By Dvir Hoffman, CEO at CommBox. How to get started with AI in 5 simple steps
Things we knew in 2023: Leveraging AI greatly increases the operational efficiency of your business – impacting everything from customer satisfaction to cost savings..
The challenge in 2024? Businesses of all sizes and across all industries need to find the best way to integrate AI technology into their daily business operations. The biggest deterrent of AI is no longer a commitment to innovation, but rather strategic planning – or more accurately – knowing how to get started.
Here’s what I have learned as a past CPO and current CEO of one of the leading AI-based customer service and engagement solutions in our market to be the foolproof step-by-step journey your business needs to take in order to effectively and easily implement AI.
Identify your top 3 business needs
Forget about AI as a grander concept, and reverse engineer your AI strategy. Ask yourself the basic questions like what existing procedures and processes are in place that need improvement? Where can we streamline processes or contribute value for both your customers and internal teams?
If you want to see radical results quickly, pinpoint the top three tasks or processes that are repetitive and time-intensive, such as information distribution for the most popular inquiries. To check if you are focusing on the right ones, determine if automating these use cases will impact the bottom line in the following ways:
- Support more volume
- Improve service level & customer experience
- Initiate a new service
- Increase cost savings
The answer is often hidden in cost structures, budgets or roadmaps. For example, if your business is always under pressure to add more manpower/agents to meet volume or spend time and resources on training agents to go to market with a new product, then you have uncovered your starting point for AI.
By aligning your business objectives with the potential advantages of AI, you can strategically plan for a successful implementation – that will provide an almost immediate ROI.
Build your AI model with quality data
AI is diverse, and how you use it—choosing the underlying technology, the data it relies on, and integrating it into your daily work—affects how well it performs and if it can personalize customer experiences. It’s not a one-size-fits-all solution and the success of AI relies on these choices.
The pitfalls of business adopting a generic LLM – open AI, Bard, Generative AI – or any technology that can digest large amounts of structured and unstructured data and start answering based on that model is that this data needs to be fine tuned to your specific business.
Choose a solution that allows you to customize the scope of knowledge of your AI model. In only some instances do you want the entire scope of the AI world, in most businesses it is critical to reign in the AI scope of information that can be used in your organization.
This way, you can quickly leverage all your organization’s existing organizational assets (PDFs, website, support articles, FAQs etc. and the AI will respond in full alignment with your organization’s business policies, security and compliance.
Select the right AI offering with this product capability checklist
A judicious choice of the customer service platform that provides the underlying AI technology ensures that your solution aligns seamlessly with your businesses specific needs and goals. Selecting the right technology is an essential step in harnessing the full potential of AI solutions. Here is a solid checklist that includes the foundational features and capabilities needed:
- Seamless integration with internal business systems, like your CRM, KMS
- AI model and technology agnostic – utilize AI engine of your choice – but also customize
- Works on all digital channels with strong self-service offering
- Level of customization of AI solution and automation/bot building
- Diverse industry expertise in framing bots for real-world use cases
Measure the right KPIs using the right data
Concrete challenges are always linked to higher business problems. For example, if you discover that your agents spend a lot of time on administration after a call, that is directly linked to lower efficiency and higher costs; In that scenario, the best KPI to measure is ”time spent by agent” scores. Or, if your business needs to improve quality of engagement (as opposed to volume) with better soft skills, service level and access to up-to-date knowledge, then measuring CSAT is the correct KPI.
Outline the required data sets, including the method for acquiring each specific type of data. This will allow you to create meaningful real-time data analytics and insights that can proactively address challenges, refine algorithms, and fine-tune AI models to align with evolving customer needs.
This proactive approach not only safeguards against potential issues but also paves the way for continuous improvement, allowing customer service industries to deliver a responsive AI-powered experience.
Start small with a scalable approach
Choose a customer service solution that doesn’t require a massive technology turnover implemented across every department with a steep learning curve. Enhance, don’t replace your CRM with an adaptable solution that doesn’t require drastic system changes. Sophisticated customer service solutions have technology so neat and flexible that your business can start small with, for example, just your customer support’s specific scheduling team.
Only after you experience the benefits of leveraging AI in customer service for that specific team, expand your AI integration to the entire customer support department. From there, you can choose to take on more use cases and more departments – from lead qualification for your sales teams, to IT, HR and finance teams.
A pilot project will also allow you to gather feedback from employees and customers to ensure that the AI solution meets their needs and expectations. If the pilot project is successful, you can proceed with the full implementation of the customer service AI solution across your organization.
2024 Marks the Rise of Autonomous Agents
Autonomous agents are bots or automations that can handle end-to-end use cases without requiring human assistance. In order to truly be autonomous, these AI bots need to have the ability to authenticate, personalize using seamless integration to a CR and other internal business systems, update information in the back-end, and, of course, access the information needed to answer questions and resolve inquiries. The last part typically involves rich AI capabilities. These autonomous agents will become the backbone of enterprises and serve as huge cost sayings.
Once many of these bots are established, your business can start transforming into what we call an Autonomous Enterprise – an AI-driven master script for autonomous communication, with multiple bots and automations running different aspects of a company such as their support operations. Of course, humans should always be in the loop not just as managers overlooking the performance of these autonomous agents, but have the ability to jump into conversations that require human touch. Still, once an autonomous enterprise is established, organizations will experience operational efficiency as they have never seen before.
Learn more about how you can leverage AI in your customer service.
