Transitioning to the Walk Phase - Deploying AI for Specific Use Cases

In the journey of deploying AI into your CX workflow, the "walk" phase is where you start to gain traction and see tangible results. At this stage, you've already laid the groundwork, gained buy-in from stakeholders, and set clear goals. Now, it's time to roll up your sleeves and put AI to work in specific use cases.

Gaining stakeholder buy-in: Multiple stories for different audiences

Before diving into the "walk" phase, it's crucial to maintain the support of your stakeholders. As you venture into AI deployment, remember that different stakeholders have varying interests and concerns. 

Craft compelling stories tailored to different audiences to ensure continued buy-in:

• For Executives: Emphasize the potential ROI, revenue growth, and strategic advantages of AI adoption. Show how it aligns with the organization's broader goals.  

• For Frontline Staff: Highlight how AI can simplify their tasks, reduce workload, and enhance customer interactions, making their jobs more efficient and satisfying. Communicate they will be on the front lines of leveraging cutting edge technology and investment in their human skills.

• For IT Teams: Address technical aspects, such as infrastructure requirements and data security measures. Assure them that AI integration will not disrupt existing systems.
• ‍For Legal and Compliance Teams: Take a proactive approach with them to build confidence and trust for your projects.

Deploying AI for specific use cases

Setting clear goals: Gaining momentum and establishing permission

In the "walk" phase, focus on specific, limited use cases. The goal is to show clear successes and build momentum, so that you'll gain permission to expand AI initiatives further. Define clear objectives that align with your organization's overarching strategy. These objectives should be simple, achievable, and measurable, and should have a significant impact on important workflows within your business. Link to Business Impact Document

Building confidence: Demonstrating incrementally

To maintain stakeholder confidence, start with projects that showcase AI's incremental value. Choose use cases where AI can make a noticeable difference without causing disruption. Demonstrating clear improvements in efficiency, customer satisfaction (CSAT), or revenue can be a powerful way to build trust in AI's capabilities.

Managing Scope: One workflow at a time

To avoid overwhelming your team and resources, focus on one workflow or process at a time. Whether it's automating a specific task or assisting agents in a particular aspect of their work, concentrate on the one thing that matters most. This laser focus allows you to achieve excellence in that area.

Reskill/Upskill to fulfill the promise of the story

Just like in the crawl phase, as you deploy AI for specific use cases, invest in reskilling and upskilling your team. Ensure they have the necessary skills to work effectively with AI technologies. This commitment not only fulfills the promises made in your stories but also empowers your team to adapt to the evolving CX landscape.  

Gaining momentum for the next project permission for the next momentum

Each successful use case in the "walk" phase should be viewed as a stepping stone to the next. Earning permission to expand AI initiatives requires delivering on your initial promises. As you gain more traction and demonstrate value, stakeholders are likely to grant permission for broader AI integration.

Examples of CX workflows/processes to experiment with

As you embark on the "walk" phase, consider these examples of CX workflows and processes to experiment with AI:

Self-service automation. Implement AI-driven interfaces to automate customer inquiries and actions, reducing the workload on your support teams. Some common examples of these include:

• Chatbots: while chatbots have been around for years, Generative AI is unlocking new abilities that make them far more effective at helping customers self-serve.
• Intelligent interactive voice recognition (IVR) systems: these smart voice trees make it possible to reduce call volume while improving the experience for customers. 

Automation to assist agents. There are a number of ways AI can easily assist your support agents:

• Executing post-interaction processes: At the conclusion of many customer interactions, an action is often taken to execute a process that takes place outside of your support team’s primary tools. Action automation should be your priority as it is the driver of your business and the priority of your customer.  ‍
• Suggested responses: Equip your customer support agents with AI tools that provide real-time insights and suggested responses,enhancing their ability to navigate through customer conversations of all kinds.

Metrics you can improve with AI

Deploying AI in your CX workflow should yield measurable improvements in various key performance indicators, including:

• Customer Satisfaction (CSAT): AI can lead to more personalized and efficient interactions, resulting in higher CSAT scores.
• Average Handling Time (AHT): By automating certain tasks and streamlining processes, AHT can decrease, allowing for quicker issue resolution.
• First-Contact Resolution (FCR): AI-driven insights and assistance can enable agents to resolve issues on the first contact more frequently.
• Automation Share: Measure the percentage of tasks or processes that AI successfully automates, reducing manual efforts.
• Self-Service Share: Track the increase in customer engagement with self-service options, which can reduce support ticket volume and costs.

In the "walk" phase, your journey with AI becomes more tangible and the benefits more apparent. By carefully selecting use cases, managing scope, and delivering incremental value, you'll pave the way for even more significant AI transformations in your CX strategies during the "run" phase.

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