AI Business Case: Understanding What AI Can Do for You

Five years ago, automation was touted as a revolution that would free humans from many manual tasks. That prompted a lot of new product development and ideas about how to use it, especially to reduce costs. Artificial intelligence (AI) offers even more promise as a revolutionary technology that can automate both simple and complex tasks.   

Think about all the manual tasks contact centre agents perform. In healthcare, for example, staff still must fill out input forms for patients. It’s very likely that a bot could handle that task before the caller engages with an agent. These types of efficiencies and productivity improvements are becoming common across all industries. Any manual task that’s done today has the potential to be automated.   

And bots will probably do a better job than a human; they’re faster and more accurate. This is the promise of generative AI because it builds those efficiencies into business models.  

All the options available today for AI can feel overwhelming. It can be difficult for busy business leaders to decide which step to take first. It’s critical to spend enough time up front building your understanding of what AI offers.  

The most robust customer experience (CX) platforms offer AI in various ways. AI should be embedded into the platform and it should be used by applications, such as predictive routing and agent-assist capabilities. These features give you the power and flexibility to support multiple use cases that meet your unique business goals and create positive customer experiences.  

Identify Highly Redundant Manual Tasks  

Most businesses already have a sense of which manual tasks are good candidates to automate. They understand how doing so could drive ROI beyond time savings to efficiency improvements, as well.   

Before you begin developing an AI business case, it’s essential to be grounded in practical application and use. Operational cost savings can be your anchor point, such as when you’re automating the manual tasks that agents no longer have to perform. Here are a few common AI use cases, by industry, that eliminate manual tasks and more:  

  • Healthcare providers reduce the use of manual processes, such as accessing patient health records. AI enables managers to make decisions based on insights using data they didn’t have access to before, including real-time occupancy rates, sentiment analysis and call transcriptions.  
  • Insurance providers can eliminate errors in manual rate calculations or payments, and they can make it easier to process claims and appraisals. Using intelligent automation also helps them adhere to compliance regulations more easily.  
  • Retailers gather customer data and analyse it automatically in real time to provide highly personalised online shopping experiences. It improves customer satisfaction and AI technology is used to plan more effective marketing campaigns.  
  • Financial services organisations are building more robust self-service capabilities using AI to handle common customer queries. This enables agents to manage more high-value, time-critical phone calls and complete them faster.  

The quality of customer service also improves. By surfacing the right information when needed, agents can answer questions based on recommended next-best actions to take instead of searching through multiple databases for the right responses. This also reduces call transfers to another agent.  

AI can easily automate many other manual tasks, including data entry and analysis, employee onboarding, and call routing before a customer even gets to an agent.  

Use the ROI of AI as a Differentiator  

Once you’ve chosen specific use cases that will drive savings or productivity, you can apply that information to differentiate your business in the marketplace.  

When evaluating AI solutions, businesses often begin by focusing on operational cost savings. That’s because they are familiar with how to measure costs. In contact centres, that might mean evaluating the productivity of agents through the cost savings in reducing average handle time, for example.  

But don’t forget that “value” is a major differentiator that encompasses more than just saving costs. It’s also the way you engage with customers and prove you value their time.    

An AI business case that includes a revenue or conversion rate improvement is a much bigger proposal. It requires a “marketing angle” that looks beyond the contact centre to compare estimated benefits with estimated costs.  

This approach gives you an opportunity to show how you can differentiate your business for the long-term and grow your footprint against your own competition. You’ll win with internal stakeholders when you formalise how you’ll differentiate your business and extend customer lifetime value.     

Quantifying the transformative potential of AI isn’t easy. But showing how much you’ll increase customer satisfaction through AI-powered self-service is a critical metric.   

The secondary costs of AI are also difficult to estimate; you might not need agents with certain skills anymore, but others will become critical. Timelines also vary considerably; some you’ll achieve immediately while others can take months.  

Vendor benefit calculators can be valuable tools for customers to estimate revenue gains and show gains in conversion rates — as well identify any hidden costs that can slip through traditional analytics.   

Simplifying Risk Mitigation  

The advantages of AI are clear and well-documented. Yet, the details vary along with the hidden costs and uncertainty because of having many options to choose from.   

Mitigating risk is much easier when you understand the big differentiators first. These will save you time and money.    

  • Embedded Integrations  

Most businesses use Salesforce or other CRM systems, and they need and expect assistance with integration. An embedded integration gives you out-of-the-box capabilities that take the burden off IT.   

Integration is simple to set up, manage and maintain. This makes it easy to adapt as your requirements change and easy extension to other applications. And it reduces the risks and delays associated with multiple vendors.   

Once deployed, it eliminates the time spent changing from one application to another during an interaction, which often frustrates customers and puts agents in a tough spot.  

  • Certified Use Cases  

As with any innovative technology, hidden costs can create risks. These risks might include time required for training and upskilling staff that slow down your time to market – chipping away at revenue goals. Starting with more certainty eliminates risks and reduces the burden on your current staff who also might be new to deploying AI use cases     

You might have a unique use case that isn’t supported in your CX platform, or you want to test it with a free tool. Having a technology vendor with tested, certified and integrated partners can fill those gaps. Certified use cases relieve your business of that task. These partners should include other strategic vendors who can easily integrate into your new CX platform and most new AI tools.   

  • Off-the-Shelf Applications  

No business has unlimited resources. Save those resources for areas where your highly skilled employees are most needed. When you move to an AI platform, look for pre-built applications that are proven and use cases that matter most to your business.   

Together with third-party partners and integrators, or other marketplace of your choice, having industry-leading applications minimises risk in your move to AI and gets you to market quickly.  

When that process is simplified and apps are easy to use, you not only save time and associated costs, but you also address the concerns of stakeholders whose teams are expected to make use of innovative technology. Making new tools simple makes good business sense.   

The Power of Data on a Single Platform     

One of the primary advantages of an AI-powered experience orchestration platform is that it enables businesses to use their data for delivering better customer experiences. That data is a lot easier to manage and maintain when you access it from a single platform. This simplicity impacts many stakeholders.  

It gives employees easy access to the knowledge they need to better serve customers. It gives customers faster and more accurate responses to their queries and journeys to purchase products and services. And it simplifies the work that IT performs, as skills development is greatly reduced because the platform is based on low code or no code.  

This speaks to the need to focus on value: Moving to AI will give your business much more than just saving agent time as they engage with customers.      

Laying AI Groundwork with an Eye to the Future   

As you prepare to dive into an AI-powered platform, reducing risk is best served through an understanding of value. By taking a conservative approach, you can still deliver net benefits in a short amount of time – even though ROI varies tremendously by business.   

During your AI journey, remember to keep the long-term big picture in mind while grounding your plans in practicality and value creation. With a strategic approach and a commitment to innovation, the possibilities of AI are limitless now and in the future. To learn more, read “How to build your business case for AI” and learn where to focus your AI efforts to achieve results and continue on your CX transformation.