How AI is Transforming Support Centers for Maximum Efficiency and Impact

There’s no doubt that AI can be pivotal in support center experiences for customers and agents. Over two-thirds of customer experience (CX) organizations agree AI can make interactions more efficient and friendly, according to a Zendesk CX Report. The challenge is finding the right path from the hype of possibilities and potential outcomes to the reality of practical implementation and use focused on those outcomes.

That means thoughtful implementation that balances efficiency with personalization and automation with human interaction. By first looking at the possibilities of AI and automation in support centers and correlating that with the challenges, organizations can realize significant practical improvements in customer satisfaction and operational efficiency.

The AI/Automation Advantage for Modern Support Centers

The most common, forward-thinking uses for AI in support centers focus on interconnected approaches to operational and interaction improvements for agents and customers. While RPA and interactive voice response (IVR) are the common vehicles for these improvements, the engine driving them has multiple moving parts.

Robotic Proces Automation (RPA) and IVR

Most organizations see RPA as the ultimate efficiency booster where software “bots” handle repetitive, rule-based tasks usually done by humans. Integrating AI with RPA can support complex tasks like decision making and language processing to make agents more efficient, lower call volumes and increase CX through faster resolution.

The Role of ASR, NLP & Conversational AI

IVR has evolved to intelligent IVR for call interactions where automatic speech recognition (ASR) and natural language processing (NLP) enable machines to understand spoken commands and process human language. The addition of conversational AI helps IVR and RPA bots to interact in a human-like manner, while predictive analytics can assess call data and match it to CRM data to enable agents, bots, or IVR systems to provide personalized CX.

How Integration Paths Deliver Greater Operational & CX Efficiencies 

Organizations can integrate these tools with other support center tools for data access and intelligent decisions, ranging from CRMs to appointment scheduling systems, workforce management applications, and payment processing systems. The benefits of AI and automation-driven tool integration into the support center can include:

• Predictive call routing to deliver the right call to the right agent at the right time
• Increased self-service options
• Better CX
• Faster time to resolution (TTR)
• Maximized agent operational efficiency and productivity
• Cost savings and increased scalability
• Increased security and regulatory compliance (improved fraud detection, authentication, and data privacy protection)
• Customer insight data sharing (CRM Integration) with agents to deliver personalized solutions based on individual customer needs and profiles
• Interaction evaluations to gain insights on support center and agent performance for training and support
• Omni-channel customer support across digital channels (improved TTR, call volume, agent productivity, customer insights and personalized CX/services)
• Increased agent support through content and knowledge base access for answers during customer interactions
• Language detection to deliver answers in each customer’s preferred language

Organizations that use third-party solutions don’t need deeper knowledge of AI in terms of large language model data sets, training, and application development. There are many AI/automation-based support center platforms and solutions available that use third-party models.

Although building solutions in-house is a more complex and costly approach, buying has similar risks and challenges (errors, hallucinations, biases) depending on use case. How enterprises decide on those different approaches can be complex, which starts with separating the practical reality from the non-specific hype of these solutions.

Key Challenges in practiacl AI for Support Center Optimization

Businesses have a large and growing list of support center tools to choose from, which requires having a clear vision for use cases, implementation, and outcomes via a defined process. Most organizations lack the defined growth path of developing a support center and overall workforce capable of meeting modern digital workforce demands. This can mean IT personnel with skills in data science, engineering, DevOps and more, which goes beyond the support center.

Balancing Human/Machine Interaction for Max Efficiency & CX

Human interaction that provides empathy and connection is still a vital part of chatbot and virtual assistant use/encounters even with advances in the technologies. Nearly half (46%) of respondents prefer human interaction with support centers but are comfortable with AI use in the background, according to a recent Cogito study. Keeping human agents in the loop is imperative to minimize risk regardless of the use of custom or third-party vendor AI/automation-driven applications, platforms, and tools.

Balancing Costs with Business Outcomes

Reducing the cost implications of AI requires the use of innovative approaches to solutions, training implementation and an overall Center of Excellence (COE) foundation. This enables cost effective implementation of Chatbots and IVR based on business cultures that embrace the realities of low code/no code solutions and developer support.

Tech stack needs for support center AI/automation implementation

Implementing AI systems, platforms and technologies that can significantly resolve complex issues is complicated. Organizations need to think about the level of tech stack sophistication they possess and how it interacts with AI/automation-driven support center applications, tools and platforms, such as:

• App development processes
• Cloud computing
• Integration across data, application, networking, and telephony systems

While these are common aspects of broader digital transformation, they are integral to AI and automation implementation for the support center.

The Role of an Expert partner in Tackling AI Support Center Challenges

Organizations measure AI/automation support center integration success in terms of execution, implementation, ROI, and business outcomes. Even incremental and pilot projects are part of a broader strategy that unfolds across time, budgets and the broader enterprise.

With so many people along with technology, process, and workflow moving parts, organizations can benefit from a partner that can provide end-to-end support. This only starts with deep experience in AI/automation, support services and developing/implementing a COE to give the business a firm foundation for support center success.

As simpler tasks become automated, support centers may need to increase their access to agents capable of handling complex interactions. AI integration with CRM and product knowledge databases is increasing agent expertise and support speed with 61% of respondents saying this will happen more often over the next three years, according to another Zendesk study.

Others may prefer to hand off support center services to third- party providers with skilled agents that have already implemented these technologies. This gives the business the time to scale up while planning strategies for internal AI and automation support systems in an affordable way.

Solugenix as Your AI/automation Support Center Partner

Successful implementation of AI/automation that optimizes the support center requires a highly integrated strategy. This is much easier when working with a single partner like Solugenix that can work with each organization on:

• All aspects of support center services (people, processes, expertise and technology)
• The digital transformation strategy that gives it its foundation

One goal of Solugenix is to help businesses lay the foundation for practical approaches to AI in the support center and improving its lifecycle ROI, business, brand and bottom-line outcomes. You can see how Solugenix has done this through case studies showing real-world approaches to support center CX improvements. Then there are deeper dives into AI/Automation support center transformations blogs that help further the understanding of real-world possibilities in the support center.

The key is having a long-range plan and starting with relatively simple use cases that deliver high value and ROI. This enables organizations in partnership with Solugenix to vet solutions and providers to see what works and what doesn’t based on specific needs and use cases. That’s one reason Solugenix offers a free RPA proof of concept.

Although it seems like AI and automation implementations are common, deriving defined benefits and ROI is less common. Developing the right strategy with incremental implementation and proof of outcome steps with a partner that can support all aspects is the best way to realize the potential you envision and begin harnessing the potential of AI in the support center.

To learn how Solugenix can partner with you in optimizing your support center with AI for practical outcomes, visit our key services page to see everything we can do.