with a high degree of success. Then, build the rationale around use cases, where the deployment focuses on a specific problem or challenge with a specific desired outcome.

This could be customer-facing, but the safer route would be an operational use case such as automating a workflow between agents and supervisors, or an agent-specific task like automating conversation summaries. Be as specific as possible as the purpose and benefit will be easier for everyone to understand.

While contact center leaders need a clear rationale for their own planning purposes, the same applies to agents and supervisors since they will be the ones using these new applications. If the rationale resonates with them, adoption will be much easier.

Ultimately, there must be trust with AI – including with your customers. Your motivating rationale needs to be reflected for everyone across the value chain. Since AI touches everything and everyone, the rationale must be carefully considered and not be an afterthought or a hasty response to a top-down decree to implement AI.