by Tony Palladino
I am constantly learning more and more about the role of AI in our business world. Recently, I was working with a client in a session focused on various use cases to leverage AI as it relates to their product offering and their website for an enhanced customer experience (CX).
The Front-end
On the “front-end” website, an AI-bot or avatar can be created as a character to interact with users or customers coming to their website. You can picture a happy puppy dog wagging its tail, willing to go fetch whatever it is you need, on the spot. Of course, the puppy dog will have the intelligence of a high school graduate armed with just the right questions to ask the user in order to steer them down the desired path. This front-end application of AI is relatively inexpensive to implement and can be done rather quickly.
The Back-end
On the “back-end”, the use of Large Language Models (LLMs) with hooks into the company’s app or product can enable a key differentiator to enhance CX, acquire new customers and drive revenue growth. Think of an arbitrage engine combing the internet for specific data needed to support a list of options and create a recommendation, as a component of the company’s product offering. This back-end application of AI is more expensive to implement and there’s a cost for each use case. The ROI is tied to the business value of the use case and can be a key differentiator impacting a positive user experience.
Orchestration
Either way, front-end or back-end integration, the AI technology that is implemented will need to be trained – and continue to train itself – to enable the desired outcomes. In both instances, there exists a business process workflow. It is a “best practice” to identify the details around the workflow prior to implementing any AI technology, including the objectives, desired outcomes, and all the steps and stages along the customer journey.
Workflow Automation
After the workflow details are documented, the company can then automate the workflow. Today, there are several tools available for workflow automation, including Pega Systems, the market leader for enterprise BPO, as well as Camunda and Appian. Both Pega and Appian employ low-code tech in their Platform as a Service (PaaS) offerings. Camunda is open source, java-based code. These BPO tools also provide Robotics Process Automation (RPA) bots, as do other RPA bot providers such as Uipath. Ease-of-use and flexibility are the most critical criteria in deciding among the solution providers. Ease-of-use translates into a faster time to market and reduces the resource cost of the deployment.
AI’s Role
Today, the BPO platforms employ AI technology to streamline their deployment using a “blueprint” template that enables the user to drag and drop the components of the workflow. The embedded AI accelerates deployment, improves time to market, reduces the cost to deploy, and enables a joyful customer experience (ideally).
Additionally, these BPO platforms employ AI/Machine Learning techniques to glean insights from the historical data and performance metrics to learn, adapt and improve the processes. Sometime soon, BPO platforms will be fully self-optimizing. They will constantly refine its tasks/behavior based upon real-time inputs, without human intervention. The AI will significantly increase its accuracy and speed, translating to a higher propensity for the desired outcomes, such as an increase in conversion rates, for example. After all, acquiring customers and growing revenue is what business is all about.
Recipe For Change
The integration of AI and BPO will prove to be the key recipe for change, accelerating a company’s progress toward a true Digital Transformation. AI will make it even easier to deploy automation and will streamline a company’s business processes. Reduced friction. Enhanced user experience. Your customers will love you for it.